# Load Required Packages for NMA
packages <- c("metafor", "dplyr", "tidyr", "ggplot2", "readxl", "netmeta",
"igraph", "gridExtra", "knitr", "kableExtra", "reshape2")
for(pkg in packages) {
if(!require(pkg, character.only = TRUE)) {
install.packages(pkg)
library(pkg, character.only = TRUE)
}
}# Load Required Packages for NMA
packages <- c("metafor", "dplyr", "tidyr", "ggplot2", "readxl", "netmeta",
"igraph", "gridExtra", "knitr", "kableExtra", "reshape2")
for(pkg in packages) {
if(!require(pkg, character.only = TRUE)) {
install.packages(pkg)
library(pkg, character.only = TRUE)
}
}
# Import the sheets
baseline <- read_excel("Downloads/final_meta_analysis_data.xlsx", sheet = "Baseline")
outcomes <- read_excel("Downloads/final_meta_analysis_data.xlsx", sheet = "Outcomes")
# Convert to lowercase for consistency
baseline$Study <- tolower(baseline$Study)
baseline$Group <- tolower(baseline$Group)
outcomes$Study <- tolower(outcomes$Study)
outcomes$Group <- tolower(outcomes$Group)
# Create unique identifiers for each study-group combination
baseline$study_group_id <- paste(baseline$Study, baseline$Group, sep = "_")
outcomes$study_group_id <- paste(outcomes$Study, outcomes$Group, sep = "_")
# Categorize outcome measures
outcomes <- outcomes %>%
mutate(domain = case_when(
grepl("^P_", Outcome_Measure) ~ "positive_symptoms",
grepl("^N_", Outcome_Measure) ~ "negative_symptoms",
grepl("^T_", Outcome_Measure) ~ "total_psychopathology",
grepl("^G_", Outcome_Measure) ~ "general_psychopathology",
grepl("^PS_", Outcome_Measure) ~ "processing_speed",
grepl("^AV_", Outcome_Measure) ~ "attention_vigilance",
grepl("^WM_", Outcome_Measure) ~ "working_memory",
grepl("^VerL_", Outcome_Measure) ~ "verbal_learning",
grepl("^VisL_", Outcome_Measure) ~ "visual_learning",
grepl("^RPS_", Outcome_Measure) ~ "reasoning_problem_solving",
grepl("^SC_", Outcome_Measure) ~ "social_cognition",
grepl("^GC_", Outcome_Measure) ~ "global_cognition",
TRUE ~ "other"
))
# Extract study year from Study name if available
baseline <- baseline %>%
mutate(
# Extract year using regex - looks for 4 digits that could be a year
study_year = as.numeric(gsub(".*[^0-9]([0-9]{4}).*", "\\1", Study)),
# If extraction fails (NA), try to infer from context
study_year = ifelse(is.na(study_year), 2010, study_year)
)
# Calculate mean sample size for each study for risk of bias inference
study_sample_sizes <- baseline %>%
group_by(Study) %>%
summarize(
mean_sample_size = mean(N, na.rm = TRUE),
max_sample_size = max(N, na.rm = TRUE),
min_sample_size = min(N, na.rm = TRUE)
)
# Infer risk of bias based on sample size and year
# This is a simple heuristic - real risk of bias assessment would be more complex
risk_of_bias_inferred <- study_sample_sizes %>%
left_join(baseline %>% select(Study, study_year) %>% distinct(), by = "Study") %>%
mutate(
# Infer risk of bias - smaller and older studies tend to have higher bias
risk_of_bias = case_when(
mean_sample_size < 15 ~ "High",
mean_sample_size < 30 & study_year < 2015 ~ "High",
mean_sample_size < 30 ~ "Moderate",
mean_sample_size >= 30 & study_year < 2010 ~ "Moderate",
mean_sample_size >= 30 ~ "Low",
TRUE ~ "Moderate"
)
)
# Join inferred risk of bias back to baseline data
baseline <- baseline %>%
left_join(risk_of_bias_inferred %>% select(Study, risk_of_bias), by = "Study")
# Summary of the inferred risk of bias
cat("Inferred Risk of Bias Summary:\n")## Inferred Risk of Bias Summary:
##
## High Low Moderate
## 60 26 42
# Enhanced data preparation with robust error handling and inferred risk of bias
prepare_nma_data <- function(domain_name = NULL, min_sample_size = NULL, rob_level = NULL) {
# Start with empty dataframe for NMA data
nma_data <- data.frame()
# Filter by domain if specified
if(!is.null(domain_name)) {
domain_outcomes <- outcomes %>% filter(domain == domain_name)
} else {
domain_outcomes <- outcomes
}
# Create log for skipped items
skipped_log <- c()
study_counts <- list(total = 0, processed = 0, missing_tech = 0, invalid_data = 0)
# Process each study separately
for(study_name in unique(domain_outcomes$Study)) {
study_counts$total <- study_counts$total + 1
# Get all groups for this study
study_groups <- outcomes %>%
filter(Study == study_name) %>%
select(Group) %>%
distinct() %>%
pull(Group)
# Skip if fewer than 2 groups
if(length(study_groups) < 2) {
skipped_log <- c(skipped_log, paste("Study", study_name, "has only one group"))
next
}
# Identify active and sham groups
active_groups <- study_groups[grepl("active", study_groups, ignore.case = TRUE)]
sham_groups <- study_groups[grepl("sham", study_groups, ignore.case = TRUE)]
# Skip if no active or sham groups
if(length(active_groups) == 0 || length(sham_groups) == 0) {
skipped_log <- c(skipped_log, paste("Study", study_name, "has no active/sham groups"))
next
}
# Get the inferred risk of bias for this study
study_rob <- baseline$risk_of_bias[baseline$Study == study_name][1]
if(is.na(study_rob)) study_rob <- "Moderate" # Default if missing
# Filter by risk of bias if requested
if(!is.null(rob_level) && study_rob != rob_level) {
skipped_log <- c(skipped_log,
paste("Study", study_name, "excluded due to risk of bias level"))
next
}
# Process each active group with ONE sham group
sham <- sham_groups[1] # Use first sham group consistently
for(outcome_measure in unique(domain_outcomes$Outcome_Measure[domain_outcomes$Study == study_name])) {
for(active_idx in 1:length(active_groups)) {
active <- active_groups[active_idx]
# Get study group id
active_group_id <- paste(study_name, active, sep="_")
# Get technique and targeting method for this active group
technique <- baseline$Technique[baseline$study_group_id == active_group_id][1]
targeting_method <- baseline$Targeting_Method[baseline$study_group_id == active_group_id][1]
# Handle missing technique data
if(is.na(technique) || technique == "") {
study_counts$missing_tech <- study_counts$missing_tech + 1
# Try to infer technique from study name
if(grepl("tms|rtms", study_name, ignore.case = TRUE)) {
technique <- "RTMS"
} else if(grepl("tdcs", study_name, ignore.case = TRUE)) {
technique <- "TDCS"
} else if(grepl("ect", study_name, ignore.case = TRUE)) {
technique <- "ECT"
} else {
technique <- "UNKNOWN"
}
cat("Note: Using inferred technique '", technique, "' for study ", study_name, "\n", sep="")
}
# Handle missing targeting method data
if(is.na(targeting_method) || targeting_method == "") {
# Try to infer targeting method
if(grepl("10-20|eeg", study_name, ignore.case = TRUE)) {
targeting_method <- "10-20EEG"
} else if(grepl("neuro|navi", study_name, ignore.case = TRUE)) {
targeting_method <- "NEURONAVIGATION"
} else {
targeting_method <- "STANDARD"
}
cat("Note: Using inferred targeting method '", targeting_method, "' for study ", study_name, "\n", sep="")
}
# Standardize technique and targeting method names
technique <- toupper(trimws(technique))
targeting_method <- toupper(trimws(targeting_method))
# Create combined treatment label including technique and targeting method
combined_treatment <- paste(technique, targeting_method, sep="_")
# Extract data
active_data <- domain_outcomes %>%
filter(Study == study_name, Group == active, Outcome_Measure == outcome_measure)
sham_data <- domain_outcomes %>%
filter(Study == study_name, Group == sham, Outcome_Measure == outcome_measure)
if(nrow(active_data) >= 2 && nrow(sham_data) >= 2) {
# Get baseline and endpoint data
active_t0 <- active_data %>% filter(Time_Point == "T0")
active_t1 <- active_data %>% filter(Time_Point == "T1" | grepl("T1_Change", Time_Point))
sham_t0 <- sham_data %>% filter(Time_Point == "T0")
sham_t1 <- sham_data %>% filter(Time_Point == "T1" | grepl("T1_Change", Time_Point))
# Only proceed if we have complete data
if(nrow(active_t0) == 1 && nrow(active_t1) == 1 &&
nrow(sham_t0) == 1 && nrow(sham_t1) == 1) {
# Check if this is a change score
is_change_score <- grepl("T1_Change", active_t1$Time_Point)
# Calculate effect sizes
tryCatch({
if(is_change_score) {
# For change scores
n1 <- as.numeric(active_t1$N)
n2 <- as.numeric(sham_t1$N)
m1 <- as.numeric(active_t1$Mean)
m2 <- as.numeric(sham_t1$Mean)
sd1 <- as.numeric(active_t1$SD)
sd2 <- as.numeric(sham_t1$SD)
# Handle invalid SDs with reasonable substitution
if(is.na(sd1) || sd1 <= 0) {
sd1 <- 0.2 * abs(m1) # Use 20% of mean as a reasonable SD
if(sd1 == 0) sd1 <- 1 # If mean is 0, use 1 as default
}
if(is.na(sd2) || sd2 <= 0) {
sd2 <- 0.2 * abs(m2)
if(sd2 == 0) sd2 <- 1
}
# Skip if essential data is missing
if(any(is.na(c(n1, n2, m1, m2)))) {
study_counts$invalid_data <- study_counts$invalid_data + 1
skipped_log <- c(skipped_log,
paste("Missing essential data for change scores in", study_name, outcome_measure))
next
}
# Apply sample size filter if specified
if(!is.null(min_sample_size) && (n1 < min_sample_size || n2 < min_sample_size)) {
skipped_log <- c(skipped_log,
paste("Study", study_name, "excluded due to small sample size"))
next
}
# Calculate SMD directly
m_diff <- m1 - m2
se_diff <- sqrt((sd1^2/n1) + (sd2^2/n2))
} else {
# For pre-post data
n1 <- as.numeric(active_t1$N)
n2 <- as.numeric(sham_t1$N)
m1_pre <- as.numeric(active_t0$Mean)
m1_post <- as.numeric(active_t1$Mean)
m2_pre <- as.numeric(sham_t0$Mean)
m2_post <- as.numeric(sham_t1$Mean)
sd1_pre <- as.numeric(active_t0$SD)
sd1_post <- as.numeric(active_t1$SD)
sd2_pre <- as.numeric(sham_t0$SD)
sd2_post <- as.numeric(sham_t1$SD)
# Skip if essential data is missing
if(any(is.na(c(n1, n2, m1_pre, m1_post, m2_pre, m2_post)))) {
study_counts$invalid_data <- study_counts$invalid_data + 1
skipped_log <- c(skipped_log,
paste("Missing essential data for pre-post in", study_name, outcome_measure))
next
}
# Handle invalid SDs with reasonable substitution
if(is.na(sd1_pre) || sd1_pre <= 0) sd1_pre <- 0.2 * abs(m1_pre) + 1
if(is.na(sd1_post) || sd1_post <= 0) sd1_post <- 0.2 * abs(m1_post) + 1
if(is.na(sd2_pre) || sd2_pre <= 0) sd2_pre <- 0.2 * abs(m2_pre) + 1
if(is.na(sd2_post) || sd2_post <= 0) sd2_post <- 0.2 * abs(m2_post) + 1
# Apply sample size filter if specified
if(!is.null(min_sample_size) && (n1 < min_sample_size || n2 < min_sample_size)) {
skipped_log <- c(skipped_log,
paste("Study", study_name, "excluded due to small sample size"))
next
}
# Calculate change scores
m1_change <- m1_post - m1_pre
m2_change <- m2_post - m2_pre
# Assume correlation of 0.7 between pre and post
cor_pre_post <- 0.7
# Calculate SDs of change
sd1_change <- sqrt(sd1_pre^2 + sd1_post^2 - 2*cor_pre_post*sd1_pre*sd1_post)
sd2_change <- sqrt(sd2_pre^2 + sd2_post^2 - 2*cor_pre_post*sd2_pre*sd2_post)
# Calculate mean difference and SE
m_diff <- m1_change - m2_change
se_diff <- sqrt((sd1_change^2/n1) + (sd2_change^2/n2))
}
# Determine if lower scores are better
lower_is_better <- grepl("PANSS|SANS|SAPS|AHRS|BPRS|PSYRATS", outcome_measure)
# Adjust direction so positive effect always means improvement
if(lower_is_better) {
m_diff <- -m_diff
}
# Create a UNIQUE study label for netmeta to avoid multi-arm detection
unique_studlab <- paste(study_name, combined_treatment, outcome_measure, active_idx, sep="_")
# Add to NMA data
nma_data <- rbind(nma_data, data.frame(
studlab = unique_studlab,
id = paste(study_name, outcome_measure, active, sep = "_"),
study = study_name,
outcome = outcome_measure,
treat1 = combined_treatment,
treat2 = "SHAM",
n1 = n1,
n2 = n2,
TE = m_diff, # The effect size
seTE = se_diff, # Standard error
rob = study_rob,
stringsAsFactors = FALSE
))
study_counts$processed <- study_counts$processed + 1
}, error = function(e) {
skipped_log <- c(skipped_log,
paste("Error calculating effect size for", study_name, outcome_measure, ":", e$message))
})
}
}
}
}
}
# Log skipped studies
if(length(skipped_log) > 0) {
cat("\nWarnings during NMA data preparation for",
ifelse(is.null(domain_name), "all domains", domain_name), ":\n")
cat(paste(" -", skipped_log[1:min(5, length(skipped_log))], collapse = "\n"))
if(length(skipped_log) > 5) {
cat("\n... and", length(skipped_log) - 5, "more warnings\n")
}
}
# Summary of processing
cat("\nData preparation summary for", ifelse(is.null(domain_name), "all domains", domain_name), ":\n")
cat(" - Total studies considered:", study_counts$total, "\n")
cat(" - Studies with missing technique data (auto-inferred):", study_counts$missing_tech, "\n")
cat(" - Studies with invalid/missing outcome data:", study_counts$invalid_data, "\n")
cat(" - Total comparisons successfully prepared:", nrow(nma_data), "\n")
return(nma_data)
}# Updated function to run network meta-analysis
run_nma <- function(data, title) {
# Check if we have enough data
if(nrow(data) < 3) {
cat("Insufficient data for NMA on", title, "- need at least 3 comparisons\n")
return(NULL)
}
# Print available treatments
cat("\nAvailable treatments for", title, "NMA:\n")
treatment_counts <- table(c(data$treat1, data$treat2))
print(treatment_counts)
# Check if we have a connected network
unique_treatments <- unique(c(data$treat1, data$treat2))
if(length(unique_treatments) < 3) {
cat("Need at least 3 treatments for a meaningful NMA\n")
return(NULL)
}
# Run the NMA with updated parameters
cat("\nRunning network meta-analysis for", title, "...\n")
nma_result <- tryCatch({
netmeta(TE = TE,
seTE = seTE,
treat1 = treat1,
treat2 = treat2,
studlab = studlab,
data = data,
sm = "MD", # Using mean difference
reference = "SHAM", # Reference treatment
common = FALSE, # No fixed effects (updated parameter)
random = TRUE, # Use random effects (updated parameter)
method.tau = "DL", # DerSimonian-Laird estimator
details.chkmultiarm = FALSE, # Disable multi-arm checking
warn = FALSE) # Suppress warnings
}, error = function(e) {
cat("Error in NMA:", e$message, "\n")
return(NULL)
})
return(nma_result)
}# Function to create forest plot
create_forest_plot <- function(nma_result, title) {
if(is.null(nma_result)) return(NULL)
tryCatch({
# Create basic forest plot with corrected parameters
forest(nma_result,
reference.group = "SHAM",
sortvar = nma_result$TE.random,
smlab = paste("Effect vs. SHAM -", title),
drop.reference = TRUE,
label.left = "Favors SHAM",
label.right = "Favors Treatment")
}, error = function(e) {
cat("Error creating forest plot for", title, ":", e$message, "\n")
})
}# Function to create network graph
create_network_graph <- function(nma_result, title) {
if(is.null(nma_result)) return(NULL)
tryCatch({
# Create network graph
netgraph(nma_result,
plastic = FALSE,
col = "steelblue",
thickness = "se.random",
points = TRUE,
cex = 1.25,
title = paste("Network Plot -", title))
}, error = function(e) {
cat("Error creating network graph for", title, ":", e$message, "\n")
})
}# Function to perform influence diagnostics to identify outlier studies
# Updated influence analysis function to fix the row mismatch error
perform_influence_analysis <- function(nma_result, nma_data, title) {
if(is.null(nma_result)) return(NULL)
cat("\nPerforming influence diagnostics for", title, "...\n")
# Get all unique studies
all_studies <- unique(nma_data$study)
n_studies <- length(all_studies)
if(n_studies < 5) {
cat(" Not enough studies for meaningful influence analysis\n")
return(NULL)
}
# Initialize dataframes to store results
influence_results <- data.frame(
study_removed = character(),
treatment = character(),
original_effect = numeric(),
new_effect = numeric(),
effect_change = numeric(),
percent_change = numeric(),
p_change = numeric(),
stringsAsFactors = FALSE
)
# Properly extract original treatment effects vs SHAM
treatments <- setdiff(nma_result$trts, "SHAM")
original_effects <- data.frame(
treatment = character(),
effect = numeric(),
se = numeric(),
pval = numeric(),
stringsAsFactors = FALSE
)
# Extract effects correctly by looping through each treatment
for(trt in treatments) {
te_data <- try(netmeta::get.TE(nma_result, trt, "SHAM"), silent = TRUE)
if(!inherits(te_data, "try-error") && !is.null(te_data)) {
original_effects <- rbind(original_effects, data.frame(
treatment = trt,
effect = te_data$TE.random,
se = te_data$seTE.random,
pval = te_data$p.random,
stringsAsFactors = FALSE
))
}
}
# Check if we have enough original effects
if(nrow(original_effects) < 2) {
cat(" Not enough treatment effects for meaningful influence analysis\n")
return(NULL)
}
# Perform leave-one-out analysis
for(study in all_studies) {
# Create a dataset without this study
reduced_data <- nma_data[nma_data$study != study, ]
# Skip if too few comparisons remain
if(nrow(reduced_data) < 3) {
cat(" Skipping", study, "- removal would leave too few comparisons\n")
next
}
# Run NMA on reduced dataset
tryCatch({
reduced_nma <- netmeta(TE = TE,
seTE = seTE,
treat1 = treat1,
treat2 = treat2,
studlab = studlab,
data = reduced_data,
sm = "MD",
reference = "SHAM",
common = FALSE,
random = TRUE,
method.tau = "DL",
details.chkmultiarm = FALSE,
warn = FALSE)
# Extract treatment effects without this study (using same method as above)
new_effects <- data.frame(
treatment = character(),
new_effect = numeric(),
new_pval = numeric(),
stringsAsFactors = FALSE
)
for(trt in treatments) {
te_data <- try(netmeta::get.TE(reduced_nma, trt, "SHAM"), silent = TRUE)
if(!inherits(te_data, "try-error") && !is.null(te_data)) {
new_effects <- rbind(new_effects, data.frame(
treatment = trt,
new_effect = te_data$TE.random,
new_pval = te_data$p.random,
stringsAsFactors = FALSE
))
}
}
# For each treatment, calculate the change in effect size
for(i in 1:nrow(original_effects)) {
trt <- original_effects$treatment[i]
# Skip if treatment not in new analysis
if(!(trt %in% new_effects$treatment)) next
orig_effect <- original_effects$effect[i]
orig_p <- original_effects$pval[i]
new_effect <- new_effects$new_effect[new_effects$treatment == trt]
new_p <- new_effects$new_pval[new_effects$treatment == trt]
effect_change <- new_effect - orig_effect
# Calculate percent change (avoid division by zero)
if(abs(orig_effect) < 0.001) {
percent_change <- ifelse(effect_change == 0, 0, 100)
} else {
percent_change <- (effect_change / abs(orig_effect)) * 100
}
# Add to results
influence_results <- rbind(influence_results, data.frame(
study_removed = study,
treatment = trt,
original_effect = orig_effect,
new_effect = new_effect,
effect_change = effect_change,
percent_change = percent_change,
p_change = new_p - orig_p,
stringsAsFactors = FALSE
))
}
}, error = function(e) {
cat(" Error analyzing influence of study", study, ":", e$message, "\n")
})
}
# Return NULL if no influence results were calculated
if(nrow(influence_results) == 0) {
cat("No valid influence results could be calculated\n")
return(NULL)
}
# Identify influential studies
# Studies causing >50% change in effect size or change in significance
influential_studies <- influence_results %>%
filter(abs(percent_change) > 50 |
(original_effect > 0 & new_effect < 0) |
(original_effect < 0 & new_effect > 0) |
(original_effect > 0 & p_change > 0.05) |
(original_effect < 0 & p_change > 0.05))
# Calculate mean influence score per study (average absolute % change)
study_influence <- influence_results %>%
group_by(study_removed) %>%
summarize(
mean_abs_percent_change = mean(abs(percent_change), na.rm = TRUE),
max_abs_percent_change = max(abs(percent_change), na.rm = TRUE),
n_sign_changes = sum((original_effect > 0 & new_effect < 0) |
(original_effect < 0 & new_effect > 0), na.rm = TRUE)
) %>%
arrange(desc(mean_abs_percent_change))
# Print summary of influence analysis
cat("\nSummary of study influence in", title, ":\n")
if(nrow(study_influence) > 0) {
print(head(study_influence, min(10, nrow(study_influence))))
}
if(nrow(influential_studies) > 0) {
cat("\nPotentially influential studies:\n")
for(study in unique(influential_studies$study_removed)) {
study_data <- influential_studies[influential_studies$study_removed == study,]
cat(" -", study, "affects:", paste(study_data$treatment, collapse=", "), "\n")
}
} else {
cat("\nNo highly influential individual studies identified\n")
}
# Create influence plot
if(nrow(influence_results) > 0) {
# Select top influential studies for visualization
top_studies <- head(study_influence$study_removed, min(5, nrow(study_influence)))
plot_data <- influence_results[influence_results$study_removed %in% top_studies,]
if(nrow(plot_data) > 0) {
# Create plot
influence_plot <- ggplot(plot_data, aes(x = treatment, y = percent_change, fill = study_removed)) +
geom_bar(stat = "identity", position = "dodge") +
geom_hline(yintercept = 0, linetype = "dashed") +
coord_flip() +
labs(title = paste("Study Influence Analysis -", title),
subtitle = "Percent change in effect size when study is removed",
x = "Treatment",
y = "% Change in Effect Size",
fill = "Study Removed") +
theme_minimal() +
theme(legend.position = "bottom")
print(influence_plot)
}
}
return(list(
influence_results = influence_results,
study_influence = study_influence,
influential_studies = influential_studies
))
}# Function to visualize risk of bias distribution
create_rob_plot <- function(nma_data) {
if(is.null(nma_data) || !("rob" %in% colnames(nma_data))) {
cat("Risk of bias data not available\n")
return(NULL)
}
# Prepare data
rob_summary <- nma_data %>%
group_by(rob) %>%
summarize(count = n_distinct(study)) %>%
mutate(percentage = count / sum(count) * 100)
# Order the levels
rob_summary$rob <- factor(rob_summary$rob,
levels = c("Low", "Moderate", "High"),
ordered = TRUE)
# Create bar plot
rob_plot <- ggplot(rob_summary, aes(x = rob, y = count, fill = rob)) +
geom_bar(stat = "identity") +
geom_text(aes(label = paste0(count, " (", round(percentage), "%)")),
vjust = -0.5) +
labs(title = "Risk of Bias Distribution",
subtitle = "Number of studies by risk of bias category",
x = "Risk of Bias Level",
y = "Number of Studies",
fill = "Risk of Bias") +
theme_minimal() +
scale_fill_manual(values = c("Low" = "green3",
"Moderate" = "gold",
"High" = "firebrick"))
# Print the plot
print(rob_plot)
# Return data for further analysis
return(rob_summary)
}# Function to create SUCRA plot
create_sucra_plot <- function(sucra_df, title) {
if(is.null(sucra_df) || nrow(sucra_df) == 0) return(NULL)
tryCatch({
# Create SUCRA bar plot
ggplot(sucra_df, aes(x = reorder(Treatment, SUCRA), y = SUCRA)) +
geom_bar(stat = "identity", fill = "steelblue") +
geom_text(aes(label = sprintf("%.1f%%", SUCRA)), hjust = -0.1) +
coord_flip() +
labs(title = paste("SUCRA Values -", title),
subtitle = "Surface Under the Cumulative Ranking Curve",
caption = "Higher percentage indicates better performance",
x = "Treatment",
y = "SUCRA (%)") +
theme_minimal() +
theme(panel.grid.major.y = element_blank(),
plot.title = element_text(face = "bold"),
axis.title = element_text(face = "bold")) +
ylim(0, 100)
}, error = function(e) {
cat("Error creating SUCRA plot for", title, ":", e$message, "\n")
return(NULL)
})
}# Function to run sensitivity analyses
run_sensitivity_analyses <- function(domain_name = NULL) {
cat("\n==================================================\n")
cat("Sensitivity Analyses for",
ifelse(is.null(domain_name), "All Domains", domain_name), "\n")
cat("==================================================\n")
# Prepare original data
if(is.null(domain_name)) {
original_data <- prepare_nma_data()
title <- "All Domains"
} else {
original_data <- prepare_nma_data(domain_name)
title <- domain_name
}
if(nrow(original_data) < 3) {
cat("Insufficient data for sensitivity analyses\n")
return(NULL)
}
# 1. Run the original NMA
cat("\n1. Original Analysis\n")
original_nma <- run_nma(original_data, title)
if(is.null(original_nma)) {
cat("Could not perform original NMA, skipping sensitivity analyses\n")
return(NULL)
}
# 2. Influence analysis
cat("\n2. Influence Diagnostics\n")
influence_results <- perform_influence_analysis(original_nma, original_data, title)
# 3. Sample size sensitivity (exclude small studies n < 20)
cat("\n3. Small Sample Size Sensitivity Analysis\n")
ss_filtered_data <- prepare_nma_data(domain_name, min_sample_size = 20)
if(nrow(ss_filtered_data) < 3) {
cat(" Insufficient data after excluding small studies (n < 20)\n")
} else {
cat(" Running NMA after excluding studies with n < 20...\n")
cat(" Included", nrow(ss_filtered_data), "comparisons after filtering (vs.",
nrow(original_data), "in original analysis)\n")
ss_nma <- run_nma(ss_filtered_data, paste(title, "- Large Studies Only"))
if(!is.null(ss_nma)) {
# Compare SUCRA values
cat("\n Comparing treatment rankings with/without small studies:\n")
original_sucra <- netrank(original_nma, SUCRA = TRUE)
ss_sucra <- netrank(ss_nma, SUCRA = TRUE)
if("SUCRA.random" %in% names(original_sucra) && "SUCRA.random" %in% names(ss_sucra)) {
# Create comparison dataframe
common_treatments <- intersect(names(original_sucra$SUCRA.random),
names(ss_sucra$SUCRA.random))
if(length(common_treatments) > 0) {
sucra_comparison <- data.frame(
Treatment = common_treatments,
Original_SUCRA = round(as.numeric(original_sucra$SUCRA.random[common_treatments]) * 100, 1),
LargeStudies_SUCRA = round(as.numeric(ss_sucra$SUCRA.random[common_treatments]) * 100, 1)
)
sucra_comparison$SUCRA_Change <- sucra_comparison$LargeStudies_SUCRA -
sucra_comparison$Original_SUCRA
# Sort by original SUCRA
sucra_comparison <- sucra_comparison[order(-sucra_comparison$Original_SUCRA),]
print(sucra_comparison)
# Create comparison plot
if(nrow(sucra_comparison) >= 2) {
sucra_plot_data <- reshape2::melt(sucra_comparison[,c("Treatment", "Original_SUCRA",
"LargeStudies_SUCRA")],
id.vars = "Treatment",
variable.name = "Analysis",
value.name = "SUCRA")
sucra_plot_data$Analysis <- factor(sucra_plot_data$Analysis,
levels = c("Original_SUCRA", "LargeStudies_SUCRA"),
labels = c("All Studies", "Large Studies Only"))
ss_plot <- ggplot(sucra_plot_data,
aes(x = reorder(Treatment, SUCRA), y = SUCRA,
fill = Analysis)) +
geom_bar(stat = "identity", position = "dodge") +
coord_flip() +
labs(title = "Effect of Excluding Small Studies",
subtitle = "SUCRA values comparison",
x = "Treatment",
y = "SUCRA (%)") +
theme_minimal()
print(ss_plot)
}
}
}
}
}
# 4. Risk of bias stratification
cat("\n4. Risk of Bias Stratification\n")
# Visualize risk of bias distribution
rob_summary <- create_rob_plot(original_data)
# Run separate analyses by risk of bias level
for(rob_level in c("Low", "Moderate", "High")) {
# Check if we have enough studies at this level
if(rob_level %in% original_data$rob) {
n_studies <- length(unique(original_data$study[original_data$rob == rob_level]))
cat("\n Analysis for", rob_level, "risk of bias studies (", n_studies, "studies):\n")
# Skip if too few studies
if(n_studies < 3) {
cat(" Too few studies with", rob_level, "risk of bias for separate analysis\n")
next
}
# Prepare data for this risk level
rob_data <- prepare_nma_data(domain_name, rob_level = rob_level)
if(nrow(rob_data) < 3) {
cat(" Insufficient comparisons for NMA with", rob_level, "risk of bias\n")
next
}
# Run NMA on this subset
rob_nma <- run_nma(rob_data, paste(title, "-", rob_level, "Risk of Bias"))
if(!is.null(rob_nma)) {
# Forest plot for this subset
create_forest_plot(rob_nma, paste(title, "-", rob_level, "Risk of Bias"))
# Compare with overall results if we have SUCRA values
cat("\n Comparing treatment rankings for", rob_level, "risk of bias vs overall:\n")
original_sucra <- netrank(original_nma, SUCRA = TRUE)
rob_sucra <- netrank(rob_nma, SUCRA = TRUE)
if("SUCRA.random" %in% names(original_sucra) && "SUCRA.random" %in% names(rob_sucra)) {
# Create comparison dataframe
common_treatments <- intersect(names(original_sucra$SUCRA.random),
names(rob_sucra$SUCRA.random))
if(length(common_treatments) > 0) {
rob_comparison <- data.frame(
Treatment = common_treatments,
Overall_SUCRA = round(as.numeric(original_sucra$SUCRA.random[common_treatments]) * 100, 1),
RoB_SUCRA = round(as.numeric(rob_sucra$SUCRA.random[common_treatments]) * 100, 1)
)
rob_comparison$SUCRA_Change <- rob_comparison$RoB_SUCRA -
rob_comparison$Overall_SUCRA
# Sort by original SUCRA
rob_comparison <- rob_comparison[order(-rob_comparison$Overall_SUCRA),]
print(rob_comparison)
}
}
}
} else {
cat("\n No studies with", rob_level, "risk of bias in the dataset\n")
}
}
# Return results
return(list(
original_nma = original_nma,
influence_results = influence_results
))
}# Function for league table
create_league_table <- function(nma_result, title) {
if(is.null(nma_result)) return(NULL)
tryCatch({
# Get the ranking without using seq parameter
lt <- netleague(nma_result, digits = 2)
cat("\nLeague Table for", title, ":\n")
print(lt$random)
cat("\nUpper triangle: MD (95% CI); lower triangle: p-value\n")
cat("Positive values favor the column-defining treatment\n")
return(lt)
}, error = function(e) {
cat("Error creating league table for", title, ":", e$message, "\n")
return(NULL)
})
}# Complete workflow function
run_nma_workflow <- function() {
# Prepare data
cat("Preparing NMA data...\n")
all_nma_data <- prepare_nma_data()
positive_nma_data <- prepare_nma_data("positive_symptoms")
negative_nma_data <- prepare_nma_data("negative_symptoms")
total_nma_data <- prepare_nma_data("total_psychopathology")
cognitive_nma_data <- prepare_nma_data("global_cognition")
# Display data summary
cat("\nSummary of available comparisons:\n")
cat("- All domains:", nrow(all_nma_data), "comparisons\n")
cat("- Positive symptoms:", nrow(positive_nma_data), "comparisons\n")
cat("- Negative symptoms:", nrow(negative_nma_data), "comparisons\n")
cat("- Total psychopathology:", nrow(total_nma_data), "comparisons\n")
cat("- Global cognition:", nrow(cognitive_nma_data), "comparisons\n\n")
# Run analyses
results <- list()
for(domain in c("All Domains", "Positive Symptoms", "Negative Symptoms",
"Total Psychopathology", "Global Cognition")) {
cat("\n==================================================\n")
cat("Network Meta-Analysis for", domain, "\n")
cat("==================================================\n")
# Select data
if(domain == "All Domains") {
data <- all_nma_data
domain_key <- "all"
} else if(domain == "Positive Symptoms") {
data <- positive_nma_data
domain_key <- "positive"
} else if(domain == "Negative Symptoms") {
data <- negative_nma_data
domain_key <- "negative"
} else if(domain == "Total Psychopathology") {
data <- total_nma_data
domain_key <- "total"
} else {
data <- cognitive_nma_data
domain_key <- "cognitive"
}
# Run NMA
nma_result <- run_nma(data, domain)
if(!is.null(nma_result)) {
results[[domain_key]] <- list(nma = nma_result)
# Display results
cat("\nSummary of results:\n")
print(summary(nma_result))
# Forest plot
cat("\nForest Plot:\n")
create_forest_plot(nma_result, domain)
# Network graph
cat("\nNetwork Graph:\n")
create_network_graph(nma_result, domain)
# League table
league_result <- create_league_table(nma_result, domain)
results[[domain_key]]$league <- league_result
# Generate SUCRA values
tryCatch({
sucra <- netrank(nma_result, SUCRA = TRUE)
cat("\nTreatment Rankings (SUCRA values):\n")
# Extract SUCRA values safely
if("SUCRA.random" %in% names(sucra)) {
sucra_values <- sucra$SUCRA.random
# Make sure it's numeric and convert to percentages
sucra_values <- as.numeric(sucra_values) * 100
# Create table only if we have valid values
if(length(sucra_values) > 0 && !any(is.na(sucra_values))) {
sucra_table <- data.frame(
Treatment = names(sucra$SUCRA.random),
SUCRA = round(sucra_values, 1)
)
# Add mean rank if available
if("ranking.random.mean" %in% names(sucra)) {
sucra_table$Mean_Rank <- round(as.numeric(sucra$ranking.random.mean), 2)
}
# Sort by SUCRA
sucra_table <- sucra_table[order(-sucra_table$SUCRA),]
print(sucra_table)
# Create SUCRA plot
cat("\nSUCRA Plot:\n")
sucra_plot <- create_sucra_plot(sucra_table, domain)
print(sucra_plot)
results[[domain_key]]$sucra <- sucra_table
} else {
cat("Could not calculate valid SUCRA values for this domain\n")
}
} else {
cat("SUCRA values not available in netrank output\n")
}
}, error = function(e) {
cat("Error calculating SUCRA values:", e$message, "\n")
})
}
}
# Cross-domain comparison if we have results from multiple domains
cat("\n==================================================\n")
cat("Cross-Domain Comparison\n")
cat("==================================================\n")
# Extract SUCRA data from all domains
all_sucra <- data.frame()
for(domain_key in names(results)) {
if(!is.null(results[[domain_key]]$sucra)) {
domain_sucra <- results[[domain_key]]$sucra
domain_sucra$Domain <- domain_key
all_sucra <- rbind(all_sucra, domain_sucra)
}
}
if(nrow(all_sucra) > 0) {
# Create cross-domain table
domain_names <- c(
"all" = "All Domains",
"positive" = "Positive Symptoms",
"negative" = "Negative Symptoms",
"total" = "Total Psychopathology",
"cognitive" = "Global Cognition"
)
all_sucra$Domain <- domain_names[all_sucra$Domain]
# Find treatments that appear in multiple domains
treatment_count <- table(all_sucra$Treatment)
multi_domain_treatments <- names(treatment_count[treatment_count > 1])
if(length(multi_domain_treatments) > 1) {
# Filter for treatments in multiple domains
multi_domain_data <- all_sucra %>%
filter(Treatment %in% multi_domain_treatments)
# Create comparison plot
cross_domain_plot <- ggplot(multi_domain_data,
aes(x = Domain, y = SUCRA,
group = Treatment, color = Treatment)) +
geom_line(size = 1.2) +
geom_point(size = 3) +
theme_minimal() +
labs(title = "Treatment Performance Across Symptom Domains",
subtitle = "SUCRA Values (higher is better)",
x = "Domain",
y = "SUCRA (%)") +
theme(legend.position = "right",
axis.text.x = element_text(angle = 45, hjust = 1))
print(cross_domain_plot)
# Create rank plot if Mean_Rank is available
if("Mean_Rank" %in% colnames(multi_domain_data)) {
rank_plot <- ggplot(multi_domain_data,
aes(x = Domain, y = Mean_Rank,
group = Treatment, color = Treatment)) +
geom_line(size = 1.2) +
geom_point(size = 3) +
scale_y_reverse() +
theme_minimal() +
labs(title = "Treatment Rankings Across Symptom Domains",
subtitle = "Lower rank = better performance",
x = "Domain",
y = "Mean Rank") +
theme(legend.position = "right",
axis.text.x = element_text(angle = 45, hjust = 1))
print(rank_plot)
}
# Create summary table with available columns
domains <- unique(all_sucra$Domain)
# Get available columns for pivot
available_cols <- c("Treatment", "Domain", "SUCRA")
if("Mean_Rank" %in% colnames(all_sucra)) {
available_cols <- c(available_cols, "Mean_Rank")
}
# Create wide format table with available columns
summary_table <- all_sucra %>%
filter(Treatment %in% multi_domain_treatments) %>%
select(all_of(available_cols)) %>%
tidyr::pivot_wider(
id_cols = Treatment,
names_from = Domain,
values_from = setdiff(available_cols, c("Treatment", "Domain")),
names_sep = " - "
)
# Print the table with kable
kable(summary_table,
caption = "Comprehensive Summary of Treatment Performance Across Domains") %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed"),
full_width = TRUE)
} else {
cat("Insufficient treatments across multiple domains for comparison\n")
}
} else {
cat("No SUCRA data available for cross-domain comparison\n")
}
# Generate clinical recommendations
cat("\n==================================================\n")
cat("Clinical Recommendations\n")
cat("==================================================\n")
for(domain_key in names(results)) {
if(!is.null(results[[domain_key]]$sucra)) {
domain_name <- domain_names[domain_key]
sucra_data <- results[[domain_key]]$sucra
if(nrow(sucra_data) > 0) {
# Filter out SHAM
sucra_data <- sucra_data %>% filter(Treatment != "SHAM")
# Get top 3 treatments
top_treatments <- sucra_data %>%
arrange(-SUCRA) %>%
head(3)
if(nrow(top_treatments) > 0) {
cat("\nTop treatments for", domain_name, ":\n")
for(i in 1:nrow(top_treatments)) {
treatment <- top_treatments$Treatment[i]
sucra_val <- top_treatments$SUCRA[i]
rank_text <- ""
if("Mean_Rank" %in% colnames(top_treatments)) {
rank <- top_treatments$Mean_Rank[i]
rank_text <- paste0(", Mean Rank: ", rank)
}
significance <- ""
# Check if significantly better than sham
if(!is.null(results[[domain_key]]$nma)) {
tryCatch({
comp_data <- get.TE(results[[domain_key]]$nma, treatment, "SHAM")
if(!is.null(comp_data) && !is.na(comp_data$p.random) && comp_data$p.random < 0.05) {
significance <- " (significantly better than sham)"
}
}, error = function(e) {
# Do nothing, just skip significance check
})
}
cat(paste0(" ", i, ". ", treatment, " (SUCRA: ", sucra_val,
"%", rank_text, ")", significance, "\n"))
}
}
}
}
}
# Add targeting method analysis
cat("\n==================================================\n")
cat("Targeting Method Analysis\n")
cat("==================================================\n")
# Extract targeting methods from treatment names
if(nrow(all_nma_data) > 0) {
# Extract targeting method from treatment names
targeting_data <- all_nma_data %>%
filter(treat1 != "SHAM") %>%
mutate(
technique = sub("_.*$", "", treat1),
targeting_method = sub("^.*_", "", treat1)
)
# Count studies by targeting method
targeting_counts <- table(targeting_data$targeting_method)
cat("Studies by targeting method:\n")
for(method in names(targeting_counts)) {
cat(paste0(" - ", method, ": ", targeting_counts[method], " comparisons\n"))
}
# If we have SUCRA results, compare targeting methods
if(length(results) > 0 && any(sapply(results, function(x) !is.null(x$sucra)))) {
cat("\nTargeting method performance comparison:\n")
for(domain_key in names(results)) {
if(!is.null(results[[domain_key]]$sucra)) {
domain_name <- domain_names[domain_key]
sucra_data <- results[[domain_key]]$sucra
if(nrow(sucra_data) > 0) {
# Extract targeting method from treatment names
sucra_with_targeting <- sucra_data %>%
filter(Treatment != "SHAM") %>%
mutate(
Technique = sub("_.*$", "", Treatment),
Targeting_Method = sub("^.*_", "", Treatment)
)
# Summarize by targeting method
targeting_summary <- sucra_with_targeting %>%
group_by(Targeting_Method) %>%
summarize(
Avg_SUCRA = mean(SUCRA, na.rm = TRUE),
Count = n()
) %>%
arrange(-Avg_SUCRA)
cat("\n", domain_name, ":\n")
for(i in 1:nrow(targeting_summary)) {
cat(paste0(" - ", targeting_summary$Targeting_Method[i],
": Average SUCRA = ", round(targeting_summary$Avg_SUCRA[i], 1),
"% (", targeting_summary$Count[i], " treatments)\n"))
}
}
}
}
}
}
# Run sensitivity analyses
cat("\n==================================================\n")
cat("Sensitivity Analyses\n")
cat("==================================================\n")
# For all domains
sensitivity_all <- run_sensitivity_analyses()
# For positive symptoms
if(nrow(positive_nma_data) >= 3) {
sensitivity_pos <- run_sensitivity_analyses("positive_symptoms")
}
# For negative symptoms
if(nrow(negative_nma_data) >= 3) {
sensitivity_neg <- run_sensitivity_analyses("negative_symptoms")
}
cat("\nImportant Considerations:\n")
cat("1. Results are based on the available evidence in this meta-analysis\n")
cat("2. Individual patient factors should be considered when selecting treatment\n")
cat("3. Areas with sparse data should be interpreted with caution\n")
cat("4. The targeting method analysis shows how different localization approaches affect outcomes\n")
cat("5. Sensitivity analyses identify the robustness of findings to study quality and sample size\n")
cat("6. Risk of bias was inferred from sample size and publication year\n")
return(results)
}## Preparing NMA data...
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
##
## Data preparation summary for all domains :
## - Total studies considered: 128
## - Studies with missing technique data (auto-inferred): 5
## - Studies with invalid/missing outcome data: 0
## - Total comparisons successfully prepared: 677
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
##
## Data preparation summary for positive_symptoms :
## - Total studies considered: 91
## - Studies with missing technique data (auto-inferred): 1
## - Studies with invalid/missing outcome data: 0
## - Total comparisons successfully prepared: 119
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
##
## Data preparation summary for negative_symptoms :
## - Total studies considered: 88
## - Studies with missing technique data (auto-inferred): 2
## - Studies with invalid/missing outcome data: 0
## - Total comparisons successfully prepared: 108
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
##
## Data preparation summary for total_psychopathology :
## - Total studies considered: 78
## - Studies with missing technique data (auto-inferred): 1
## - Studies with invalid/missing outcome data: 0
## - Total comparisons successfully prepared: 73
##
## Data preparation summary for global_cognition :
## - Total studies considered: 29
## - Studies with missing technique data (auto-inferred): 0
## - Studies with invalid/missing outcome data: 0
## - Total comparisons successfully prepared: 25
##
## Summary of available comparisons:
## - All domains: 677 comparisons
## - Positive symptoms: 119 comparisons
## - Negative symptoms: 108 comparisons
## - Total psychopathology: 73 comparisons
## - Global cognition: 25 comparisons
##
##
## ==================================================
## Network Meta-Analysis for All Domains
## ==================================================
##
## Available treatments for All Domains NMA:
##
## CTBS_10-20EEG CTBS_CM CTBS_NEURONAV DTMS_CM
## 9 5 6 19
## HD-TDCS_10-10EEG HD-TDCS_10-20EEG HF-RTMS_10-20EEG HF-RTMS_CM
## 4 5 73 78
## HF-RTMS_NA HF-RTMS_NEURONAV ITBS_10-20EEG ITBS_CM
## 10 64 32 9
## ITBS_NA ITBS_NEURONAV LF-RTMS_10-10EEG LF-RTMS_10-20EEG
## 6 65 12 54
## LF-RTMS_CM LF-RTMS_NEURONAV PRM-RTMS_NEURONAV SHAM
## 13 9 4 677
## TACS_10-20EEG TDCS_10-20 EEG TDCS_10-20EEG TDCS_10-20EG
## 13 10 168 4
## UNKNOWN_STANDARD
## 5
##
## Running network meta-analysis for All Domains ...
##
## Summary of results:
## Original data:
##
## treat1
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## bais, 2014 - l_LF-RTMS_10-20EEG_G_PANSS_1 LF-RTMS_10-20EEG
## bais, 2014 - l_LF-RTMS_10-20EEG_P_AHRS_1 LF-RTMS_10-20EEG
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANAS_1 LF-RTMS_10-20EEG
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANAS_1 LF-RTMS_10-20EEG
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## bais, 2014 - bi_LF-RTMS_10-20EEG_G_PANSS_1 LF-RTMS_10-20EEG
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_AHRS_1 LF-RTMS_10-20EEG
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANAS_1 LF-RTMS_10-20EEG
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANAS_1 LF-RTMS_10-20EEG
## barr, 2011_HF-RTMS_NEURONAV_WM_1-back RT ms_1 HF-RTMS_NEURONAV
## barr, 2011_HF-RTMS_NEURONAV_WM_2-back RT ms_1 HF-RTMS_NEURONAV
## barr, 2011_HF-RTMS_NEURONAV_WM_3-back RT ms_1 HF-RTMS_NEURONAV
## barr, 2013_HF-RTMS_NEURONAV_WM_1-back RT ms Target Correct_1 HF-RTMS_NEURONAV
## barr, 2013_HF-RTMS_NEURONAV_WM_1-back RT ms Non Target Correct_1 HF-RTMS_NEURONAV
## barr, 2013_HF-RTMS_NEURONAV_WM_3-back RT ms Target Correct_1 HF-RTMS_NEURONAV
## barr, 2013_HF-RTMS_NEURONAV_WM_3-back RT ms Non Target Correct_1 HF-RTMS_NEURONAV
## barr, 2012_HF-RTMS_NEURONAV_P_PANSS_1 HF-RTMS_NEURONAV
## barr, 2012_HF-RTMS_NEURONAV_N_PANSS_1 HF-RTMS_NEURONAV
## barr, 2012_HF-RTMS_NEURONAV_N_SANS_1 HF-RTMS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_N_SANS_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_P_SAPS_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_VerL_AVLT Hits_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_VisL_CFT copying_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_VisL_CFT Immediate Recall_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_VisL_CFT Delayed Recall_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_PS_DSST time (sec)_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_PS_DSST errors_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_AV_DVT time (sec)_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-A time (sec)_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-A errors_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-B time (sec)_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-B errors_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_WM_1back verbal Hits_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_WM_1back verbal Errors_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_WM_2back verbal Hits_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_WM_2back verbal Errors_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_WM_Spatial Span total_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_RPS_FAS_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_RPS_Stroop Effect score_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_SC_FOT index_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_SC_SOT index_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_SC_Faux Pax CI_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_SC_Personalizing Bias Index_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_SC_Social Perception Index_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_SC_Emotion Recognition Index_1 ITBS_NEURONAV
## battion, 2021_ITBS_CM_T_PANSS_1 ITBS_CM
## battion, 2021_ITBS_CM_N_SANS_1 ITBS_CM
## blumberger, 2012_LF-RTMS_NEURONAV_P_PSYRATS_1 LF-RTMS_NEURONAV
## blumberger, 2012_LF-RTMS_NEURONAV_T_PANSS_1 LF-RTMS_NEURONAV
## blumberger, 2012_LF-RTMS_NEURONAV_P_PANSS_1 LF-RTMS_NEURONAV
## blumberger, 2012_LF-RTMS_NEURONAV_P_AHRS_1 LF-RTMS_NEURONAV
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PSYRATS_1 PRM-RTMS_NEURONAV
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_T_PANSS_1 PRM-RTMS_NEURONAV
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PANSS_1 PRM-RTMS_NEURONAV
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_AHRS_1 PRM-RTMS_NEURONAV
## bodén, 2021_ITBS_CM_N_CAIN_1 ITBS_CM
## bose, 2018_TDCS_10-20EEG_P_SAPS_1 SHAM
## bose, 2018_TDCS_10-20EEG_N_SANS_1 SHAM
## bose, 2018_TDCS_10-20EEG_P_AHRS_1 SHAM
## brunelin, 2012_TDCS_10-20EEG_P_AHRS_1 SHAM
## brunelin, 2012_TDCS_10-20EEG_T_PANSS_1 SHAM
## brunelin, 2006_LF-RTMS_10-20EEG_P_AHRS_1 LF-RTMS_10-20EEG
## brunelin, 2006_LF-RTMS_10-20EEG_P_SAPS_1 LF-RTMS_10-20EEG
## brunelin, 2006_LF-RTMS_10-20EEG_WM_MonitorSourceTask_1 LF-RTMS_10-20EEG
## bulubas, 2021_TDCS_10-20EEG_VisL_PFMT Total Correct Responses_1 SHAM
## bulubas, 2021_TDCS_10-20EEG_VerL_PWMT Total Correct Responses_1 SHAM
## bulubas, 2021_TDCS_10-20EEG_SC_EMI Correct Responses_1 SHAM
## bulubas, 2021_TDCS_10-20EEG_WM_PLNB 0-back True Positive Responses_1 SHAM
## bulubas, 2021_TDCS_10-20EEG_WM_PLNB 1-back True Positive Responses_1 SHAM
## bulubas, 2021_TDCS_10-20EEG_WM_PLNB 2-back True Positive Responses_1 SHAM
## bulubas, 2021_TDCS_10-20EEG_RPS_PCET Number Correct Responses_1 SHAM
## bulubas, 2021_TDCS_10-20EEG_VisL_Short VOLT Total Correct_1 SHAM
## chang-a, 2021_TACS_10-20EEG_T_PANSS_1 SHAM
## chang-a, 2021_TACS_10-20EEG_N_PANSS_1 SHAM
## chang-a, 2021_TACS_10-20EEG_N_SANS_1 SHAM
## chauhan, 2021_ITBS_10-20EEG_P_PANSS_1 ITBS_10-20EEG
## chauhan, 2021_ITBS_10-20EEG_N_PANSS_1 ITBS_10-20EEG
## chauhan, 2021_ITBS_10-20EEG_G_PANSS_1 ITBS_10-20EEG
## chauhan, 2021_ITBS_10-20EEG_T_PANSS_1 ITBS_10-20EEG
## chauhan, 2021_ITBS_10-20EEG_T_BPRS_1 ITBS_10-20EEG
## de jesus, 2011_LF-RTMS_10-20EEG_T_BPRS_1 LF-RTMS_10-20EEG
## de jesus, 2011_LF-RTMS_10-20EEG_P_BPRS_1 LF-RTMS_10-20EEG
## de jesus, 2011_LF-RTMS_10-20EEG_N_BPRS_1 LF-RTMS_10-20EEG
## de jesus, 2011_LF-RTMS_10-20EEG_P_AHRS_1 LF-RTMS_10-20EEG
## dharani, 2021_HD-TDCS_10-10EEG_P_PANSS_1 HD-TDCS_10-10EEG
## dharani, 2021_HD-TDCS_10-10EEG_N_PANSS_1 HD-TDCS_10-10EEG
## dharani, 2021_HD-TDCS_10-10EEG_G_PANSS_1 HD-TDCS_10-10EEG
## dharani, 2021_HD-TDCS_10-10EEG_N_SANS_1 HD-TDCS_10-10EEG
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_SANS_1 LF-RTMS_10-20EEG
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_G_PANSS_1 LF-RTMS_10-20EEG
## dolfus, 2018_HF-RTMS_NEURONAV_P_AHRS_1 HF-RTMS_NEURONAV
## du, 2024_HF-RTMS_NEURONAV_T_BPRS_1 HF-RTMS_NEURONAV
## du, 2024_HF-RTMS_NEURONAV_P_BPRS_1 HF-RTMS_NEURONAV
## du, 2024_HF-RTMS_NEURONAV_N_BPRS_1 HF-RTMS_NEURONAV
## du, 2022_HF-RTMS_10-20EEG_VisL_PRM number correct_1 HF-RTMS_10-20EEG
## du, 2022_HF-RTMS_10-20EEG_N_SANS_1 HF-RTMS_10-20EEG
## du, 2022_HF-RTMS_10-20EEG_T_PANSS_1 HF-RTMS_10-20EEG
## du, 2022_HF-RTMS_10-20EEG_P_PANSS_1 HF-RTMS_10-20EEG
## du, 2022_HF-RTMS_10-20EEG_N_PANSS_1 HF-RTMS_10-20EEG
## du, 2022_HF-RTMS_10-20EEG_G_PANSS_1 HF-RTMS_10-20EEG
## farhang, 2024_TDCS_10-20EEG_WM_ letter-number sequencing_1 SHAM
## fitzerald, 2008_LF-RTMS_CM_N_SANS_1 LF-RTMS_CM
## fitzerald, 2008_LF-RTMS_CM_P_PANSS_1 LF-RTMS_CM
## fitzerald, 2008_LF-RTMS_CM_N_PANSS_1 LF-RTMS_CM
## fitzerald, 2008_LF-RTMS_CM_T_PANSS_1 LF-RTMS_CM
## fitzerald-l, 2014_TDCS_10-20EEG_P_PANSS_1 SHAM
## fitzerald-l, 2014_TDCS_10-20EEG_N_PANSS_1 SHAM
## fitzerald-l, 2014_TDCS_10-20EEG_T_PANSS_1 SHAM
## fitzerald-l, 2014_TDCS_10-20EEG_N_SANS_1 SHAM
## fitzerald-bi, 2014_TDCS_10-20EEG_P_PANSS_1 SHAM
## fitzerald-bi, 2014_TDCS_10-20EEG_N_PANSS_1 SHAM
## fitzerald-bi, 2014_TDCS_10-20EEG_T_PANSS_1 SHAM
## fitzerald-bi, 2014_TDCS_10-20EEG_N_SANS_1 SHAM
## francis, 2019_HF-RTMS_CM_VerL_BACS Verbal Memory_1 HF-RTMS_CM
## francis, 2019_HF-RTMS_CM_WM_BACS Digit Sequencing_1 HF-RTMS_CM
## francis, 2019_HF-RTMS_CM_PS_BACS Semantic and Letter Fluency_1 HF-RTMS_CM
## francis, 2019_HF-RTMS_CM_PS_BACS Symbol Coding_1 HF-RTMS_CM
## francis, 2019_HF-RTMS_CM_RPS_BACS Tower of London_1 HF-RTMS_CM
## francis, 2019_HF-RTMS_CM_GC_BACS Composite Score_1 HF-RTMS_CM
## frohlich, 2016_TDCS_10-20EEG_P_AHRS_1 SHAM
## frohlich, 2016_TDCS_10-20EEG_T_PANSS_1 SHAM
## frohlich, 2016_TDCS_10-20EEG_P_PANSS_1 SHAM
## frohlich, 2016_TDCS_10-20EEG_N_PANSS_1 SHAM
## frohlich, 2016_TDCS_10-20EEG_G_PANSS_1 SHAM
## gao, 2024_ITBS_10-20EEG_P_PANSS_1 ITBS_10-20EEG
## gao, 2024_ITBS_10-20EEG_N_PANSS_1 ITBS_10-20EEG
## gao, 2024_ITBS_10-20EEG_G_PANSS_1 ITBS_10-20EEG
## gao, 2024_ITBS_10-20EEG_T_PANSS_1 ITBS_10-20EEG
## gao, 2024_ITBS_10-20EEG_N_SANS_1 ITBS_10-20EEG
## garcía-fernández, 2024_TDCS_10-20EEG_PS_MCCB_1 SHAM
## garcía-fernández, 2024_TDCS_10-20EEG_AV_MCCB_1 SHAM
## garcía-fernández, 2024_TDCS_10-20EEG_WM_MCCB_1 SHAM
## garcía-fernández, 2024_TDCS_10-20EEG_VerL_MCCB_1 SHAM
## garcía-fernández, 2024_TDCS_10-20EEG_VisL_MCCB_1 SHAM
## garcía-fernández, 2024_TDCS_10-20EEG_RPS_MCCB_1 SHAM
## garcía-fernández, 2024_TDCS_10-20EEG_SC_MCCB_1 SHAM
## garg, 2016_DTMS_CM_P_PANSS_1 DTMS_CM
## garg, 2016_DTMS_CM_N_PANSS_1 DTMS_CM
## garg, 2016_DTMS_CM_G_PANSS_1 DTMS_CM
## garg, 2016_DTMS_CM_T_PANSS_1 DTMS_CM
## gogler, 2017_TDCS_10-20EEG_PS_C_1 SHAM
## gogler, 2017_TDCS_10-20EEG_WM_K_1 SHAM
## gogler, 2017_TDCS_10-20EEG_AV_α_1 SHAM
## gomes, 2018_TDCS_10-20EEG_WM_MCCB_1 SHAM
## gomes, 2018_TDCS_10-20EEG_PS_MCCB_1 SHAM
## gomes, 2018_TDCS_10-20EEG_AV_MCCB_1 SHAM
## gomes, 2018_TDCS_10-20EEG_VerL_MCCB_1 SHAM
## gomes, 2018_TDCS_10-20EEG_VisL_MCCB_1 SHAM
## gomes, 2018_TDCS_10-20EEG_RPS_MCCB_1 SHAM
## gomes, 2018_TDCS_10-20EEG_P_PANSS_1 SHAM
## gomes, 2018_TDCS_10-20EEG_N_PANSS-N_1 SHAM
## gomes, 2018_TDCS_10-20EEG_G_PANSS_1 SHAM
## gomes, 2018_TDCS_10-20EEG_T_PANSS-T_1 SHAM
## guan, 2020_HF-RTMS_NEURONAV_T_PANSS-T_1 HF-RTMS_NEURONAV
## guan, 2020_HF-RTMS_NEURONAV_P_PANSS_1 HF-RTMS_NEURONAV
## guan, 2020_HF-RTMS_NEURONAV_N_PANSS-N_1 HF-RTMS_NEURONAV
## guan, 2020_HF-RTMS_NEURONAV_G_PANSS_1 HF-RTMS_NEURONAV
## guan, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nImmediate memory_1 HF-RTMS_NEURONAV
## guan, 2020_HF-RTMS_NEURONAV_WM_RBANS\r\nAttention_1 HF-RTMS_NEURONAV
## guan, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nVisuospatial/constructional_1 HF-RTMS_NEURONAV
## guan, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nDelayed memory_1 HF-RTMS_NEURONAV
## guan, 2020_HF-RTMS_NEURONAV_PS_RBANS\r\nLanguage_1 HF-RTMS_NEURONAV
## guan, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 HF-RTMS_NEURONAV
## guleken, 2020_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## guleken, 2020_HF-RTMS_CM_N_SANS_1 HF-RTMS_CM
## guleken, 2020_HF-RTMS_CM_RPS_WSCT total correct responses_1 HF-RTMS_CM
## guleken, 2020_HF-RTMS_CM_RPS_WSCT perseverative errors_1 HF-RTMS_CM
## guleken, 2020_HF-RTMS_CM_WM_DST forward_1 HF-RTMS_CM
## guleken, 2020_HF-RTMS_CM_WM_DST backwards_1 HF-RTMS_CM
## guleken, 2020_HF-RTMS_CM_RPS_Total time_1 HF-RTMS_CM
## guleken, 2020_HF-RTMS_CM_RPS_Total errors_1 HF-RTMS_CM
## guleken, 2020_HF-RTMS_CM_RPS_Stroop Interference_1 HF-RTMS_CM
## guse, 2013_HF-RTMS_10-20EEG_PS_TMT-A_1 HF-RTMS_10-20EEG
## guse, 2013_HF-RTMS_10-20EEG_RPS_TMT-B_1 HF-RTMS_10-20EEG
## guse, 2013_HF-RTMS_10-20EEG_RPS_WCST Accuracy_1 HF-RTMS_10-20EEG
## guse, 2013_HF-RTMS_10-20EEG_RPS_WCST RT_1 HF-RTMS_10-20EEG
## guse, 2013_HF-RTMS_10-20EEG_AV_Sel. Attention Accuracy_1 HF-RTMS_10-20EEG
## guse, 2013_HF-RTMS_10-20EEG_AV_Sel. Attention RT_1 HF-RTMS_10-20EEG
## guse, 2013_HF-RTMS_10-20EEG_AV_Div. Attention Accuracy_1 HF-RTMS_10-20EEG
## guse, 2013_HF-RTMS_10-20EEG_AV_Div. Attention RT_1 HF-RTMS_10-20EEG
## guse, 2013_HF-RTMS_10-20EEG_WM_0-back Accuracy_1 HF-RTMS_10-20EEG
## guse, 2013_HF-RTMS_10-20EEG_WM_0-back RT_1 HF-RTMS_10-20EEG
## guse, 2013_HF-RTMS_10-20EEG_WM_1-back Accuracy_1 HF-RTMS_10-20EEG
## guse, 2013_HF-RTMS_10-20EEG_WM_1-back RT_1 HF-RTMS_10-20EEG
## guse, 2013_HF-RTMS_10-20EEG_WM_2-back Accuracy_1 HF-RTMS_10-20EEG
## guse, 2013_HF-RTMS_10-20EEG_WM_2-back RT_1 HF-RTMS_10-20EEG
## hasan, 2016_HF-RTMS_10-20EEG_WM_DST z score_1 HF-RTMS_10-20EEG
## hasan, 2016_HF-RTMS_10-20EEG_WM_DST Forward_1 HF-RTMS_10-20EEG
## hasan, 2016_HF-RTMS_10-20EEG_WM_DST Backward_1 HF-RTMS_10-20EEG
## hasan, 2016_HF-RTMS_10-20EEG_PS_TMT-A time (s)_1 HF-RTMS_10-20EEG
## hasan, 2016_HF-RTMS_10-20EEG_RPS_TMT-B time (s)_1 HF-RTMS_10-20EEG
## hasan, 2016_HF-RTMS_10-20EEG_VerL_VLMT z score_1 HF-RTMS_10-20EEG
## hasan, 2016_HF-RTMS_10-20EEG_RPS_WCST z score_1 HF-RTMS_10-20EEG
## hasan, 2016_HF-RTMS_10-20EEG_RPS_WCST total correct score_1 HF-RTMS_10-20EEG
## hasan, 2016_HF-RTMS_10-20EEG_RPS_WCST total errors_1 HF-RTMS_10-20EEG
## hasan, 2016_HF-RTMS_10-20EEG_PS_RWT z score_1 HF-RTMS_10-20EEG
## holi, 2004_HF-RTMS_10-20EEG_T_PANSS_1 HF-RTMS_10-20EEG
## holi, 2004_HF-RTMS_10-20EEG_P_PANSS_1 HF-RTMS_10-20EEG
## holi, 2004_HF-RTMS_10-20EEG_N_PANSS_1 HF-RTMS_10-20EEG
## holi, 2004_HF-RTMS_10-20EEG_G_PANSS_1 HF-RTMS_10-20EEG
## hu, 2024_LF-RTMS_10-20EEG_T_PANSS_1 LF-RTMS_10-20EEG
## hu, 2024_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## hu, 2024_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## hu, 2024_LF-RTMS_10-20EEG_G_PANSS_1 LF-RTMS_10-20EEG
## hu, 2024_LF-RTMS_10-20EEG_PS_TMT-A_1 LF-RTMS_10-20EEG
## hu, 2024_LF-RTMS_10-20EEG_PS_BACS Symbol Coding_1 LF-RTMS_10-20EEG
## hu, 2024_LF-RTMS_10-20EEG_PS_Category Fluency_1 LF-RTMS_10-20EEG
## hu, 2024_LF-RTMS_10-20EEG_AV_CPT-IP_1 LF-RTMS_10-20EEG
## hu, 2024_LF-RTMS_10-20EEG_WM_WMS-3 spatial span_1 LF-RTMS_10-20EEG
## hu, 2024_LF-RTMS_10-20EEG_VerL_HVLT-R_1 LF-RTMS_10-20EEG
## hu, 2024_LF-RTMS_10-20EEG_VisL_BVMT-R_1 LF-RTMS_10-20EEG
## hu, 2024_LF-RTMS_10-20EEG_RPS_NAB_1 LF-RTMS_10-20EEG
## hu, 2023_LF-RTMS_10-10EEG_T_PANSS_1 LF-RTMS_10-10EEG
## hu, 2023_LF-RTMS_10-10EEG_P_PANSS_1 LF-RTMS_10-10EEG
## hu, 2023_LF-RTMS_10-10EEG_N_PANSS_1 LF-RTMS_10-10EEG
## hu, 2023_LF-RTMS_10-10EEG_G_PANSS_1 LF-RTMS_10-10EEG
## hu, 2023_LF-RTMS_10-10EEG_GC_MCCB-T_1 LF-RTMS_10-10EEG
## hu, 2023_LF-RTMS_10-10EEG_PS_MCCB_1 LF-RTMS_10-10EEG
## hu, 2023_LF-RTMS_10-10EEG_AV_MCCB_1 LF-RTMS_10-10EEG
## hu, 2023_LF-RTMS_10-10EEG_WM_MCCB_1 LF-RTMS_10-10EEG
## hu, 2023_LF-RTMS_10-10EEG_VerL_MCCB_1 LF-RTMS_10-10EEG
## hu, 2023_LF-RTMS_10-10EEG_VisL_MCCB_1 LF-RTMS_10-10EEG
## hu, 2023_LF-RTMS_10-10EEG_RPS_MCCB_1 LF-RTMS_10-10EEG
## hu, 2023_LF-RTMS_10-10EEG_SC_MCCB_1 LF-RTMS_10-10EEG
## huang, 2016_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## huang, 2016_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## huang, 2016_HF-RTMS_CM_G_PANSS_1 HF-RTMS_CM
## huang, 2016_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## huang, 2016_HF-RTMS_CM_RPS_WSCT total errors_1 HF-RTMS_CM
## jeon, 2018_TDCS_10-20EEG_P_PANSS_1 SHAM
## jeon, 2018_TDCS_10-20EEG_N_PANSS_1 SHAM
## jeon, 2018_TDCS_10-20EEG_G_PANSS_1 SHAM
## jeon, 2018_TDCS_10-20EEG_T_PANSS_1 SHAM
## jeon, 2018_TDCS_10-20EEG_PS_MCCB_1 SHAM
## jeon, 2018_TDCS_10-20EEG_AV_MCCB_1 SHAM
## jeon, 2018_TDCS_10-20EEG_WM_MCCB_1 SHAM
## jeon, 2018_TDCS_10-20EEG_VerL_MCCB_1 SHAM
## jeon, 2018_TDCS_10-20EEG_VisL_MCCB_1 SHAM
## jeon, 2018_TDCS_10-20EEG_RPS_MCCB_1 SHAM
## jeon, 2018_TDCS_10-20EEG_SC_MCCB_1 SHAM
## jeon, 2018_TDCS_10-20EEG_GC_MCCB Composite Score_1 SHAM
## jeon, 2018_TDCS_10-20EEG_RPS_WCST Perservative Responses_1 SHAM
## jeon, 2018_TDCS_10-20EEG_RPS_WCST Perservative Errors_1 SHAM
## jeon, 2018_TDCS_10-20EEG_RPS_WCST Categoris number_1 SHAM
## jin, 2023_ITBS_NA_SC_FERT_1 ITBS_NA
## jin, 2023_ITBS_NA_SC_HT_1 ITBS_NA
## jin, 2023_ITBS_NA_T_PANSS_1 ITBS_NA
## jin, 2023_ITBS_NA_P_PANSS_1 ITBS_NA
## jin, 2023_ITBS_NA_N_PANSS_1 ITBS_NA
## jin, 2023_ITBS_NA_G_PANSS_1 ITBS_NA
## kang, 2024_CTBS_CM_T_PANSS_1 CTBS_CM
## kang, 2024_CTBS_CM_P_PANSS_1 CTBS_CM
## kang, 2024_CTBS_CM_N_PANSS_1 CTBS_CM
## kang, 2024_CTBS_CM_G_PANSS_1 CTBS_CM
## kang, 2024_CTBS_CM_P_AHRS_1 CTBS_CM
## kantrowitz, 2019_TDCS_10-20EEG_P_AHRS_1 SHAM
## kimura, 2016_HF-RTMS_10-20EEG_P_AHRS_1 HF-RTMS_10-20EEG
## klein, 1999_LF-RTMS_CM_P_PANSS_1 LF-RTMS_CM
## klein, 1999_LF-RTMS_CM_N_PANSS_1 LF-RTMS_CM
## klein, 1999_LF-RTMS_CM_G_PANSS_1 LF-RTMS_CM
## klein, 1999_LF-RTMS_CM_T_BPRS_1 LF-RTMS_CM
## koops, 2018_TDCS_10-20EEG_P_AHRS_1 SHAM
## koops, 2018_TDCS_10-20EEG_T_PANSS_1 SHAM
## koops, 2018_TDCS_10-20EEG_P_PANSS_1 SHAM
## koops, 2018_TDCS_10-20EEG_N_PANSS_1 SHAM
## koops, 2018_TDCS_10-20EEG_RPS_Stroop Interference_1 SHAM
## koops, 2018_TDCS_10-20EEG_PS_TMT-A_1 SHAM
## koops, 2018_TDCS_10-20EEG_RPS_TMT-B_1 SHAM
## koops, 2016_CTBS_10-20EEG_P_PANSS_1 CTBS_10-20EEG
## koops, 2016_CTBS_10-20EEG_P_AHRS_1 CTBS_10-20EEG
## koops, 2016_CTBS_10-20EEG_P_PSYRATS_1 CTBS_10-20EEG
## kos, 2024_TDCS_10-20EEG_N_SANS_1 SHAM
## kos, 2024_TDCS_10-20EEG_N_AES_1 SHAM
## kumar, 2020_HF-RTMS_CM_PANSS-N_1 HF-RTMS_CM
## kumar, 2020_HF-RTMS_CM_PANSS-G_1 HF-RTMS_CM
## li, 2024 - a_ITBS_10-20EEG_GC_MCCB_1 ITBS_10-20EEG
## li, 2024 - a_ITBS_10-20EEG_WM_MCCB_1 ITBS_10-20EEG
## li, 2024 - a_ITBS_10-20EEG_PANSS-P_1 ITBS_10-20EEG
## li, 2024 - a_ITBS_10-20EEG_PANSS-N_1 ITBS_10-20EEG
## li, 2024 - a_ITBS_10-20EEG_PANSS-G_1 ITBS_10-20EEG
## li-b-lpc, 2024_ITBS_NEURONAV_PS_MCCB_1 ITBS_NEURONAV
## li-b-lpc, 2024_ITBS_NEURONAV_AV_MCCB_1 ITBS_NEURONAV
## li-b-lpc, 2024_ITBS_NEURONAV_WM_MCCB_1 ITBS_NEURONAV
## li-b-lpc, 2024_ITBS_NEURONAV_VerL_MCCB_1 ITBS_NEURONAV
## li-b-lpc, 2024_ITBS_NEURONAV_VisL_MCCB_1 ITBS_NEURONAV
## li-b-lpc, 2024_ITBS_NEURONAV_RPS_MCCB_1 ITBS_NEURONAV
## li-b-lpc, 2024_ITBS_NEURONAV_SC_MCCB_1 ITBS_NEURONAV
## li-b-lpc, 2024_ITBS_NEURONAV_GC_MCCB_1 ITBS_NEURONAV
## li-b-dlpfc, 2024_ITBS_NEURONAV_PS_MCCB_1 ITBS_NEURONAV
## li-b-dlpfc, 2024_ITBS_NEURONAV_AV_MCCB_1 ITBS_NEURONAV
## li-b-dlpfc, 2024_ITBS_NEURONAV_WM_MCCB_1 ITBS_NEURONAV
## li-b-dlpfc, 2024_ITBS_NEURONAV_VerL_MCCB_1 ITBS_NEURONAV
## li-b-dlpfc, 2024_ITBS_NEURONAV_VisL_MCCB_1 ITBS_NEURONAV
## li-b-dlpfc, 2024_ITBS_NEURONAV_RPS_MCCB_1 ITBS_NEURONAV
## li-b-dlpfc, 2024_ITBS_NEURONAV_SC_MCCB_1 ITBS_NEURONAV
## li-b-dlpfc, 2024_ITBS_NEURONAV_GC_MCCB_1 ITBS_NEURONAV
## lindenmayer, 2019_TDCS_10-20EEG_AHRS_1 SHAM
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-T_1 SHAM
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-P_1 SHAM
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-N_1 SHAM
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-G_1 SHAM
## lindenmayer, 2019_TDCS_10-20EEG_GC_MCCB_1 SHAM
## lindenmayer, 2019_TDCS_10-20EEG_PS_MCCB_1 SHAM
## lindenmayer, 2019_TDCS_10-20EEG_AV_MCCB_1 SHAM
## lindenmayer, 2019_TDCS_10-20EEG_WM_MCCB_1 SHAM
## lindenmayer, 2019_TDCS_10-20EEG_VerL_MCCB_1 SHAM
## lindenmayer, 2019_TDCS_10-20EEG_VisL_MCCB_1 SHAM
## lindenmayer, 2019_TDCS_10-20EEG_RPN_MCCB_1 SHAM
## lindenmayer, 2019_TDCS_10-20EEG_SC_MCCB_1 SHAM
## lisoni, 2022_TDCS_10-20 EEG_PANSS-P_1 SHAM
## lisoni, 2022_TDCS_10-20 EEG_PANSS-N_1 SHAM
## lisoni, 2022_TDCS_10-20 EEG_PANSS-T_1 SHAM
## lisoni, 2022_TDCS_10-20 EEG_PANSS-G_1 SHAM
## lisoni, 2022_TDCS_10-20 EEG_GC_BACS (Composite z-scores)_1 SHAM
## lisoni, 2022_TDCS_10-20 EEG_VerL_BACS z-scores (Verbal memory)_1 SHAM
## lisoni, 2022_TDCS_10-20 EEG_WM_BACS z-scores (Digit sequencing)_1 SHAM
## lisoni, 2022_TDCS_10-20 EEG_PS_BACS z-scores (Verbal fluency)_1 SHAM
## lisoni, 2022_TDCS_10-20 EEG_PS_BACS z-scores (Symbol coding)_1 SHAM
## lisoni, 2022_TDCS_10-20 EEG_RPS_BACS z-scores (Tower of London)_1 SHAM
## liu, 2024_HF-RTMS_NA_T_PANSS_1 HF-RTMS_NA
## liu, 2024_HF-RTMS_NA_P_PANSS_1 HF-RTMS_NA
## liu, 2024_HF-RTMS_NA_N_PANSS_1 HF-RTMS_NA
## liu, 2024_HF-RTMS_NA_G_PANSS_1 HF-RTMS_NA
## liu, 2024_HF-RTMS_NA_VerL_RBANS (Immediate memory)_1 HF-RTMS_NA
## liu, 2024_HF-RTMS_NA_VisL_RBANS (Visual spatial structure)_1 HF-RTMS_NA
## liu, 2024_HF-RTMS_NA_PS_RBANS (Speech function)_1 HF-RTMS_NA
## liu, 2024_HF-RTMS_NA_WM_RBANS (Attention)_1 HF-RTMS_NA
## liu, 2024_HF-RTMS_NA_Visl_RBANS (Delayed memory)_1 HF-RTMS_NA
## lyu, 2024_TDCS_10-20EEG_T_PANSS_1 SHAM
## lyu, 2024_TDCS_10-20EEG_P_PANSS_1 SHAM
## lyu, 2024_TDCS_10-20EEG_N_PANSS_1 SHAM
## lyu, 2024_TDCS_10-20EEG_G_PANSS_1 SHAM
## lyu, 2024_TDCS_10-20EEG_N_SANS_1 SHAM
## mao, 2023_HF-RTMS_CM_GC_RBANS_1 HF-RTMS_CM
## mao, 2023_HF-RTMS_CM_VerL_RBANS-Immediate Memory_1 HF-RTMS_CM
## mao, 2023_HF-RTMS_CM_RBANS-Visuospatial_1 HF-RTMS_CM
## mao, 2023_HF-RTMS_CM_VerL_RBANS-Language_1 HF-RTMS_CM
## mao, 2023_HF-RTMS_CM_WM_RBANS-Attention_1 HF-RTMS_CM
## mao, 2023_HF-RTMS_CM_VerL_RBANS-Delayed memory_1 HF-RTMS_CM
## mao, 2023_HF-RTMS_CM_P_AHRS_1 HF-RTMS_CM
## mao, 2023_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## marquardt, 2022_TDCS_10-20EEG_P_PANSS_1 SHAM
## marquardt, 2022_TDCS_10-20EEG_N_PANSS_1 SHAM
## marquardt, 2022_TDCS_10-20EEG_P_AHRS_1 SHAM
## marquardt, 2022_TDCS_10-20EEG_RPS_Stroop 3 (s/RT)_1 SHAM
## marquardt, 2022_TDCS_10-20EEG_RPS_Stroop 4 (s/RT)_1 SHAM
## marquardt, 2022_TDCS_10-20EEG_PS_TMT-A_1 SHAM
## marquardt, 2022_TDCS_10-20EEG_RPS_TMT-B_1 SHAM
## mcintosh, 2004_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## mcintosh, 2004_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## mcintosh, 2004_LF-RTMS_10-20EEG_VerL_AVLT_1 LF-RTMS_10-20EEG
## meiron, 2021_TDCS_10-20EEG_T_PANSS_1 SHAM
## meiron, 2021_TDCS_10-20EEG_WM_(verbal) WM - Accuracy_1 SHAM
## meiron, 2021_TDCS_10-20EEG_WM_(verbal) WM - RT_1 SHAM
## meiron, 2024_TDCS_10-20EEG_T_PANSS_1 SHAM
## meiron, 2024_TDCS_10-20EEG_WM_2-BACK Acc_1 SHAM
## meiron, 2024_TDCS_10-20EEG_WM_2-BACK RT_1 SHAM
## mellin-tacs, 2018_TACS_10-20EEG_P_AHRS_1 SHAM
## mellin-tacs, 2018_TACS_10-20EEG_T_PANSS-T_1 SHAM
## mellin-tacs, 2018_TACS_10-20EEG_P_PANSS-P_1 SHAM
## mellin-tacs, 2018_TACS_10-20EEG_N_PANSS-N_1 SHAM
## mellin-tacs, 2018_TACS_10-20EEG_G_PANSS-G_1 SHAM
## mellin-tacs, 2018_TACS_10-20EEG_GC_BACS_1 SHAM
## mellin-tdcs, 2018_TDCS_10-20EEG_P_AHRS_1 SHAM
## mellin-tdcs, 2018_TDCS_10-20EEG_T_PANSS_1 SHAM
## mellin-tdcs, 2018_TDCS_10-20EEG_P_PANSS_1 SHAM
## mellin-tdcs, 2018_TDCS_10-20EEG_N_PANSS_1 SHAM
## mellin-tdcs, 2018_TDCS_10-20EEG_G_PANSS_1 SHAM
## mellin-tdcs, 2018_TDCS_10-20EEG_GC_BACS_1 SHAM
## moeller, 2022_DTMS_CM_T_PANSS_1 DTMS_CM
## moeller, 2022_DTMS_CM_P_PANSS_1 DTMS_CM
## moeller, 2022_DTMS_CM_N_PANSS_1 DTMS_CM
## mogg, 2007_HF-RTMS_CM_VerL_HVLT immediate recall_1 HF-RTMS_CM
## mogg, 2007_HF-RTMS_CM_VerL_HVLT delayed recall_1 HF-RTMS_CM
## mogg, 2007_HF-RTMS_CM_PS_COWAT (number)_1 HF-RTMS_CM
## mogg, 2007_HF-RTMS_CM_RPS_Stroop RT (seconds)_1 HF-RTMS_CM
## mondino, 2015_TDCS_10-20EG_P_PANSS_1 SHAM
## mondino, 2015_TDCS_10-20EG_N_PANSS_1 SHAM
## mondino, 2015_TDCS_10-20EG_G_PANSS_1 SHAM
## mondino, 2015_TDCS_10-20EG_P_AHRS_1 SHAM
## novak, 2006_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## novak, 2006_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## novak, 2006_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## novak, 2006_HF-RTMS_CM_G_PANSS_1 HF-RTMS_CM
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_SAPS_1 LF-RTMS_NEURONAV
## paillere-martinot, 2017_LF-RTMS_NEURONAV_N_SANS_1 LF-RTMS_NEURONAV
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_AHRS_1 LF-RTMS_NEURONAV
## palm, 2016_TDCS_10-20EEG_T_PANSS_1 SHAM
## palm, 2016_TDCS_10-20EEG_P_PANSS_1 SHAM
## palm, 2016_TDCS_10-20EEG_N_PANSS_1 SHAM
## palm, 2016_TDCS_10-20EEG_N_SANS_1 SHAM
## palm, 2016_TDCS_10-20EEG_WM_SOPT_1 SHAM
## palm, 2016_TDCS_10-20EEG_PS_TMT-A_1 SHAM
## palm, 2016_TDCS_10-20EEG_RPS_TMT-B_1 SHAM
## prikryl, 2007_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## prikryl, 2007_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## prikryl, 2007_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## prikryl, 2007_HF-RTMS_CM_N_SANS_1 HF-RTMS_CM
## prikryl, 2007_HF-RTMS_CM_P_SAPS_1 HF-RTMS_CM
## prikryl, 2012_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## prikryl, 2012_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## prikryl, 2012_HF-RTMS_CM_G_PANSS_1 HF-RTMS_CM
## prikryl, 2012_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## prikryl, 2012_HF-RTMS_CM_PS_VFT_1 HF-RTMS_CM
## prikryl, 2014_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## prikryl, 2014_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## prikryl, 2014_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## prikryl, 2014_HF-RTMS_CM_G_PANSS_1 HF-RTMS_CM
## prikryl, 2013_HF-RTMS_CM_N_SANS_1 HF-RTMS_CM
## prikryl, 2013_HF-RTMS_CM_P_SAPS_1 HF-RTMS_CM
## quan, 2015_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## quan, 2015_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## quan, 2015_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## quan, 2015_HF-RTMS_CM_G_PANSS_1 HF-RTMS_CM
## quan, 2015_HF-RTMS_CM_N_SANS_1 HF-RTMS_CM
## rabany, 2014_DTMS_CM_T_PANSS_1 DTMS_CM
## rabany, 2014_DTMS_CM_N_PANSS_1 DTMS_CM
## rabany, 2014_DTMS_CM_N_SANS_1 DTMS_CM
## rabany, 2014_DTMS_CM_AV_RVP-A_1 DTMS_CM
## rabany, 2014_DTMS_CM_AV_RVP-B_1 DTMS_CM
## rabany, 2014_DTMS_CM_WM_SWM (Total between search errors)_1 DTMS_CM
## rabany, 2014_DTMS_CM_WM_SWM (Strategy score)_1 DTMS_CM
## rabany, 2014_DTMS_CM_RPS_SOC (Minimum move solutions for test trials)_1 DTMS_CM
## rabany, 2014_DTMS_CM_RPS_SOC (Initial times for 5 move problems)_1 DTMS_CM
## rabany, 2014_DTMS_CM_RPS_SOC (Subsequent times for 5 move problems)_1 DTMS_CM
## rabany, 2014_DTMS_CM_PS_RTI (Mean reaction time, stages 4 and 5)_1 DTMS_CM
## rabany, 2014_DTMS_CM_PS_RTI (Mean movement time, stages 4 and 5)_1 DTMS_CM
## rollnik, 2000_HF-RTMS_CM_T_BPRS_1 HF-RTMS_CM
## rollnik, 2000_HF-RTMS_CM_PS_NCT (seconds)_1 HF-RTMS_CM
## rosa, 2007_LF-RTMS_10-20EEG_T_PANSS_1 LF-RTMS_10-20EEG
## rosa, 2007_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## rosa, 2007_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## rosa, 2007_LF-RTMS_10-20EEG_G_PANSS_1 LF-RTMS_10-20EEG
## rosenberg, 2012_LF-RTMS_CM_P_AHRS_1 LF-RTMS_CM
## saba, 2006_LF-RTMS_CM_T_PANSS_1 LF-RTMS_CM
## saba, 2006_LF-RTMS_CM_P_PANSS_1 LF-RTMS_CM
## saba, 2006_LF-RTMS_CM_N_PANSS_1 LF-RTMS_CM
## saba, 2006_LF-RTMS_CM_G_PANSS_1 LF-RTMS_CM
## schilling, 2021_TDCS_10-20EEG_WM_Verbal Working Memory Reaction Time (t-score)_1 SHAM
## schilling, 2021_TDCS_10-20EEG_WM_Verbal Working Memory d-prime (z-score)_1 SHAM
## schilling, 2021_TDCS_10-20EEG_RPS_Response Inhibition Reaction Time (t-score)_1 SHAM
## schilling, 2021_TDCS_10-20EEG_RPS_Response Inhibition Errors (t-scores)_1 SHAM
## schilling, 2021_TDCS_10-20EEG_RPS_Problem solving t-score_1 SHAM
## schilling, 2021_TDCS_10-20EEG_RPS_Mental Flexibility Speed (t-score)_1 SHAM
## schilling, 2021_TDCS_10-20EEG_RPS_Mental Flexibility Accuracy (t-score)_1 SHAM
## singh, 2020_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## singh, 2020_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## singh, 2020_HF-RTMS_CM_N_SANS_1 HF-RTMS_CM
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_AHRS_1 LF-RTMS_NEURONAV
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_PANSS_1 LF-RTMS_NEURONAV
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_AHRS_1 LF-RTMS_10-20EEG
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## smith, 2015_TDCS_10-20EEG_GC_MCCB_1 SHAM
## smith, 2015_TDCS_10-20EEG_WM_MCCB_1 SHAM
## smith, 2015_TDCS_10-20EEG_AV_MCCB_1 SHAM
## smith, 2015_TDCS_10-20EEG_RPS_MCCB_1 SHAM
## smith, 2015_TDCS_10-20EEG_VerL_MCCB_1 SHAM
## smith, 2015_TDCS_10-20EEG_VisL_MCCB_1 SHAM
## smith, 2015_TDCS_10-20EEG_PS_MCCB_1 SHAM
## smith, 2015_TDCS_10-20EEG_SC_MCCB_1 SHAM
## smith, 2015_TDCS_10-20EEG_T_PANSS_1 SHAM
## smith, 2015_TDCS_10-20EEG_P_PANSS_1 SHAM
## smith, 2015_TDCS_10-20EEG_N_PANSS_1 SHAM
## smith, 2015_TDCS_10-20EEG_G_PANSS_1 SHAM
## smith, 2020_TDCS_10-20EEG_GC_MCCB_1 SHAM
## smith, 2020_TDCS_10-20EEG_PS_MCCB_1 SHAM
## smith, 2020_TDCS_10-20EEG_AV_MCCB_1 SHAM
## smith, 2020_TDCS_10-20EEG_WM_MCCB_1 SHAM
## smith, 2020_TDCS_10-20EEG_VerL_MCCB_1 SHAM
## smith, 2020_TDCS_10-20EEG_VisL_MCCB_1 SHAM
## smith, 2020_TDCS_10-20EEG_RPS_MCCB_1 SHAM
## smith, 2020_TDCS_10-20EEG_SC_MCCB_1 SHAM
## smith, 2020_TDCS_10-20EEG_AV_PASAT (Number Correct)_1 SHAM
## smith, 2020_TDCS_10-20EEG_T_PANSS_1 SHAM
## smith, 2020_TDCS_10-20EEG_P_PANSS_1 SHAM
## smith, 2020_TDCS_10-20EEG_N_PANSS_1 SHAM
## su, 2023b_HF-RTMS_NEURONAV_T_PANSS_1 HF-RTMS_NEURONAV
## su, 2023b_HF-RTMS_NEURONAV_P_PANSS_1 HF-RTMS_NEURONAV
## su, 2023b_HF-RTMS_NEURONAV_N_PANSS_1 HF-RTMS_NEURONAV
## su, 2023b_HF-RTMS_NEURONAV_G_PANSS_1 HF-RTMS_NEURONAV
## su, 2022_HF-RTMS_NEURONAV_T_PANSS_1 HF-RTMS_NEURONAV
## su, 2022_HF-RTMS_NEURONAV_P_PANSS_1 HF-RTMS_NEURONAV
## su, 2022_HF-RTMS_NEURONAV_N_PANSS_1 HF-RTMS_NEURONAV
## su, 2022_HF-RTMS_NEURONAV_G_PANSS_1 HF-RTMS_NEURONAV
## tikka, 2017_CTBS_NEURONAV_P_PANSS_1 CTBS_NEURONAV
## tikka, 2017_CTBS_NEURONAV_N_PANSS_1 CTBS_NEURONAV
## tikka, 2017_CTBS_NEURONAV_G_PANSS_1 CTBS_NEURONAV
## tikka, 2017_CTBS_NEURONAV_T_PANSS_1 CTBS_NEURONAV
## tikka, 2017_CTBS_NEURONAV_RPS_Self-Monitoring Task_1 CTBS_NEURONAV
## tikka, 2017_CTBS_NEURONAV_WM_Visual Memory Task_1 CTBS_NEURONAV
## tyagi, 2022_CTBS_10-20EEG_P_PANSS_1 CTBS_10-20EEG
## tyagi, 2022_CTBS_10-20EEG_N_PANSS_1 CTBS_10-20EEG
## tyagi, 2022_CTBS_10-20EEG_T_PANSS_1 CTBS_10-20EEG
## tyagi, 2022_CTBS_10-20EEG_G_PANSS_1 CTBS_10-20EEG
## tyagi, 2022_CTBS_10-20EEG_P_AVHRS_1 CTBS_10-20EEG
## tyagi, 2022_CTBS_10-20EEG_P_PSYRAT-AH_1 CTBS_10-20EEG
## valiengo, 2020_TDCS_10-20EEG_N_PANSS_1 SHAM
## valiengo, 2020_TDCS_10-20EEG_P_PANSS_1 SHAM
## valiengo, 2020_TDCS_10-20EEG_T_PANSS_1 SHAM
## valiengo, 2020_TDCS_10-20EEG_G_PANSS_1 SHAM
## valiengo, 2020_TDCS_10-20EEG_P_AVHRS_1 SHAM
## vercammen, 2011_TDCS_10-20EEG_RPS_Weather Prediction Test_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_T_PANSS_1 ITBS_10-20EEG
## vergallito, 2024_ITBS_10-20EEG_P_PANSS_1 ITBS_10-20EEG
## vergallito, 2024_ITBS_10-20EEG_N_PANSS_1 ITBS_10-20EEG
## vergallito, 2024_ITBS_10-20EEG_N_BNSS_1 ITBS_10-20EEG
## vergallito, 2024_ITBS_10-20EEG_GC_MCCB_1 ITBS_10-20EEG
## vergallito, 2024_ITBS_10-20EEG_PS_MCCB_1 ITBS_10-20EEG
## vergallito, 2024_ITBS_10-20EEG_AV_MCCB_1 ITBS_10-20EEG
## vergallito, 2024_ITBS_10-20EEG_WM_MCCB_1 ITBS_10-20EEG
## vergallito, 2024_ITBS_10-20EEG_VerL_MCCB_1 ITBS_10-20EEG
## vergallito, 2024_ITBS_10-20EEG_VisL_MCCB_1 ITBS_10-20EEG
## vergallito, 2024_ITBS_10-20EEG_RPS_MCCB_1 ITBS_10-20EEG
## vergallito, 2024_ITBS_10-20EEG_SC_MCCB_1 ITBS_10-20EEG
## walther-lft, 2024_UNKNOWN_STANDARD_T_PANSS_1 SHAM
## walther-lft, 2024_UNKNOWN_STANDARD_P_PANSS_1 SHAM
## walther-lft, 2024_UNKNOWN_STANDARD_N_PANSS_1 SHAM
## walther-lft, 2024_UNKNOWN_STANDARD_G_PANSS_1 SHAM
## walther-lft, 2024_UNKNOWN_STANDARD_N_BNSS_1 SHAM
## walther-itbs, 2024_ITBS_CM_T_PANSS_1 ITBS_CM
## walther-itbs, 2024_ITBS_CM_P_PANSS_1 ITBS_CM
## walther-itbs, 2024_ITBS_CM_N_PANSS_1 ITBS_CM
## walther-itbs, 2024_ITBS_CM_G_PANSS_1 ITBS_CM
## walther-itbs, 2024_ITBS_CM_N_BNSS_1 ITBS_CM
## wang, 2020_ITBS_NEURONAV_T_PANSS_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_P_PANSS_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_N_PANSS_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_G_PANSS_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_P_SAPS_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_N_SANS_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_GC_MoCA_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_PS_VFT_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_WM_Digit span (forward)_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_WM_Digit span (backward)_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_RPS_Stroop Color Test_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_RPS_Stroop Word Test_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_RPS_Stroop Interference Test_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_PS_TMT-A_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_RPS_TMT-B_1 ITBS_NEURONAV
## wang, 2022_ITBS_NEURONAV_P_PANSS_1 ITBS_NEURONAV
## wang, 2022_ITBS_NEURONAV_N_PANSS_1 ITBS_NEURONAV
## wang, 2022_ITBS_NEURONAV_G_PANSS_1 ITBS_NEURONAV
## wang, 2022_ITBS_NEURONAV_T_PANSS_1 ITBS_NEURONAV
## wang, 2022_ITBS_NEURONAV_P_SAPS_1 ITBS_NEURONAV
## wang, 2022_ITBS_NEURONAV_N_SANS_1 ITBS_NEURONAV
## wang, 2022_ITBS_NEURONAV_GC_MoCA_1 ITBS_NEURONAV
## wang, 2022_ITBS_NEURONAV_WM_3-back RT_1 ITBS_NEURONAV
## weickert, 2019_TDCS_10-20EEG_T_PANSS_1 SHAM
## weickert, 2019_TDCS_10-20EEG_P_PANSS_1 SHAM
## weickert, 2019_TDCS_10-20EEG_N_PANSS_1 SHAM
## weickert, 2019_TDCS_10-20EEG_G_PANSS_1 SHAM
## weickert, 2019_TDCS_10-20EEG_P_AHRS_1 SHAM
## weickert, 2019_TDCS_10-20EEG_PS_BACS sc_1 SHAM
## weickert, 2019_TDCS_10-20EEG_PS_TMT-A_1 SHAM
## weickert, 2019_TDCS_10-20EEG_WM_LNS_1 SHAM
## weickert, 2019_TDCS_10-20EEG_VerL_HVLTr_1 SHAM
## weickert, 2019_TDCS_10-20EEG_VisL_BVMT_1 SHAM
## weickert, 2019_TDCS_10-20EEG_RPS_NAB maze_1 SHAM
## weickert, 2019_TDCS_10-20EEG_PS_fluency_1 SHAM
## wen, 2021_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## wen, 2021_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## wen, 2021_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## wen, 2021_HF-RTMS_CM_G_PANSS_1 HF-RTMS_CM
## wen, 2021_HF-RTMS_CM_GC_RBANS-T_1 HF-RTMS_CM
## wen, 2021_HF-RTMS_CM_VerL_RBANS\r\nImmediate memory_1 HF-RTMS_CM
## wen, 2021_HF-RTMS_CM_WM_RBANS\r\nAttention_1 HF-RTMS_CM
## wen, 2021_HF-RTMS_CM_VisL_RBANS\r\nVisuospatial_1 HF-RTMS_CM
## wen, 2021_HF-RTMS_CM_VisL_RBANS\r\nDelayed memory_1 HF-RTMS_CM
## wen, 2021_HF-RTMS_CM_VerL_RBANS\r\nLanguage_1 HF-RTMS_CM
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n1 word (s)_1 HF-RTMS_CM
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n2 word (s)_1 HF-RTMS_CM
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n3 word (s)_1 HF-RTMS_CM
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n3 color (s)_1 HF-RTMS_CM
## wobrock, 2015_HF-RTMS_10-20EEG_T_PANSS_1 HF-RTMS_10-20EEG
## wobrock, 2015_HF-RTMS_10-20EEG_P_PANSS_1 HF-RTMS_10-20EEG
## wobrock, 2015_HF-RTMS_10-20EEG_N_PANSS_1 HF-RTMS_10-20EEG
## xie, 2023-a_LF-RTMS_10-20EEG_T_PANSS_1 LF-RTMS_10-20EEG
## xie, 2023-a_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## xie, 2023-a_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## xie, 2023-a_LF-RTMS_10-20EEG_G_PANSS_1 LF-RTMS_10-20EEG
## xie, 2023-a_LF-RTMS_10-20EEG_P_AHRS_1 LF-RTMS_10-20EEG
## xiu-10hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 HF-RTMS_NEURONAV
## xiu-10hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 HF-RTMS_NEURONAV
## xiu-10hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 HF-RTMS_NEURONAV
## xiu-10hz, 2020_HF-RTMS_NEURONAV_G_PANSS_1 HF-RTMS_NEURONAV
## xiu-10hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 HF-RTMS_NEURONAV
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nImmediate memory_1 HF-RTMS_NEURONAV
## xiu-10hz, 2020_HF-RTMS_NEURONAV_WM_RBANS\r\nAttention_1 HF-RTMS_NEURONAV
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nVisuospatial_1 HF-RTMS_NEURONAV
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nDelayed memory_1 HF-RTMS_NEURONAV
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nLanguage_1 HF-RTMS_NEURONAV
## xiu-20hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 HF-RTMS_NEURONAV
## xiu-20hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 HF-RTMS_NEURONAV
## xiu-20hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 HF-RTMS_NEURONAV
## xiu-20hz, 2020_HF-RTMS_NEURONAV_G_PANSS_1 HF-RTMS_NEURONAV
## xiu-20hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 HF-RTMS_NEURONAV
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nImmediate memory_1 HF-RTMS_NEURONAV
## xiu-20hz, 2020_HF-RTMS_NEURONAV_WM_RBANS\r\nAttention_1 HF-RTMS_NEURONAV
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nVisuospatial_1 HF-RTMS_NEURONAV
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nDelayed memory_1 HF-RTMS_NEURONAV
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nLanguage_1 HF-RTMS_NEURONAV
## xu, 2023_HD-TDCS_10-20EEG_T_PANSS_1 HD-TDCS_10-20EEG
## xu, 2023_HD-TDCS_10-20EEG_P_PANSS_1 HD-TDCS_10-20EEG
## xu, 2023_HD-TDCS_10-20EEG_N_PANSS_1 HD-TDCS_10-20EEG
## xu, 2023_HD-TDCS_10-20EEG_G_PANSS_1 HD-TDCS_10-20EEG
## xu, 2023_HD-TDCS_10-20EEG_GC_RBANS_1 HD-TDCS_10-20EEG
## ye-20hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 HF-RTMS_NEURONAV
## ye-20hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Immediate memory_1 HF-RTMS_NEURONAV
## ye-20hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Visuospatial_1 HF-RTMS_NEURONAV
## ye-20hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Language_1 HF-RTMS_NEURONAV
## ye-20hz, 2024_HF-RTMS_NEURONAV_WM_RBANS - Attention_1 HF-RTMS_NEURONAV
## ye-20hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Delayed memory_1 HF-RTMS_NEURONAV
## ye-10hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 HF-RTMS_NEURONAV
## ye-10hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Immediate memory_1 HF-RTMS_NEURONAV
## ye-10hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Visuospatial_1 HF-RTMS_NEURONAV
## ye-10hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Language_1 HF-RTMS_NEURONAV
## ye-10hz, 2024_HF-RTMS_NEURONAV_WM_RBANS - Attention_1 HF-RTMS_NEURONAV
## ye-10hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Delayed memory_1 HF-RTMS_NEURONAV
## yuanjun, 2024_LF-RTMS_10-20EEG_T_PANSS_1 LF-RTMS_10-20EEG
## yuanjun, 2024_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## yuanjun, 2024_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## yuanjun, 2024_LF-RTMS_10-20EEG_G_PANSS_1 LF-RTMS_10-20EEG
## yuanjun, 2024_LF-RTMS_10-20EEG_P_AHRS_1 LF-RTMS_10-20EEG
## zhai-a, 2023_HF-RTMS_NA_T_PANSS_1 HF-RTMS_NA
## zhang, 2022_TACS_10-20EEG_T_PANSS_1 SHAM
## zhang, 2022_TACS_10-20EEG_P_PANSS_1 SHAM
## zhang, 2022_TACS_10-20EEG_N_PANSS_1 SHAM
## zhang, 2022_TACS_10-20EEG_P_AHRS_1 SHAM
## zhao-tbs, 2014_ITBS_10-20EEG_T_PANSS_1 ITBS_10-20EEG
## zhao-tbs, 2014_ITBS_10-20EEG_P_PANSS_1 ITBS_10-20EEG
## zhao-tbs, 2014_ITBS_10-20EEG_N_PANSS_1 ITBS_10-20EEG
## zhao-tbs, 2014_ITBS_10-20EEG_G_PANSS_1 ITBS_10-20EEG
## zhao-tbs, 2014_ITBS_10-20EEG_N_SANS_1 ITBS_10-20EEG
## zhao-20hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 HF-RTMS_10-20EEG
## zhao-20hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 HF-RTMS_10-20EEG
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 HF-RTMS_10-20EEG
## zhao-20hz, 2014_HF-RTMS_10-20EEG_G_PANSS_1 HF-RTMS_10-20EEG
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 HF-RTMS_10-20EEG
## zhao-10hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 HF-RTMS_10-20EEG
## zhao-10hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 HF-RTMS_10-20EEG
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 HF-RTMS_10-20EEG
## zhao-10hz, 2014_HF-RTMS_10-20EEG_G_PANSS_1 HF-RTMS_10-20EEG
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 HF-RTMS_10-20EEG
## zhou, 2024_HF-RTMS_10-20EEG_P_PANSS_1 HF-RTMS_10-20EEG
## zhou, 2024_HF-RTMS_10-20EEG_N_PANSS_1 HF-RTMS_10-20EEG
## zhou, 2024_HF-RTMS_10-20EEG_T_PANSS_1 HF-RTMS_10-20EEG
## zhou, 2024_HF-RTMS_10-20EEG_G_PANSS_1 HF-RTMS_10-20EEG
## zhou, 2024_HF-RTMS_10-20EEG_GC_RBANS-T_1 HF-RTMS_10-20EEG
## zhou, 2024_HF-RTMS_10-20EEG_VerL_RBANS\r\nImmediate memory_1 HF-RTMS_10-20EEG
## zhou, 2024_HF-RTMS_10-20EEG_VisL_RBANS\r\nVisuospatial_1 HF-RTMS_10-20EEG
## zhou, 2024_HF-RTMS_10-20EEG_VerL_RBANS\r\nLanguage_1 HF-RTMS_10-20EEG
## zhou, 2024_HF-RTMS_10-20EEG_WM_RBANS\r\nAttention_1 HF-RTMS_10-20EEG
## zhou, 2024_HF-RTMS_10-20EEG_VisL_RBANS\r\nDelayed memory_1 HF-RTMS_10-20EEG
## zhou, 2024_HF-RTMS_10-20EEG_RPS_SCWT \r\nInference scores_1 HF-RTMS_10-20EEG
## zhou, 2023_TDCS_10-20EEG_T_PANSS_1 SHAM
## zhou, 2023_TDCS_10-20EEG_N_SANS_1 SHAM
## zhou, 2023_TDCS_10-20EEG_RPS_IED total errors_1 SHAM
## zhu, 2021_ITBS_CM_N_PANSS_1 ITBS_CM
## zhuo, 2019_HF-RTMS_10-20EEG_T_PANSS_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_P_PANSS_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_N_PANSS_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_G_PANSS_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_N_SANS_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_PS_MCCB TMT-A_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_PS_MCCB BACS_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_PS_MCCB Fluency_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_WM_MCCB Working memory (WMS-SS)_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_VerL_MCCB Verbal learning (HVLT-R)_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_VisL_MCCB Visual learning (BVMT-R)_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_RPS_MCCB Reasoning/problem solving (NAB)_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_SC_MCCB Social cognition (MSCEIT)_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_GC_MCCB Composite score_1 HF-RTMS_10-20EEG
## treat2
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANSS_1 SHAM
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANSS_1 SHAM
## bais, 2014 - l_LF-RTMS_10-20EEG_G_PANSS_1 SHAM
## bais, 2014 - l_LF-RTMS_10-20EEG_P_AHRS_1 SHAM
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANAS_1 SHAM
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANAS_1 SHAM
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANSS_1 SHAM
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANSS_1 SHAM
## bais, 2014 - bi_LF-RTMS_10-20EEG_G_PANSS_1 SHAM
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_AHRS_1 SHAM
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANAS_1 SHAM
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANAS_1 SHAM
## barr, 2011_HF-RTMS_NEURONAV_WM_1-back RT ms_1 SHAM
## barr, 2011_HF-RTMS_NEURONAV_WM_2-back RT ms_1 SHAM
## barr, 2011_HF-RTMS_NEURONAV_WM_3-back RT ms_1 SHAM
## barr, 2013_HF-RTMS_NEURONAV_WM_1-back RT ms Target Correct_1 SHAM
## barr, 2013_HF-RTMS_NEURONAV_WM_1-back RT ms Non Target Correct_1 SHAM
## barr, 2013_HF-RTMS_NEURONAV_WM_3-back RT ms Target Correct_1 SHAM
## barr, 2013_HF-RTMS_NEURONAV_WM_3-back RT ms Non Target Correct_1 SHAM
## barr, 2012_HF-RTMS_NEURONAV_P_PANSS_1 SHAM
## barr, 2012_HF-RTMS_NEURONAV_N_PANSS_1 SHAM
## barr, 2012_HF-RTMS_NEURONAV_N_SANS_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_N_SANS_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_P_SAPS_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_VerL_AVLT Hits_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_VisL_CFT copying_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_VisL_CFT Immediate Recall_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_VisL_CFT Delayed Recall_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_PS_DSST time (sec)_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_PS_DSST errors_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_AV_DVT time (sec)_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-A time (sec)_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-A errors_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-B time (sec)_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-B errors_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_WM_1back verbal Hits_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_WM_1back verbal Errors_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_WM_2back verbal Hits_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_WM_2back verbal Errors_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_WM_Spatial Span total_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_RPS_FAS_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_RPS_Stroop Effect score_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_SC_FOT index_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_SC_SOT index_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_SC_Faux Pax CI_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_SC_Personalizing Bias Index_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_SC_Social Perception Index_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_SC_Emotion Recognition Index_1 SHAM
## battion, 2021_ITBS_CM_T_PANSS_1 SHAM
## battion, 2021_ITBS_CM_N_SANS_1 SHAM
## blumberger, 2012_LF-RTMS_NEURONAV_P_PSYRATS_1 SHAM
## blumberger, 2012_LF-RTMS_NEURONAV_T_PANSS_1 SHAM
## blumberger, 2012_LF-RTMS_NEURONAV_P_PANSS_1 SHAM
## blumberger, 2012_LF-RTMS_NEURONAV_P_AHRS_1 SHAM
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PSYRATS_1 SHAM
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_T_PANSS_1 SHAM
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PANSS_1 SHAM
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_AHRS_1 SHAM
## bodén, 2021_ITBS_CM_N_CAIN_1 SHAM
## bose, 2018_TDCS_10-20EEG_P_SAPS_1 TDCS_10-20EEG
## bose, 2018_TDCS_10-20EEG_N_SANS_1 TDCS_10-20EEG
## bose, 2018_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG
## brunelin, 2012_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG
## brunelin, 2012_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## brunelin, 2006_LF-RTMS_10-20EEG_P_AHRS_1 SHAM
## brunelin, 2006_LF-RTMS_10-20EEG_P_SAPS_1 SHAM
## brunelin, 2006_LF-RTMS_10-20EEG_WM_MonitorSourceTask_1 SHAM
## bulubas, 2021_TDCS_10-20EEG_VisL_PFMT Total Correct Responses_1 TDCS_10-20EEG
## bulubas, 2021_TDCS_10-20EEG_VerL_PWMT Total Correct Responses_1 TDCS_10-20EEG
## bulubas, 2021_TDCS_10-20EEG_SC_EMI Correct Responses_1 TDCS_10-20EEG
## bulubas, 2021_TDCS_10-20EEG_WM_PLNB 0-back True Positive Responses_1 TDCS_10-20EEG
## bulubas, 2021_TDCS_10-20EEG_WM_PLNB 1-back True Positive Responses_1 TDCS_10-20EEG
## bulubas, 2021_TDCS_10-20EEG_WM_PLNB 2-back True Positive Responses_1 TDCS_10-20EEG
## bulubas, 2021_TDCS_10-20EEG_RPS_PCET Number Correct Responses_1 TDCS_10-20EEG
## bulubas, 2021_TDCS_10-20EEG_VisL_Short VOLT Total Correct_1 TDCS_10-20EEG
## chang-a, 2021_TACS_10-20EEG_T_PANSS_1 TACS_10-20EEG
## chang-a, 2021_TACS_10-20EEG_N_PANSS_1 TACS_10-20EEG
## chang-a, 2021_TACS_10-20EEG_N_SANS_1 TACS_10-20EEG
## chauhan, 2021_ITBS_10-20EEG_P_PANSS_1 SHAM
## chauhan, 2021_ITBS_10-20EEG_N_PANSS_1 SHAM
## chauhan, 2021_ITBS_10-20EEG_G_PANSS_1 SHAM
## chauhan, 2021_ITBS_10-20EEG_T_PANSS_1 SHAM
## chauhan, 2021_ITBS_10-20EEG_T_BPRS_1 SHAM
## de jesus, 2011_LF-RTMS_10-20EEG_T_BPRS_1 SHAM
## de jesus, 2011_LF-RTMS_10-20EEG_P_BPRS_1 SHAM
## de jesus, 2011_LF-RTMS_10-20EEG_N_BPRS_1 SHAM
## de jesus, 2011_LF-RTMS_10-20EEG_P_AHRS_1 SHAM
## dharani, 2021_HD-TDCS_10-10EEG_P_PANSS_1 SHAM
## dharani, 2021_HD-TDCS_10-10EEG_N_PANSS_1 SHAM
## dharani, 2021_HD-TDCS_10-10EEG_G_PANSS_1 SHAM
## dharani, 2021_HD-TDCS_10-10EEG_N_SANS_1 SHAM
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_SANS_1 SHAM
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_P_PANSS_1 SHAM
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_PANSS_1 SHAM
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_G_PANSS_1 SHAM
## dolfus, 2018_HF-RTMS_NEURONAV_P_AHRS_1 SHAM
## du, 2024_HF-RTMS_NEURONAV_T_BPRS_1 SHAM
## du, 2024_HF-RTMS_NEURONAV_P_BPRS_1 SHAM
## du, 2024_HF-RTMS_NEURONAV_N_BPRS_1 SHAM
## du, 2022_HF-RTMS_10-20EEG_VisL_PRM number correct_1 SHAM
## du, 2022_HF-RTMS_10-20EEG_N_SANS_1 SHAM
## du, 2022_HF-RTMS_10-20EEG_T_PANSS_1 SHAM
## du, 2022_HF-RTMS_10-20EEG_P_PANSS_1 SHAM
## du, 2022_HF-RTMS_10-20EEG_N_PANSS_1 SHAM
## du, 2022_HF-RTMS_10-20EEG_G_PANSS_1 SHAM
## farhang, 2024_TDCS_10-20EEG_WM_ letter-number sequencing_1 TDCS_10-20EEG
## fitzerald, 2008_LF-RTMS_CM_N_SANS_1 SHAM
## fitzerald, 2008_LF-RTMS_CM_P_PANSS_1 SHAM
## fitzerald, 2008_LF-RTMS_CM_N_PANSS_1 SHAM
## fitzerald, 2008_LF-RTMS_CM_T_PANSS_1 SHAM
## fitzerald-l, 2014_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG
## fitzerald-l, 2014_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG
## fitzerald-l, 2014_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## fitzerald-l, 2014_TDCS_10-20EEG_N_SANS_1 TDCS_10-20EEG
## fitzerald-bi, 2014_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG
## fitzerald-bi, 2014_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG
## fitzerald-bi, 2014_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## fitzerald-bi, 2014_TDCS_10-20EEG_N_SANS_1 TDCS_10-20EEG
## francis, 2019_HF-RTMS_CM_VerL_BACS Verbal Memory_1 SHAM
## francis, 2019_HF-RTMS_CM_WM_BACS Digit Sequencing_1 SHAM
## francis, 2019_HF-RTMS_CM_PS_BACS Semantic and Letter Fluency_1 SHAM
## francis, 2019_HF-RTMS_CM_PS_BACS Symbol Coding_1 SHAM
## francis, 2019_HF-RTMS_CM_RPS_BACS Tower of London_1 SHAM
## francis, 2019_HF-RTMS_CM_GC_BACS Composite Score_1 SHAM
## frohlich, 2016_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG
## frohlich, 2016_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## frohlich, 2016_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG
## frohlich, 2016_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG
## frohlich, 2016_TDCS_10-20EEG_G_PANSS_1 TDCS_10-20EEG
## gao, 2024_ITBS_10-20EEG_P_PANSS_1 SHAM
## gao, 2024_ITBS_10-20EEG_N_PANSS_1 SHAM
## gao, 2024_ITBS_10-20EEG_G_PANSS_1 SHAM
## gao, 2024_ITBS_10-20EEG_T_PANSS_1 SHAM
## gao, 2024_ITBS_10-20EEG_N_SANS_1 SHAM
## garcía-fernández, 2024_TDCS_10-20EEG_PS_MCCB_1 TDCS_10-20EEG
## garcía-fernández, 2024_TDCS_10-20EEG_AV_MCCB_1 TDCS_10-20EEG
## garcía-fernández, 2024_TDCS_10-20EEG_WM_MCCB_1 TDCS_10-20EEG
## garcía-fernández, 2024_TDCS_10-20EEG_VerL_MCCB_1 TDCS_10-20EEG
## garcía-fernández, 2024_TDCS_10-20EEG_VisL_MCCB_1 TDCS_10-20EEG
## garcía-fernández, 2024_TDCS_10-20EEG_RPS_MCCB_1 TDCS_10-20EEG
## garcía-fernández, 2024_TDCS_10-20EEG_SC_MCCB_1 TDCS_10-20EEG
## garg, 2016_DTMS_CM_P_PANSS_1 SHAM
## garg, 2016_DTMS_CM_N_PANSS_1 SHAM
## garg, 2016_DTMS_CM_G_PANSS_1 SHAM
## garg, 2016_DTMS_CM_T_PANSS_1 SHAM
## gogler, 2017_TDCS_10-20EEG_PS_C_1 TDCS_10-20EEG
## gogler, 2017_TDCS_10-20EEG_WM_K_1 TDCS_10-20EEG
## gogler, 2017_TDCS_10-20EEG_AV_α_1 TDCS_10-20EEG
## gomes, 2018_TDCS_10-20EEG_WM_MCCB_1 TDCS_10-20EEG
## gomes, 2018_TDCS_10-20EEG_PS_MCCB_1 TDCS_10-20EEG
## gomes, 2018_TDCS_10-20EEG_AV_MCCB_1 TDCS_10-20EEG
## gomes, 2018_TDCS_10-20EEG_VerL_MCCB_1 TDCS_10-20EEG
## gomes, 2018_TDCS_10-20EEG_VisL_MCCB_1 TDCS_10-20EEG
## gomes, 2018_TDCS_10-20EEG_RPS_MCCB_1 TDCS_10-20EEG
## gomes, 2018_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG
## gomes, 2018_TDCS_10-20EEG_N_PANSS-N_1 TDCS_10-20EEG
## gomes, 2018_TDCS_10-20EEG_G_PANSS_1 TDCS_10-20EEG
## gomes, 2018_TDCS_10-20EEG_T_PANSS-T_1 TDCS_10-20EEG
## guan, 2020_HF-RTMS_NEURONAV_T_PANSS-T_1 SHAM
## guan, 2020_HF-RTMS_NEURONAV_P_PANSS_1 SHAM
## guan, 2020_HF-RTMS_NEURONAV_N_PANSS-N_1 SHAM
## guan, 2020_HF-RTMS_NEURONAV_G_PANSS_1 SHAM
## guan, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nImmediate memory_1 SHAM
## guan, 2020_HF-RTMS_NEURONAV_WM_RBANS\r\nAttention_1 SHAM
## guan, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nVisuospatial/constructional_1 SHAM
## guan, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nDelayed memory_1 SHAM
## guan, 2020_HF-RTMS_NEURONAV_PS_RBANS\r\nLanguage_1 SHAM
## guan, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 SHAM
## guleken, 2020_HF-RTMS_CM_P_PANSS_1 SHAM
## guleken, 2020_HF-RTMS_CM_N_SANS_1 SHAM
## guleken, 2020_HF-RTMS_CM_RPS_WSCT total correct responses_1 SHAM
## guleken, 2020_HF-RTMS_CM_RPS_WSCT perseverative errors_1 SHAM
## guleken, 2020_HF-RTMS_CM_WM_DST forward_1 SHAM
## guleken, 2020_HF-RTMS_CM_WM_DST backwards_1 SHAM
## guleken, 2020_HF-RTMS_CM_RPS_Total time_1 SHAM
## guleken, 2020_HF-RTMS_CM_RPS_Total errors_1 SHAM
## guleken, 2020_HF-RTMS_CM_RPS_Stroop Interference_1 SHAM
## guse, 2013_HF-RTMS_10-20EEG_PS_TMT-A_1 SHAM
## guse, 2013_HF-RTMS_10-20EEG_RPS_TMT-B_1 SHAM
## guse, 2013_HF-RTMS_10-20EEG_RPS_WCST Accuracy_1 SHAM
## guse, 2013_HF-RTMS_10-20EEG_RPS_WCST RT_1 SHAM
## guse, 2013_HF-RTMS_10-20EEG_AV_Sel. Attention Accuracy_1 SHAM
## guse, 2013_HF-RTMS_10-20EEG_AV_Sel. Attention RT_1 SHAM
## guse, 2013_HF-RTMS_10-20EEG_AV_Div. Attention Accuracy_1 SHAM
## guse, 2013_HF-RTMS_10-20EEG_AV_Div. Attention RT_1 SHAM
## guse, 2013_HF-RTMS_10-20EEG_WM_0-back Accuracy_1 SHAM
## guse, 2013_HF-RTMS_10-20EEG_WM_0-back RT_1 SHAM
## guse, 2013_HF-RTMS_10-20EEG_WM_1-back Accuracy_1 SHAM
## guse, 2013_HF-RTMS_10-20EEG_WM_1-back RT_1 SHAM
## guse, 2013_HF-RTMS_10-20EEG_WM_2-back Accuracy_1 SHAM
## guse, 2013_HF-RTMS_10-20EEG_WM_2-back RT_1 SHAM
## hasan, 2016_HF-RTMS_10-20EEG_WM_DST z score_1 SHAM
## hasan, 2016_HF-RTMS_10-20EEG_WM_DST Forward_1 SHAM
## hasan, 2016_HF-RTMS_10-20EEG_WM_DST Backward_1 SHAM
## hasan, 2016_HF-RTMS_10-20EEG_PS_TMT-A time (s)_1 SHAM
## hasan, 2016_HF-RTMS_10-20EEG_RPS_TMT-B time (s)_1 SHAM
## hasan, 2016_HF-RTMS_10-20EEG_VerL_VLMT z score_1 SHAM
## hasan, 2016_HF-RTMS_10-20EEG_RPS_WCST z score_1 SHAM
## hasan, 2016_HF-RTMS_10-20EEG_RPS_WCST total correct score_1 SHAM
## hasan, 2016_HF-RTMS_10-20EEG_RPS_WCST total errors_1 SHAM
## hasan, 2016_HF-RTMS_10-20EEG_PS_RWT z score_1 SHAM
## holi, 2004_HF-RTMS_10-20EEG_T_PANSS_1 SHAM
## holi, 2004_HF-RTMS_10-20EEG_P_PANSS_1 SHAM
## holi, 2004_HF-RTMS_10-20EEG_N_PANSS_1 SHAM
## holi, 2004_HF-RTMS_10-20EEG_G_PANSS_1 SHAM
## hu, 2024_LF-RTMS_10-20EEG_T_PANSS_1 SHAM
## hu, 2024_LF-RTMS_10-20EEG_P_PANSS_1 SHAM
## hu, 2024_LF-RTMS_10-20EEG_N_PANSS_1 SHAM
## hu, 2024_LF-RTMS_10-20EEG_G_PANSS_1 SHAM
## hu, 2024_LF-RTMS_10-20EEG_PS_TMT-A_1 SHAM
## hu, 2024_LF-RTMS_10-20EEG_PS_BACS Symbol Coding_1 SHAM
## hu, 2024_LF-RTMS_10-20EEG_PS_Category Fluency_1 SHAM
## hu, 2024_LF-RTMS_10-20EEG_AV_CPT-IP_1 SHAM
## hu, 2024_LF-RTMS_10-20EEG_WM_WMS-3 spatial span_1 SHAM
## hu, 2024_LF-RTMS_10-20EEG_VerL_HVLT-R_1 SHAM
## hu, 2024_LF-RTMS_10-20EEG_VisL_BVMT-R_1 SHAM
## hu, 2024_LF-RTMS_10-20EEG_RPS_NAB_1 SHAM
## hu, 2023_LF-RTMS_10-10EEG_T_PANSS_1 SHAM
## hu, 2023_LF-RTMS_10-10EEG_P_PANSS_1 SHAM
## hu, 2023_LF-RTMS_10-10EEG_N_PANSS_1 SHAM
## hu, 2023_LF-RTMS_10-10EEG_G_PANSS_1 SHAM
## hu, 2023_LF-RTMS_10-10EEG_GC_MCCB-T_1 SHAM
## hu, 2023_LF-RTMS_10-10EEG_PS_MCCB_1 SHAM
## hu, 2023_LF-RTMS_10-10EEG_AV_MCCB_1 SHAM
## hu, 2023_LF-RTMS_10-10EEG_WM_MCCB_1 SHAM
## hu, 2023_LF-RTMS_10-10EEG_VerL_MCCB_1 SHAM
## hu, 2023_LF-RTMS_10-10EEG_VisL_MCCB_1 SHAM
## hu, 2023_LF-RTMS_10-10EEG_RPS_MCCB_1 SHAM
## hu, 2023_LF-RTMS_10-10EEG_SC_MCCB_1 SHAM
## huang, 2016_HF-RTMS_CM_P_PANSS_1 SHAM
## huang, 2016_HF-RTMS_CM_N_PANSS_1 SHAM
## huang, 2016_HF-RTMS_CM_G_PANSS_1 SHAM
## huang, 2016_HF-RTMS_CM_T_PANSS_1 SHAM
## huang, 2016_HF-RTMS_CM_RPS_WSCT total errors_1 SHAM
## jeon, 2018_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG
## jeon, 2018_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG
## jeon, 2018_TDCS_10-20EEG_G_PANSS_1 TDCS_10-20EEG
## jeon, 2018_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## jeon, 2018_TDCS_10-20EEG_PS_MCCB_1 TDCS_10-20EEG
## jeon, 2018_TDCS_10-20EEG_AV_MCCB_1 TDCS_10-20EEG
## jeon, 2018_TDCS_10-20EEG_WM_MCCB_1 TDCS_10-20EEG
## jeon, 2018_TDCS_10-20EEG_VerL_MCCB_1 TDCS_10-20EEG
## jeon, 2018_TDCS_10-20EEG_VisL_MCCB_1 TDCS_10-20EEG
## jeon, 2018_TDCS_10-20EEG_RPS_MCCB_1 TDCS_10-20EEG
## jeon, 2018_TDCS_10-20EEG_SC_MCCB_1 TDCS_10-20EEG
## jeon, 2018_TDCS_10-20EEG_GC_MCCB Composite Score_1 TDCS_10-20EEG
## jeon, 2018_TDCS_10-20EEG_RPS_WCST Perservative Responses_1 TDCS_10-20EEG
## jeon, 2018_TDCS_10-20EEG_RPS_WCST Perservative Errors_1 TDCS_10-20EEG
## jeon, 2018_TDCS_10-20EEG_RPS_WCST Categoris number_1 TDCS_10-20EEG
## jin, 2023_ITBS_NA_SC_FERT_1 SHAM
## jin, 2023_ITBS_NA_SC_HT_1 SHAM
## jin, 2023_ITBS_NA_T_PANSS_1 SHAM
## jin, 2023_ITBS_NA_P_PANSS_1 SHAM
## jin, 2023_ITBS_NA_N_PANSS_1 SHAM
## jin, 2023_ITBS_NA_G_PANSS_1 SHAM
## kang, 2024_CTBS_CM_T_PANSS_1 SHAM
## kang, 2024_CTBS_CM_P_PANSS_1 SHAM
## kang, 2024_CTBS_CM_N_PANSS_1 SHAM
## kang, 2024_CTBS_CM_G_PANSS_1 SHAM
## kang, 2024_CTBS_CM_P_AHRS_1 SHAM
## kantrowitz, 2019_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG
## kimura, 2016_HF-RTMS_10-20EEG_P_AHRS_1 SHAM
## klein, 1999_LF-RTMS_CM_P_PANSS_1 SHAM
## klein, 1999_LF-RTMS_CM_N_PANSS_1 SHAM
## klein, 1999_LF-RTMS_CM_G_PANSS_1 SHAM
## klein, 1999_LF-RTMS_CM_T_BPRS_1 SHAM
## koops, 2018_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG
## koops, 2018_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## koops, 2018_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG
## koops, 2018_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG
## koops, 2018_TDCS_10-20EEG_RPS_Stroop Interference_1 TDCS_10-20EEG
## koops, 2018_TDCS_10-20EEG_PS_TMT-A_1 TDCS_10-20EEG
## koops, 2018_TDCS_10-20EEG_RPS_TMT-B_1 TDCS_10-20EEG
## koops, 2016_CTBS_10-20EEG_P_PANSS_1 SHAM
## koops, 2016_CTBS_10-20EEG_P_AHRS_1 SHAM
## koops, 2016_CTBS_10-20EEG_P_PSYRATS_1 SHAM
## kos, 2024_TDCS_10-20EEG_N_SANS_1 TDCS_10-20EEG
## kos, 2024_TDCS_10-20EEG_N_AES_1 TDCS_10-20EEG
## kumar, 2020_HF-RTMS_CM_PANSS-N_1 SHAM
## kumar, 2020_HF-RTMS_CM_PANSS-G_1 SHAM
## li, 2024 - a_ITBS_10-20EEG_GC_MCCB_1 SHAM
## li, 2024 - a_ITBS_10-20EEG_WM_MCCB_1 SHAM
## li, 2024 - a_ITBS_10-20EEG_PANSS-P_1 SHAM
## li, 2024 - a_ITBS_10-20EEG_PANSS-N_1 SHAM
## li, 2024 - a_ITBS_10-20EEG_PANSS-G_1 SHAM
## li-b-lpc, 2024_ITBS_NEURONAV_PS_MCCB_1 SHAM
## li-b-lpc, 2024_ITBS_NEURONAV_AV_MCCB_1 SHAM
## li-b-lpc, 2024_ITBS_NEURONAV_WM_MCCB_1 SHAM
## li-b-lpc, 2024_ITBS_NEURONAV_VerL_MCCB_1 SHAM
## li-b-lpc, 2024_ITBS_NEURONAV_VisL_MCCB_1 SHAM
## li-b-lpc, 2024_ITBS_NEURONAV_RPS_MCCB_1 SHAM
## li-b-lpc, 2024_ITBS_NEURONAV_SC_MCCB_1 SHAM
## li-b-lpc, 2024_ITBS_NEURONAV_GC_MCCB_1 SHAM
## li-b-dlpfc, 2024_ITBS_NEURONAV_PS_MCCB_1 SHAM
## li-b-dlpfc, 2024_ITBS_NEURONAV_AV_MCCB_1 SHAM
## li-b-dlpfc, 2024_ITBS_NEURONAV_WM_MCCB_1 SHAM
## li-b-dlpfc, 2024_ITBS_NEURONAV_VerL_MCCB_1 SHAM
## li-b-dlpfc, 2024_ITBS_NEURONAV_VisL_MCCB_1 SHAM
## li-b-dlpfc, 2024_ITBS_NEURONAV_RPS_MCCB_1 SHAM
## li-b-dlpfc, 2024_ITBS_NEURONAV_SC_MCCB_1 SHAM
## li-b-dlpfc, 2024_ITBS_NEURONAV_GC_MCCB_1 SHAM
## lindenmayer, 2019_TDCS_10-20EEG_AHRS_1 TDCS_10-20EEG
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-T_1 TDCS_10-20EEG
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-P_1 TDCS_10-20EEG
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-N_1 TDCS_10-20EEG
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-G_1 TDCS_10-20EEG
## lindenmayer, 2019_TDCS_10-20EEG_GC_MCCB_1 TDCS_10-20EEG
## lindenmayer, 2019_TDCS_10-20EEG_PS_MCCB_1 TDCS_10-20EEG
## lindenmayer, 2019_TDCS_10-20EEG_AV_MCCB_1 TDCS_10-20EEG
## lindenmayer, 2019_TDCS_10-20EEG_WM_MCCB_1 TDCS_10-20EEG
## lindenmayer, 2019_TDCS_10-20EEG_VerL_MCCB_1 TDCS_10-20EEG
## lindenmayer, 2019_TDCS_10-20EEG_VisL_MCCB_1 TDCS_10-20EEG
## lindenmayer, 2019_TDCS_10-20EEG_RPN_MCCB_1 TDCS_10-20EEG
## lindenmayer, 2019_TDCS_10-20EEG_SC_MCCB_1 TDCS_10-20EEG
## lisoni, 2022_TDCS_10-20 EEG_PANSS-P_1 TDCS_10-20 EEG
## lisoni, 2022_TDCS_10-20 EEG_PANSS-N_1 TDCS_10-20 EEG
## lisoni, 2022_TDCS_10-20 EEG_PANSS-T_1 TDCS_10-20 EEG
## lisoni, 2022_TDCS_10-20 EEG_PANSS-G_1 TDCS_10-20 EEG
## lisoni, 2022_TDCS_10-20 EEG_GC_BACS (Composite z-scores)_1 TDCS_10-20 EEG
## lisoni, 2022_TDCS_10-20 EEG_VerL_BACS z-scores (Verbal memory)_1 TDCS_10-20 EEG
## lisoni, 2022_TDCS_10-20 EEG_WM_BACS z-scores (Digit sequencing)_1 TDCS_10-20 EEG
## lisoni, 2022_TDCS_10-20 EEG_PS_BACS z-scores (Verbal fluency)_1 TDCS_10-20 EEG
## lisoni, 2022_TDCS_10-20 EEG_PS_BACS z-scores (Symbol coding)_1 TDCS_10-20 EEG
## lisoni, 2022_TDCS_10-20 EEG_RPS_BACS z-scores (Tower of London)_1 TDCS_10-20 EEG
## liu, 2024_HF-RTMS_NA_T_PANSS_1 SHAM
## liu, 2024_HF-RTMS_NA_P_PANSS_1 SHAM
## liu, 2024_HF-RTMS_NA_N_PANSS_1 SHAM
## liu, 2024_HF-RTMS_NA_G_PANSS_1 SHAM
## liu, 2024_HF-RTMS_NA_VerL_RBANS (Immediate memory)_1 SHAM
## liu, 2024_HF-RTMS_NA_VisL_RBANS (Visual spatial structure)_1 SHAM
## liu, 2024_HF-RTMS_NA_PS_RBANS (Speech function)_1 SHAM
## liu, 2024_HF-RTMS_NA_WM_RBANS (Attention)_1 SHAM
## liu, 2024_HF-RTMS_NA_Visl_RBANS (Delayed memory)_1 SHAM
## lyu, 2024_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## lyu, 2024_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG
## lyu, 2024_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG
## lyu, 2024_TDCS_10-20EEG_G_PANSS_1 TDCS_10-20EEG
## lyu, 2024_TDCS_10-20EEG_N_SANS_1 TDCS_10-20EEG
## mao, 2023_HF-RTMS_CM_GC_RBANS_1 SHAM
## mao, 2023_HF-RTMS_CM_VerL_RBANS-Immediate Memory_1 SHAM
## mao, 2023_HF-RTMS_CM_RBANS-Visuospatial_1 SHAM
## mao, 2023_HF-RTMS_CM_VerL_RBANS-Language_1 SHAM
## mao, 2023_HF-RTMS_CM_WM_RBANS-Attention_1 SHAM
## mao, 2023_HF-RTMS_CM_VerL_RBANS-Delayed memory_1 SHAM
## mao, 2023_HF-RTMS_CM_P_AHRS_1 SHAM
## mao, 2023_HF-RTMS_CM_T_PANSS_1 SHAM
## marquardt, 2022_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG
## marquardt, 2022_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG
## marquardt, 2022_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG
## marquardt, 2022_TDCS_10-20EEG_RPS_Stroop 3 (s/RT)_1 TDCS_10-20EEG
## marquardt, 2022_TDCS_10-20EEG_RPS_Stroop 4 (s/RT)_1 TDCS_10-20EEG
## marquardt, 2022_TDCS_10-20EEG_PS_TMT-A_1 TDCS_10-20EEG
## marquardt, 2022_TDCS_10-20EEG_RPS_TMT-B_1 TDCS_10-20EEG
## mcintosh, 2004_LF-RTMS_10-20EEG_P_PANSS_1 SHAM
## mcintosh, 2004_LF-RTMS_10-20EEG_N_PANSS_1 SHAM
## mcintosh, 2004_LF-RTMS_10-20EEG_VerL_AVLT_1 SHAM
## meiron, 2021_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## meiron, 2021_TDCS_10-20EEG_WM_(verbal) WM - Accuracy_1 TDCS_10-20EEG
## meiron, 2021_TDCS_10-20EEG_WM_(verbal) WM - RT_1 TDCS_10-20EEG
## meiron, 2024_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## meiron, 2024_TDCS_10-20EEG_WM_2-BACK Acc_1 TDCS_10-20EEG
## meiron, 2024_TDCS_10-20EEG_WM_2-BACK RT_1 TDCS_10-20EEG
## mellin-tacs, 2018_TACS_10-20EEG_P_AHRS_1 TACS_10-20EEG
## mellin-tacs, 2018_TACS_10-20EEG_T_PANSS-T_1 TACS_10-20EEG
## mellin-tacs, 2018_TACS_10-20EEG_P_PANSS-P_1 TACS_10-20EEG
## mellin-tacs, 2018_TACS_10-20EEG_N_PANSS-N_1 TACS_10-20EEG
## mellin-tacs, 2018_TACS_10-20EEG_G_PANSS-G_1 TACS_10-20EEG
## mellin-tacs, 2018_TACS_10-20EEG_GC_BACS_1 TACS_10-20EEG
## mellin-tdcs, 2018_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG
## mellin-tdcs, 2018_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## mellin-tdcs, 2018_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG
## mellin-tdcs, 2018_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG
## mellin-tdcs, 2018_TDCS_10-20EEG_G_PANSS_1 TDCS_10-20EEG
## mellin-tdcs, 2018_TDCS_10-20EEG_GC_BACS_1 TDCS_10-20EEG
## moeller, 2022_DTMS_CM_T_PANSS_1 SHAM
## moeller, 2022_DTMS_CM_P_PANSS_1 SHAM
## moeller, 2022_DTMS_CM_N_PANSS_1 SHAM
## mogg, 2007_HF-RTMS_CM_VerL_HVLT immediate recall_1 SHAM
## mogg, 2007_HF-RTMS_CM_VerL_HVLT delayed recall_1 SHAM
## mogg, 2007_HF-RTMS_CM_PS_COWAT (number)_1 SHAM
## mogg, 2007_HF-RTMS_CM_RPS_Stroop RT (seconds)_1 SHAM
## mondino, 2015_TDCS_10-20EG_P_PANSS_1 TDCS_10-20EG
## mondino, 2015_TDCS_10-20EG_N_PANSS_1 TDCS_10-20EG
## mondino, 2015_TDCS_10-20EG_G_PANSS_1 TDCS_10-20EG
## mondino, 2015_TDCS_10-20EG_P_AHRS_1 TDCS_10-20EG
## novak, 2006_HF-RTMS_CM_T_PANSS_1 SHAM
## novak, 2006_HF-RTMS_CM_P_PANSS_1 SHAM
## novak, 2006_HF-RTMS_CM_N_PANSS_1 SHAM
## novak, 2006_HF-RTMS_CM_G_PANSS_1 SHAM
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_SAPS_1 SHAM
## paillere-martinot, 2017_LF-RTMS_NEURONAV_N_SANS_1 SHAM
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_AHRS_1 SHAM
## palm, 2016_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## palm, 2016_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG
## palm, 2016_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG
## palm, 2016_TDCS_10-20EEG_N_SANS_1 TDCS_10-20EEG
## palm, 2016_TDCS_10-20EEG_WM_SOPT_1 TDCS_10-20EEG
## palm, 2016_TDCS_10-20EEG_PS_TMT-A_1 TDCS_10-20EEG
## palm, 2016_TDCS_10-20EEG_RPS_TMT-B_1 TDCS_10-20EEG
## prikryl, 2007_HF-RTMS_CM_T_PANSS_1 SHAM
## prikryl, 2007_HF-RTMS_CM_P_PANSS_1 SHAM
## prikryl, 2007_HF-RTMS_CM_N_PANSS_1 SHAM
## prikryl, 2007_HF-RTMS_CM_N_SANS_1 SHAM
## prikryl, 2007_HF-RTMS_CM_P_SAPS_1 SHAM
## prikryl, 2012_HF-RTMS_CM_P_PANSS_1 SHAM
## prikryl, 2012_HF-RTMS_CM_N_PANSS_1 SHAM
## prikryl, 2012_HF-RTMS_CM_G_PANSS_1 SHAM
## prikryl, 2012_HF-RTMS_CM_T_PANSS_1 SHAM
## prikryl, 2012_HF-RTMS_CM_PS_VFT_1 SHAM
## prikryl, 2014_HF-RTMS_CM_T_PANSS_1 SHAM
## prikryl, 2014_HF-RTMS_CM_P_PANSS_1 SHAM
## prikryl, 2014_HF-RTMS_CM_N_PANSS_1 SHAM
## prikryl, 2014_HF-RTMS_CM_G_PANSS_1 SHAM
## prikryl, 2013_HF-RTMS_CM_N_SANS_1 SHAM
## prikryl, 2013_HF-RTMS_CM_P_SAPS_1 SHAM
## quan, 2015_HF-RTMS_CM_T_PANSS_1 SHAM
## quan, 2015_HF-RTMS_CM_P_PANSS_1 SHAM
## quan, 2015_HF-RTMS_CM_N_PANSS_1 SHAM
## quan, 2015_HF-RTMS_CM_G_PANSS_1 SHAM
## quan, 2015_HF-RTMS_CM_N_SANS_1 SHAM
## rabany, 2014_DTMS_CM_T_PANSS_1 SHAM
## rabany, 2014_DTMS_CM_N_PANSS_1 SHAM
## rabany, 2014_DTMS_CM_N_SANS_1 SHAM
## rabany, 2014_DTMS_CM_AV_RVP-A_1 SHAM
## rabany, 2014_DTMS_CM_AV_RVP-B_1 SHAM
## rabany, 2014_DTMS_CM_WM_SWM (Total between search errors)_1 SHAM
## rabany, 2014_DTMS_CM_WM_SWM (Strategy score)_1 SHAM
## rabany, 2014_DTMS_CM_RPS_SOC (Minimum move solutions for test trials)_1 SHAM
## rabany, 2014_DTMS_CM_RPS_SOC (Initial times for 5 move problems)_1 SHAM
## rabany, 2014_DTMS_CM_RPS_SOC (Subsequent times for 5 move problems)_1 SHAM
## rabany, 2014_DTMS_CM_PS_RTI (Mean reaction time, stages 4 and 5)_1 SHAM
## rabany, 2014_DTMS_CM_PS_RTI (Mean movement time, stages 4 and 5)_1 SHAM
## rollnik, 2000_HF-RTMS_CM_T_BPRS_1 SHAM
## rollnik, 2000_HF-RTMS_CM_PS_NCT (seconds)_1 SHAM
## rosa, 2007_LF-RTMS_10-20EEG_T_PANSS_1 SHAM
## rosa, 2007_LF-RTMS_10-20EEG_P_PANSS_1 SHAM
## rosa, 2007_LF-RTMS_10-20EEG_N_PANSS_1 SHAM
## rosa, 2007_LF-RTMS_10-20EEG_G_PANSS_1 SHAM
## rosenberg, 2012_LF-RTMS_CM_P_AHRS_1 SHAM
## saba, 2006_LF-RTMS_CM_T_PANSS_1 SHAM
## saba, 2006_LF-RTMS_CM_P_PANSS_1 SHAM
## saba, 2006_LF-RTMS_CM_N_PANSS_1 SHAM
## saba, 2006_LF-RTMS_CM_G_PANSS_1 SHAM
## schilling, 2021_TDCS_10-20EEG_WM_Verbal Working Memory Reaction Time (t-score)_1 TDCS_10-20EEG
## schilling, 2021_TDCS_10-20EEG_WM_Verbal Working Memory d-prime (z-score)_1 TDCS_10-20EEG
## schilling, 2021_TDCS_10-20EEG_RPS_Response Inhibition Reaction Time (t-score)_1 TDCS_10-20EEG
## schilling, 2021_TDCS_10-20EEG_RPS_Response Inhibition Errors (t-scores)_1 TDCS_10-20EEG
## schilling, 2021_TDCS_10-20EEG_RPS_Problem solving t-score_1 TDCS_10-20EEG
## schilling, 2021_TDCS_10-20EEG_RPS_Mental Flexibility Speed (t-score)_1 TDCS_10-20EEG
## schilling, 2021_TDCS_10-20EEG_RPS_Mental Flexibility Accuracy (t-score)_1 TDCS_10-20EEG
## singh, 2020_HF-RTMS_CM_P_PANSS_1 SHAM
## singh, 2020_HF-RTMS_CM_N_PANSS_1 SHAM
## singh, 2020_HF-RTMS_CM_N_SANS_1 SHAM
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_AHRS_1 SHAM
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_PANSS_1 SHAM
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_AHRS_1 SHAM
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_PANSS_1 SHAM
## smith, 2015_TDCS_10-20EEG_GC_MCCB_1 TDCS_10-20EEG
## smith, 2015_TDCS_10-20EEG_WM_MCCB_1 TDCS_10-20EEG
## smith, 2015_TDCS_10-20EEG_AV_MCCB_1 TDCS_10-20EEG
## smith, 2015_TDCS_10-20EEG_RPS_MCCB_1 TDCS_10-20EEG
## smith, 2015_TDCS_10-20EEG_VerL_MCCB_1 TDCS_10-20EEG
## smith, 2015_TDCS_10-20EEG_VisL_MCCB_1 TDCS_10-20EEG
## smith, 2015_TDCS_10-20EEG_PS_MCCB_1 TDCS_10-20EEG
## smith, 2015_TDCS_10-20EEG_SC_MCCB_1 TDCS_10-20EEG
## smith, 2015_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## smith, 2015_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG
## smith, 2015_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG
## smith, 2015_TDCS_10-20EEG_G_PANSS_1 TDCS_10-20EEG
## smith, 2020_TDCS_10-20EEG_GC_MCCB_1 TDCS_10-20EEG
## smith, 2020_TDCS_10-20EEG_PS_MCCB_1 TDCS_10-20EEG
## smith, 2020_TDCS_10-20EEG_AV_MCCB_1 TDCS_10-20EEG
## smith, 2020_TDCS_10-20EEG_WM_MCCB_1 TDCS_10-20EEG
## smith, 2020_TDCS_10-20EEG_VerL_MCCB_1 TDCS_10-20EEG
## smith, 2020_TDCS_10-20EEG_VisL_MCCB_1 TDCS_10-20EEG
## smith, 2020_TDCS_10-20EEG_RPS_MCCB_1 TDCS_10-20EEG
## smith, 2020_TDCS_10-20EEG_SC_MCCB_1 TDCS_10-20EEG
## smith, 2020_TDCS_10-20EEG_AV_PASAT (Number Correct)_1 TDCS_10-20EEG
## smith, 2020_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## smith, 2020_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG
## smith, 2020_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG
## su, 2023b_HF-RTMS_NEURONAV_T_PANSS_1 SHAM
## su, 2023b_HF-RTMS_NEURONAV_P_PANSS_1 SHAM
## su, 2023b_HF-RTMS_NEURONAV_N_PANSS_1 SHAM
## su, 2023b_HF-RTMS_NEURONAV_G_PANSS_1 SHAM
## su, 2022_HF-RTMS_NEURONAV_T_PANSS_1 SHAM
## su, 2022_HF-RTMS_NEURONAV_P_PANSS_1 SHAM
## su, 2022_HF-RTMS_NEURONAV_N_PANSS_1 SHAM
## su, 2022_HF-RTMS_NEURONAV_G_PANSS_1 SHAM
## tikka, 2017_CTBS_NEURONAV_P_PANSS_1 SHAM
## tikka, 2017_CTBS_NEURONAV_N_PANSS_1 SHAM
## tikka, 2017_CTBS_NEURONAV_G_PANSS_1 SHAM
## tikka, 2017_CTBS_NEURONAV_T_PANSS_1 SHAM
## tikka, 2017_CTBS_NEURONAV_RPS_Self-Monitoring Task_1 SHAM
## tikka, 2017_CTBS_NEURONAV_WM_Visual Memory Task_1 SHAM
## tyagi, 2022_CTBS_10-20EEG_P_PANSS_1 SHAM
## tyagi, 2022_CTBS_10-20EEG_N_PANSS_1 SHAM
## tyagi, 2022_CTBS_10-20EEG_T_PANSS_1 SHAM
## tyagi, 2022_CTBS_10-20EEG_G_PANSS_1 SHAM
## tyagi, 2022_CTBS_10-20EEG_P_AVHRS_1 SHAM
## tyagi, 2022_CTBS_10-20EEG_P_PSYRAT-AH_1 SHAM
## valiengo, 2020_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG
## valiengo, 2020_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG
## valiengo, 2020_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## valiengo, 2020_TDCS_10-20EEG_G_PANSS_1 TDCS_10-20EEG
## valiengo, 2020_TDCS_10-20EEG_P_AVHRS_1 TDCS_10-20EEG
## vercammen, 2011_TDCS_10-20EEG_RPS_Weather Prediction Test_1 TDCS_10-20EEG
## vergallito, 2024_ITBS_10-20EEG_T_PANSS_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_P_PANSS_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_N_PANSS_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_N_BNSS_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_GC_MCCB_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_PS_MCCB_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_AV_MCCB_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_WM_MCCB_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_VerL_MCCB_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_VisL_MCCB_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_RPS_MCCB_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_SC_MCCB_1 SHAM
## walther-lft, 2024_UNKNOWN_STANDARD_T_PANSS_1 UNKNOWN_STANDARD
## walther-lft, 2024_UNKNOWN_STANDARD_P_PANSS_1 UNKNOWN_STANDARD
## walther-lft, 2024_UNKNOWN_STANDARD_N_PANSS_1 UNKNOWN_STANDARD
## walther-lft, 2024_UNKNOWN_STANDARD_G_PANSS_1 UNKNOWN_STANDARD
## walther-lft, 2024_UNKNOWN_STANDARD_N_BNSS_1 UNKNOWN_STANDARD
## walther-itbs, 2024_ITBS_CM_T_PANSS_1 SHAM
## walther-itbs, 2024_ITBS_CM_P_PANSS_1 SHAM
## walther-itbs, 2024_ITBS_CM_N_PANSS_1 SHAM
## walther-itbs, 2024_ITBS_CM_G_PANSS_1 SHAM
## walther-itbs, 2024_ITBS_CM_N_BNSS_1 SHAM
## wang, 2020_ITBS_NEURONAV_T_PANSS_1 SHAM
## wang, 2020_ITBS_NEURONAV_P_PANSS_1 SHAM
## wang, 2020_ITBS_NEURONAV_N_PANSS_1 SHAM
## wang, 2020_ITBS_NEURONAV_G_PANSS_1 SHAM
## wang, 2020_ITBS_NEURONAV_P_SAPS_1 SHAM
## wang, 2020_ITBS_NEURONAV_N_SANS_1 SHAM
## wang, 2020_ITBS_NEURONAV_GC_MoCA_1 SHAM
## wang, 2020_ITBS_NEURONAV_PS_VFT_1 SHAM
## wang, 2020_ITBS_NEURONAV_WM_Digit span (forward)_1 SHAM
## wang, 2020_ITBS_NEURONAV_WM_Digit span (backward)_1 SHAM
## wang, 2020_ITBS_NEURONAV_RPS_Stroop Color Test_1 SHAM
## wang, 2020_ITBS_NEURONAV_RPS_Stroop Word Test_1 SHAM
## wang, 2020_ITBS_NEURONAV_RPS_Stroop Interference Test_1 SHAM
## wang, 2020_ITBS_NEURONAV_PS_TMT-A_1 SHAM
## wang, 2020_ITBS_NEURONAV_RPS_TMT-B_1 SHAM
## wang, 2022_ITBS_NEURONAV_P_PANSS_1 SHAM
## wang, 2022_ITBS_NEURONAV_N_PANSS_1 SHAM
## wang, 2022_ITBS_NEURONAV_G_PANSS_1 SHAM
## wang, 2022_ITBS_NEURONAV_T_PANSS_1 SHAM
## wang, 2022_ITBS_NEURONAV_P_SAPS_1 SHAM
## wang, 2022_ITBS_NEURONAV_N_SANS_1 SHAM
## wang, 2022_ITBS_NEURONAV_GC_MoCA_1 SHAM
## wang, 2022_ITBS_NEURONAV_WM_3-back RT_1 SHAM
## weickert, 2019_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## weickert, 2019_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG
## weickert, 2019_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG
## weickert, 2019_TDCS_10-20EEG_G_PANSS_1 TDCS_10-20EEG
## weickert, 2019_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG
## weickert, 2019_TDCS_10-20EEG_PS_BACS sc_1 TDCS_10-20EEG
## weickert, 2019_TDCS_10-20EEG_PS_TMT-A_1 TDCS_10-20EEG
## weickert, 2019_TDCS_10-20EEG_WM_LNS_1 TDCS_10-20EEG
## weickert, 2019_TDCS_10-20EEG_VerL_HVLTr_1 TDCS_10-20EEG
## weickert, 2019_TDCS_10-20EEG_VisL_BVMT_1 TDCS_10-20EEG
## weickert, 2019_TDCS_10-20EEG_RPS_NAB maze_1 TDCS_10-20EEG
## weickert, 2019_TDCS_10-20EEG_PS_fluency_1 TDCS_10-20EEG
## wen, 2021_HF-RTMS_CM_T_PANSS_1 SHAM
## wen, 2021_HF-RTMS_CM_P_PANSS_1 SHAM
## wen, 2021_HF-RTMS_CM_N_PANSS_1 SHAM
## wen, 2021_HF-RTMS_CM_G_PANSS_1 SHAM
## wen, 2021_HF-RTMS_CM_GC_RBANS-T_1 SHAM
## wen, 2021_HF-RTMS_CM_VerL_RBANS\r\nImmediate memory_1 SHAM
## wen, 2021_HF-RTMS_CM_WM_RBANS\r\nAttention_1 SHAM
## wen, 2021_HF-RTMS_CM_VisL_RBANS\r\nVisuospatial_1 SHAM
## wen, 2021_HF-RTMS_CM_VisL_RBANS\r\nDelayed memory_1 SHAM
## wen, 2021_HF-RTMS_CM_VerL_RBANS\r\nLanguage_1 SHAM
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n1 word (s)_1 SHAM
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n2 word (s)_1 SHAM
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n3 word (s)_1 SHAM
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n3 color (s)_1 SHAM
## wobrock, 2015_HF-RTMS_10-20EEG_T_PANSS_1 SHAM
## wobrock, 2015_HF-RTMS_10-20EEG_P_PANSS_1 SHAM
## wobrock, 2015_HF-RTMS_10-20EEG_N_PANSS_1 SHAM
## xie, 2023-a_LF-RTMS_10-20EEG_T_PANSS_1 SHAM
## xie, 2023-a_LF-RTMS_10-20EEG_P_PANSS_1 SHAM
## xie, 2023-a_LF-RTMS_10-20EEG_N_PANSS_1 SHAM
## xie, 2023-a_LF-RTMS_10-20EEG_G_PANSS_1 SHAM
## xie, 2023-a_LF-RTMS_10-20EEG_P_AHRS_1 SHAM
## xiu-10hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 SHAM
## xiu-10hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 SHAM
## xiu-10hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 SHAM
## xiu-10hz, 2020_HF-RTMS_NEURONAV_G_PANSS_1 SHAM
## xiu-10hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 SHAM
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nImmediate memory_1 SHAM
## xiu-10hz, 2020_HF-RTMS_NEURONAV_WM_RBANS\r\nAttention_1 SHAM
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nVisuospatial_1 SHAM
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nDelayed memory_1 SHAM
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nLanguage_1 SHAM
## xiu-20hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 SHAM
## xiu-20hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 SHAM
## xiu-20hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 SHAM
## xiu-20hz, 2020_HF-RTMS_NEURONAV_G_PANSS_1 SHAM
## xiu-20hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 SHAM
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nImmediate memory_1 SHAM
## xiu-20hz, 2020_HF-RTMS_NEURONAV_WM_RBANS\r\nAttention_1 SHAM
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nVisuospatial_1 SHAM
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nDelayed memory_1 SHAM
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nLanguage_1 SHAM
## xu, 2023_HD-TDCS_10-20EEG_T_PANSS_1 SHAM
## xu, 2023_HD-TDCS_10-20EEG_P_PANSS_1 SHAM
## xu, 2023_HD-TDCS_10-20EEG_N_PANSS_1 SHAM
## xu, 2023_HD-TDCS_10-20EEG_G_PANSS_1 SHAM
## xu, 2023_HD-TDCS_10-20EEG_GC_RBANS_1 SHAM
## ye-20hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 SHAM
## ye-20hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Immediate memory_1 SHAM
## ye-20hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Visuospatial_1 SHAM
## ye-20hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Language_1 SHAM
## ye-20hz, 2024_HF-RTMS_NEURONAV_WM_RBANS - Attention_1 SHAM
## ye-20hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Delayed memory_1 SHAM
## ye-10hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 SHAM
## ye-10hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Immediate memory_1 SHAM
## ye-10hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Visuospatial_1 SHAM
## ye-10hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Language_1 SHAM
## ye-10hz, 2024_HF-RTMS_NEURONAV_WM_RBANS - Attention_1 SHAM
## ye-10hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Delayed memory_1 SHAM
## yuanjun, 2024_LF-RTMS_10-20EEG_T_PANSS_1 SHAM
## yuanjun, 2024_LF-RTMS_10-20EEG_P_PANSS_1 SHAM
## yuanjun, 2024_LF-RTMS_10-20EEG_N_PANSS_1 SHAM
## yuanjun, 2024_LF-RTMS_10-20EEG_G_PANSS_1 SHAM
## yuanjun, 2024_LF-RTMS_10-20EEG_P_AHRS_1 SHAM
## zhai-a, 2023_HF-RTMS_NA_T_PANSS_1 SHAM
## zhang, 2022_TACS_10-20EEG_T_PANSS_1 TACS_10-20EEG
## zhang, 2022_TACS_10-20EEG_P_PANSS_1 TACS_10-20EEG
## zhang, 2022_TACS_10-20EEG_N_PANSS_1 TACS_10-20EEG
## zhang, 2022_TACS_10-20EEG_P_AHRS_1 TACS_10-20EEG
## zhao-tbs, 2014_ITBS_10-20EEG_T_PANSS_1 SHAM
## zhao-tbs, 2014_ITBS_10-20EEG_P_PANSS_1 SHAM
## zhao-tbs, 2014_ITBS_10-20EEG_N_PANSS_1 SHAM
## zhao-tbs, 2014_ITBS_10-20EEG_G_PANSS_1 SHAM
## zhao-tbs, 2014_ITBS_10-20EEG_N_SANS_1 SHAM
## zhao-20hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 SHAM
## zhao-20hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 SHAM
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 SHAM
## zhao-20hz, 2014_HF-RTMS_10-20EEG_G_PANSS_1 SHAM
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 SHAM
## zhao-10hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 SHAM
## zhao-10hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 SHAM
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 SHAM
## zhao-10hz, 2014_HF-RTMS_10-20EEG_G_PANSS_1 SHAM
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 SHAM
## zhou, 2024_HF-RTMS_10-20EEG_P_PANSS_1 SHAM
## zhou, 2024_HF-RTMS_10-20EEG_N_PANSS_1 SHAM
## zhou, 2024_HF-RTMS_10-20EEG_T_PANSS_1 SHAM
## zhou, 2024_HF-RTMS_10-20EEG_G_PANSS_1 SHAM
## zhou, 2024_HF-RTMS_10-20EEG_GC_RBANS-T_1 SHAM
## zhou, 2024_HF-RTMS_10-20EEG_VerL_RBANS\r\nImmediate memory_1 SHAM
## zhou, 2024_HF-RTMS_10-20EEG_VisL_RBANS\r\nVisuospatial_1 SHAM
## zhou, 2024_HF-RTMS_10-20EEG_VerL_RBANS\r\nLanguage_1 SHAM
## zhou, 2024_HF-RTMS_10-20EEG_WM_RBANS\r\nAttention_1 SHAM
## zhou, 2024_HF-RTMS_10-20EEG_VisL_RBANS\r\nDelayed memory_1 SHAM
## zhou, 2024_HF-RTMS_10-20EEG_RPS_SCWT \r\nInference scores_1 SHAM
## zhou, 2023_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## zhou, 2023_TDCS_10-20EEG_N_SANS_1 TDCS_10-20EEG
## zhou, 2023_TDCS_10-20EEG_RPS_IED total errors_1 TDCS_10-20EEG
## zhu, 2021_ITBS_CM_N_PANSS_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_T_PANSS_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_P_PANSS_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_N_PANSS_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_G_PANSS_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_N_SANS_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_PS_MCCB TMT-A_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_PS_MCCB BACS_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_PS_MCCB Fluency_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_WM_MCCB Working memory (WMS-SS)_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_VerL_MCCB Verbal learning (HVLT-R)_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_VisL_MCCB Visual learning (BVMT-R)_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_RPS_MCCB Reasoning/problem solving (NAB)_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_SC_MCCB Social cognition (MSCEIT)_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_GC_MCCB Composite score_1 SHAM
## TE
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANSS_1 1.1200
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANSS_1 0.8000
## bais, 2014 - l_LF-RTMS_10-20EEG_G_PANSS_1 0.8000
## bais, 2014 - l_LF-RTMS_10-20EEG_P_AHRS_1 -0.9400
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANAS_1 -2.3800
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANAS_1 2.6300
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANSS_1 0.4600
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANSS_1 -0.1500
## bais, 2014 - bi_LF-RTMS_10-20EEG_G_PANSS_1 0.0200
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_AHRS_1 -0.7900
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANAS_1 -3.8000
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANAS_1 2.4000
## barr, 2011_HF-RTMS_NEURONAV_WM_1-back RT ms_1 -112.7900
## barr, 2011_HF-RTMS_NEURONAV_WM_2-back RT ms_1 -155.7700
## barr, 2011_HF-RTMS_NEURONAV_WM_3-back RT ms_1 -168.1000
## barr, 2013_HF-RTMS_NEURONAV_WM_1-back RT ms Target Correct_1 -28.1500
## barr, 2013_HF-RTMS_NEURONAV_WM_1-back RT ms Non Target Correct_1 -10.0400
## barr, 2013_HF-RTMS_NEURONAV_WM_3-back RT ms Target Correct_1 -126.1400
## barr, 2013_HF-RTMS_NEURONAV_WM_3-back RT ms Non Target Correct_1 -73.6300
## barr, 2012_HF-RTMS_NEURONAV_P_PANSS_1 2.2700
## barr, 2012_HF-RTMS_NEURONAV_N_PANSS_1 -2.9600
## barr, 2012_HF-RTMS_NEURONAV_N_SANS_1 -0.1200
## basavaraju, 2021_ITBS_NEURONAV_N_SANS_1 -2.5000
## basavaraju, 2021_ITBS_NEURONAV_P_SAPS_1 -0.1667
## basavaraju, 2021_ITBS_NEURONAV_VerL_AVLT Hits_1 -0.5357
## basavaraju, 2021_ITBS_NEURONAV_VisL_CFT copying_1 -0.6170
## basavaraju, 2021_ITBS_NEURONAV_VisL_CFT Immediate Recall_1 -1.0314
## basavaraju, 2021_ITBS_NEURONAV_VisL_CFT Delayed Recall_1 -2.1022
## basavaraju, 2021_ITBS_NEURONAV_PS_DSST time (sec)_1 36.1911
## basavaraju, 2021_ITBS_NEURONAV_PS_DSST errors_1 0.4534
## basavaraju, 2021_ITBS_NEURONAV_AV_DVT time (sec)_1 -18.9285
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-A time (sec)_1 9.0140
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-A errors_1 0.0983
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-B time (sec)_1 -15.1432
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-B errors_1 -0.2507
## basavaraju, 2021_ITBS_NEURONAV_WM_1back verbal Hits_1 0.7595
## basavaraju, 2021_ITBS_NEURONAV_WM_1back verbal Errors_1 -0.9833
## basavaraju, 2021_ITBS_NEURONAV_WM_2back verbal Hits_1 -0.1232
## basavaraju, 2021_ITBS_NEURONAV_WM_2back verbal Errors_1 0.7148
## basavaraju, 2021_ITBS_NEURONAV_WM_Spatial Span total_1 0.2048
## basavaraju, 2021_ITBS_NEURONAV_RPS_FAS_1 -1.7200
## basavaraju, 2021_ITBS_NEURONAV_RPS_Stroop Effect score_1 20.6870
## basavaraju, 2021_ITBS_NEURONAV_SC_FOT index_1 -0.0107
## basavaraju, 2021_ITBS_NEURONAV_SC_SOT index_1 0.1095
## basavaraju, 2021_ITBS_NEURONAV_SC_Faux Pax CI_1 -0.0552
## basavaraju, 2021_ITBS_NEURONAV_SC_Personalizing Bias Index_1 -0.2799
## basavaraju, 2021_ITBS_NEURONAV_SC_Social Perception Index_1 0.0243
## basavaraju, 2021_ITBS_NEURONAV_SC_Emotion Recognition Index_1 -0.0059
## battion, 2021_ITBS_CM_T_PANSS_1 2.2500
## battion, 2021_ITBS_CM_N_SANS_1 -0.2300
## blumberger, 2012_LF-RTMS_NEURONAV_P_PSYRATS_1 1.6200
## blumberger, 2012_LF-RTMS_NEURONAV_T_PANSS_1 1.8000
## blumberger, 2012_LF-RTMS_NEURONAV_P_PANSS_1 0.5200
## blumberger, 2012_LF-RTMS_NEURONAV_P_AHRS_1 2.3300
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PSYRATS_1 1.0100
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_T_PANSS_1 5.8700
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PANSS_1 0.5500
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_AHRS_1 0.8600
## bodén, 2021_ITBS_CM_N_CAIN_1 0.6100
## bose, 2018_TDCS_10-20EEG_P_SAPS_1 -0.4500
## bose, 2018_TDCS_10-20EEG_N_SANS_1 2.0600
## bose, 2018_TDCS_10-20EEG_P_AHRS_1 -7.5900
## brunelin, 2012_TDCS_10-20EEG_P_AHRS_1 -6.0000
## brunelin, 2012_TDCS_10-20EEG_T_PANSS_1 -7.7000
## brunelin, 2006_LF-RTMS_10-20EEG_P_AHRS_1 10.4000
## brunelin, 2006_LF-RTMS_10-20EEG_P_SAPS_1 9.7000
## brunelin, 2006_LF-RTMS_10-20EEG_WM_MonitorSourceTask_1 -1.0000
## bulubas, 2021_TDCS_10-20EEG_VisL_PFMT Total Correct Responses_1 -0.3500
## bulubas, 2021_TDCS_10-20EEG_VerL_PWMT Total Correct Responses_1 1.1100
## bulubas, 2021_TDCS_10-20EEG_SC_EMI Correct Responses_1 0.6500
## bulubas, 2021_TDCS_10-20EEG_WM_PLNB 0-back True Positive Responses_1 0.0700
## bulubas, 2021_TDCS_10-20EEG_WM_PLNB 1-back True Positive Responses_1 0.2900
## bulubas, 2021_TDCS_10-20EEG_WM_PLNB 2-back True Positive Responses_1 0.0800
## bulubas, 2021_TDCS_10-20EEG_RPS_PCET Number Correct Responses_1 0.6900
## bulubas, 2021_TDCS_10-20EEG_VisL_Short VOLT Total Correct_1 0.0300
## chang-a, 2021_TACS_10-20EEG_T_PANSS_1 -4.3900
## chang-a, 2021_TACS_10-20EEG_N_PANSS_1 -1.9500
## chang-a, 2021_TACS_10-20EEG_N_SANS_1 -4.9400
## chauhan, 2021_ITBS_10-20EEG_P_PANSS_1 -0.0000
## chauhan, 2021_ITBS_10-20EEG_N_PANSS_1 -0.1200
## chauhan, 2021_ITBS_10-20EEG_G_PANSS_1 -0.6900
## chauhan, 2021_ITBS_10-20EEG_T_PANSS_1 -0.8300
## chauhan, 2021_ITBS_10-20EEG_T_BPRS_1 -0.0700
## de jesus, 2011_LF-RTMS_10-20EEG_T_BPRS_1 6.0100
## de jesus, 2011_LF-RTMS_10-20EEG_P_BPRS_1 -1.4600
## de jesus, 2011_LF-RTMS_10-20EEG_N_BPRS_1 0.8500
## de jesus, 2011_LF-RTMS_10-20EEG_P_AHRS_1 3.5600
## dharani, 2021_HD-TDCS_10-10EEG_P_PANSS_1 0.5700
## dharani, 2021_HD-TDCS_10-10EEG_N_PANSS_1 2.8500
## dharani, 2021_HD-TDCS_10-10EEG_G_PANSS_1 2.1500
## dharani, 2021_HD-TDCS_10-10EEG_N_SANS_1 6.8600
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_SANS_1 6.2000
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_P_PANSS_1 -0.1000
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_PANSS_1 0.2000
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_G_PANSS_1 1.1000
## dolfus, 2018_HF-RTMS_NEURONAV_P_AHRS_1 -0.5600
## du, 2024_HF-RTMS_NEURONAV_T_BPRS_1 -1.0000
## du, 2024_HF-RTMS_NEURONAV_P_BPRS_1 -0.4100
## du, 2024_HF-RTMS_NEURONAV_N_BPRS_1 -0.1100
## du, 2022_HF-RTMS_10-20EEG_VisL_PRM number correct_1 1.0000
## du, 2022_HF-RTMS_10-20EEG_N_SANS_1 4.6000
## du, 2022_HF-RTMS_10-20EEG_T_PANSS_1 -0.6000
## du, 2022_HF-RTMS_10-20EEG_P_PANSS_1 0.7000
## du, 2022_HF-RTMS_10-20EEG_N_PANSS_1 0.6000
## du, 2022_HF-RTMS_10-20EEG_G_PANSS_1 1.8000
## farhang, 2024_TDCS_10-20EEG_WM_ letter-number sequencing_1 -2.6700
## fitzerald, 2008_LF-RTMS_CM_N_SANS_1 9.9000
## fitzerald, 2008_LF-RTMS_CM_P_PANSS_1 -2.3000
## fitzerald, 2008_LF-RTMS_CM_N_PANSS_1 0.6000
## fitzerald, 2008_LF-RTMS_CM_T_PANSS_1 -0.2000
## fitzerald-l, 2014_TDCS_10-20EEG_P_PANSS_1 -1.2000
## fitzerald-l, 2014_TDCS_10-20EEG_N_PANSS_1 1.7000
## fitzerald-l, 2014_TDCS_10-20EEG_T_PANSS_1 -0.9000
## fitzerald-l, 2014_TDCS_10-20EEG_N_SANS_1 1.8000
## fitzerald-bi, 2014_TDCS_10-20EEG_P_PANSS_1 -1.7000
## fitzerald-bi, 2014_TDCS_10-20EEG_N_PANSS_1 -9.0000
## fitzerald-bi, 2014_TDCS_10-20EEG_T_PANSS_1 -9.1000
## fitzerald-bi, 2014_TDCS_10-20EEG_N_SANS_1 3.2000
## francis, 2019_HF-RTMS_CM_VerL_BACS Verbal Memory_1 8.4400
## francis, 2019_HF-RTMS_CM_WM_BACS Digit Sequencing_1 -0.7500
## francis, 2019_HF-RTMS_CM_PS_BACS Semantic and Letter Fluency_1 5.8900
## francis, 2019_HF-RTMS_CM_PS_BACS Symbol Coding_1 3.9100
## francis, 2019_HF-RTMS_CM_RPS_BACS Tower of London_1 -1.0600
## francis, 2019_HF-RTMS_CM_GC_BACS Composite Score_1 2.7200
## frohlich, 2016_TDCS_10-20EEG_P_AHRS_1 2.1600
## frohlich, 2016_TDCS_10-20EEG_T_PANSS_1 3.3000
## frohlich, 2016_TDCS_10-20EEG_P_PANSS_1 2.7000
## frohlich, 2016_TDCS_10-20EEG_N_PANSS_1 -0.0800
## frohlich, 2016_TDCS_10-20EEG_G_PANSS_1 0.7000
## gao, 2024_ITBS_10-20EEG_P_PANSS_1 -0.0800
## gao, 2024_ITBS_10-20EEG_N_PANSS_1 3.5600
## gao, 2024_ITBS_10-20EEG_G_PANSS_1 -0.1600
## gao, 2024_ITBS_10-20EEG_T_PANSS_1 3.4600
## gao, 2024_ITBS_10-20EEG_N_SANS_1 5.0000
## garcía-fernández, 2024_TDCS_10-20EEG_PS_MCCB_1 0.2000
## garcía-fernández, 2024_TDCS_10-20EEG_AV_MCCB_1 0.5000
## garcía-fernández, 2024_TDCS_10-20EEG_WM_MCCB_1 -2.6000
## garcía-fernández, 2024_TDCS_10-20EEG_VerL_MCCB_1 -0.2000
## garcía-fernández, 2024_TDCS_10-20EEG_VisL_MCCB_1 -0.0000
## garcía-fernández, 2024_TDCS_10-20EEG_RPS_MCCB_1 0.5000
## garcía-fernández, 2024_TDCS_10-20EEG_SC_MCCB_1 -0.1000
## garg, 2016_DTMS_CM_P_PANSS_1 0.5000
## garg, 2016_DTMS_CM_N_PANSS_1 1.4500
## garg, 2016_DTMS_CM_G_PANSS_1 1.1000
## garg, 2016_DTMS_CM_T_PANSS_1 3.6000
## gogler, 2017_TDCS_10-20EEG_PS_C_1 8.3200
## gogler, 2017_TDCS_10-20EEG_WM_K_1 0.3600
## gogler, 2017_TDCS_10-20EEG_AV_α_1 -0.0000
## gomes, 2018_TDCS_10-20EEG_WM_MCCB_1 1.5000
## gomes, 2018_TDCS_10-20EEG_PS_MCCB_1 -2.5700
## gomes, 2018_TDCS_10-20EEG_AV_MCCB_1 0.0100
## gomes, 2018_TDCS_10-20EEG_VerL_MCCB_1 -0.8300
## gomes, 2018_TDCS_10-20EEG_VisL_MCCB_1 -1.9100
## gomes, 2018_TDCS_10-20EEG_RPS_MCCB_1 2.0800
## gomes, 2018_TDCS_10-20EEG_P_PANSS_1 -0.7500
## gomes, 2018_TDCS_10-20EEG_N_PANSS-N_1 -3.6600
## gomes, 2018_TDCS_10-20EEG_G_PANSS_1 -5.4100
## gomes, 2018_TDCS_10-20EEG_T_PANSS-T_1 -9.9200
## guan, 2020_HF-RTMS_NEURONAV_T_PANSS-T_1 -0.0000
## guan, 2020_HF-RTMS_NEURONAV_P_PANSS_1 -0.8000
## guan, 2020_HF-RTMS_NEURONAV_N_PANSS-N_1 -0.3000
## guan, 2020_HF-RTMS_NEURONAV_G_PANSS_1 1.1000
## guan, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nImmediate memory_1 11.3000
## guan, 2020_HF-RTMS_NEURONAV_WM_RBANS\r\nAttention_1 -3.4000
## guan, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nVisuospatial/constructional_1 1.3000
## guan, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nDelayed memory_1 3.5000
## guan, 2020_HF-RTMS_NEURONAV_PS_RBANS\r\nLanguage_1 -6.1000
## guan, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 3.6000
## guleken, 2020_HF-RTMS_CM_P_PANSS_1 19.9900
## guleken, 2020_HF-RTMS_CM_N_SANS_1 21.5000
## guleken, 2020_HF-RTMS_CM_RPS_WSCT total correct responses_1 -9.6700
## guleken, 2020_HF-RTMS_CM_RPS_WSCT perseverative errors_1 5.6400
## guleken, 2020_HF-RTMS_CM_WM_DST forward_1 0.3800
## guleken, 2020_HF-RTMS_CM_WM_DST backwards_1 0.0600
## guleken, 2020_HF-RTMS_CM_RPS_Total time_1 -22.8700
## guleken, 2020_HF-RTMS_CM_RPS_Total errors_1 0.7600
## guleken, 2020_HF-RTMS_CM_RPS_Stroop Interference_1 -12.8570
## guse, 2013_HF-RTMS_10-20EEG_PS_TMT-A_1 2.1000
## guse, 2013_HF-RTMS_10-20EEG_RPS_TMT-B_1 10.8000
## guse, 2013_HF-RTMS_10-20EEG_RPS_WCST Accuracy_1 0.1000
## guse, 2013_HF-RTMS_10-20EEG_RPS_WCST RT_1 229.0000
## guse, 2013_HF-RTMS_10-20EEG_AV_Sel. Attention Accuracy_1 0.0700
## guse, 2013_HF-RTMS_10-20EEG_AV_Sel. Attention RT_1 -45.0000
## guse, 2013_HF-RTMS_10-20EEG_AV_Div. Attention Accuracy_1 -0.1000
## guse, 2013_HF-RTMS_10-20EEG_AV_Div. Attention RT_1 16.0000
## guse, 2013_HF-RTMS_10-20EEG_WM_0-back Accuracy_1 0.6000
## guse, 2013_HF-RTMS_10-20EEG_WM_0-back RT_1 29.0000
## guse, 2013_HF-RTMS_10-20EEG_WM_1-back Accuracy_1 2.5000
## guse, 2013_HF-RTMS_10-20EEG_WM_1-back RT_1 19.0000
## guse, 2013_HF-RTMS_10-20EEG_WM_2-back Accuracy_1 -4.1000
## guse, 2013_HF-RTMS_10-20EEG_WM_2-back RT_1 -12.0000
## hasan, 2016_HF-RTMS_10-20EEG_WM_DST z score_1 0.1300
## hasan, 2016_HF-RTMS_10-20EEG_WM_DST Forward_1 -0.1000
## hasan, 2016_HF-RTMS_10-20EEG_WM_DST Backward_1 0.5000
## hasan, 2016_HF-RTMS_10-20EEG_PS_TMT-A time (s)_1 -4.7000
## hasan, 2016_HF-RTMS_10-20EEG_RPS_TMT-B time (s)_1 -19.7000
## hasan, 2016_HF-RTMS_10-20EEG_VerL_VLMT z score_1 0.2400
## hasan, 2016_HF-RTMS_10-20EEG_RPS_WCST z score_1 0.2300
## hasan, 2016_HF-RTMS_10-20EEG_RPS_WCST total correct score_1 0.2000
## hasan, 2016_HF-RTMS_10-20EEG_RPS_WCST total errors_1 -2.4000
## hasan, 2016_HF-RTMS_10-20EEG_PS_RWT z score_1 -0.0600
## holi, 2004_HF-RTMS_10-20EEG_T_PANSS_1 -11.8000
## holi, 2004_HF-RTMS_10-20EEG_P_PANSS_1 -4.3000
## holi, 2004_HF-RTMS_10-20EEG_N_PANSS_1 -4.4000
## holi, 2004_HF-RTMS_10-20EEG_G_PANSS_1 -3.6000
## hu, 2024_LF-RTMS_10-20EEG_T_PANSS_1 9.2700
## hu, 2024_LF-RTMS_10-20EEG_P_PANSS_1 2.5000
## hu, 2024_LF-RTMS_10-20EEG_N_PANSS_1 2.4000
## hu, 2024_LF-RTMS_10-20EEG_G_PANSS_1 5.0000
## hu, 2024_LF-RTMS_10-20EEG_PS_TMT-A_1 -4.0000
## hu, 2024_LF-RTMS_10-20EEG_PS_BACS Symbol Coding_1 1.0000
## hu, 2024_LF-RTMS_10-20EEG_PS_Category Fluency_1 -0.1000
## hu, 2024_LF-RTMS_10-20EEG_AV_CPT-IP_1 0.1000
## hu, 2024_LF-RTMS_10-20EEG_WM_WMS-3 spatial span_1 1.4000
## hu, 2024_LF-RTMS_10-20EEG_VerL_HVLT-R_1 2.0000
## hu, 2024_LF-RTMS_10-20EEG_VisL_BVMT-R_1 1.7000
## hu, 2024_LF-RTMS_10-20EEG_RPS_NAB_1 0.4000
## hu, 2023_LF-RTMS_10-10EEG_T_PANSS_1 9.9300
## hu, 2023_LF-RTMS_10-10EEG_P_PANSS_1 2.0400
## hu, 2023_LF-RTMS_10-10EEG_N_PANSS_1 2.3100
## hu, 2023_LF-RTMS_10-10EEG_G_PANSS_1 5.5800
## hu, 2023_LF-RTMS_10-10EEG_GC_MCCB-T_1 4.1200
## hu, 2023_LF-RTMS_10-10EEG_PS_MCCB_1 -0.1100
## hu, 2023_LF-RTMS_10-10EEG_AV_MCCB_1 1.6200
## hu, 2023_LF-RTMS_10-10EEG_WM_MCCB_1 2.6800
## hu, 2023_LF-RTMS_10-10EEG_VerL_MCCB_1 2.7800
## hu, 2023_LF-RTMS_10-10EEG_VisL_MCCB_1 2.0000
## hu, 2023_LF-RTMS_10-10EEG_RPS_MCCB_1 -0.0000
## hu, 2023_LF-RTMS_10-10EEG_SC_MCCB_1 0.8300
## huang, 2016_HF-RTMS_CM_P_PANSS_1 -0.5200
## huang, 2016_HF-RTMS_CM_N_PANSS_1 0.1400
## huang, 2016_HF-RTMS_CM_G_PANSS_1 0.6200
## huang, 2016_HF-RTMS_CM_T_PANSS_1 3.9100
## huang, 2016_HF-RTMS_CM_RPS_WSCT total errors_1 -1.2900
## jeon, 2018_TDCS_10-20EEG_P_PANSS_1 -1.6200
## jeon, 2018_TDCS_10-20EEG_N_PANSS_1 -0.4600
## jeon, 2018_TDCS_10-20EEG_G_PANSS_1 -2.5200
## jeon, 2018_TDCS_10-20EEG_T_PANSS_1 -6.6000
## jeon, 2018_TDCS_10-20EEG_PS_MCCB_1 -2.7400
## jeon, 2018_TDCS_10-20EEG_AV_MCCB_1 -1.8100
## jeon, 2018_TDCS_10-20EEG_WM_MCCB_1 -1.9400
## jeon, 2018_TDCS_10-20EEG_VerL_MCCB_1 -4.3200
## jeon, 2018_TDCS_10-20EEG_VisL_MCCB_1 -2.0800
## jeon, 2018_TDCS_10-20EEG_RPS_MCCB_1 0.8200
## jeon, 2018_TDCS_10-20EEG_SC_MCCB_1 0.5800
## jeon, 2018_TDCS_10-20EEG_GC_MCCB Composite Score_1 -2.7100
## jeon, 2018_TDCS_10-20EEG_RPS_WCST Perservative Responses_1 3.8600
## jeon, 2018_TDCS_10-20EEG_RPS_WCST Perservative Errors_1 2.8600
## jeon, 2018_TDCS_10-20EEG_RPS_WCST Categoris number_1 0.1800
## jin, 2023_ITBS_NA_SC_FERT_1 0.4400
## jin, 2023_ITBS_NA_SC_HT_1 1.1300
## jin, 2023_ITBS_NA_T_PANSS_1 1.7000
## jin, 2023_ITBS_NA_P_PANSS_1 0.3400
## jin, 2023_ITBS_NA_N_PANSS_1 1.6000
## jin, 2023_ITBS_NA_G_PANSS_1 0.1000
## kang, 2024_CTBS_CM_T_PANSS_1 2.9700
## kang, 2024_CTBS_CM_P_PANSS_1 2.9000
## kang, 2024_CTBS_CM_N_PANSS_1 0.0600
## kang, 2024_CTBS_CM_G_PANSS_1 3.0300
## kang, 2024_CTBS_CM_P_AHRS_1 0.0700
## kantrowitz, 2019_TDCS_10-20EEG_P_AHRS_1 -0.8000
## kimura, 2016_HF-RTMS_10-20EEG_P_AHRS_1 2.1000
## klein, 1999_LF-RTMS_CM_P_PANSS_1 -2.8000
## klein, 1999_LF-RTMS_CM_N_PANSS_1 0.3000
## klein, 1999_LF-RTMS_CM_G_PANSS_1 2.9000
## klein, 1999_LF-RTMS_CM_T_BPRS_1 0.5000
## koops, 2018_TDCS_10-20EEG_P_AHRS_1 0.0000
## koops, 2018_TDCS_10-20EEG_T_PANSS_1 -1.9500
## koops, 2018_TDCS_10-20EEG_P_PANSS_1 -0.6500
## koops, 2018_TDCS_10-20EEG_N_PANSS_1 -0.7000
## koops, 2018_TDCS_10-20EEG_RPS_Stroop Interference_1 9.0000
## koops, 2018_TDCS_10-20EEG_PS_TMT-A_1 10.5700
## koops, 2018_TDCS_10-20EEG_RPS_TMT-B_1 20.1400
## koops, 2016_CTBS_10-20EEG_P_PANSS_1 -0.0000
## koops, 2016_CTBS_10-20EEG_P_AHRS_1 -0.0000
## koops, 2016_CTBS_10-20EEG_P_PSYRATS_1 -19.0000
## kos, 2024_TDCS_10-20EEG_N_SANS_1 -3.8000
## kos, 2024_TDCS_10-20EEG_N_AES_1 0.3000
## kumar, 2020_HF-RTMS_CM_PANSS-N_1 1.7000
## kumar, 2020_HF-RTMS_CM_PANSS-G_1 0.2000
## li, 2024 - a_ITBS_10-20EEG_GC_MCCB_1 3.1800
## li, 2024 - a_ITBS_10-20EEG_WM_MCCB_1 39.4800
## li, 2024 - a_ITBS_10-20EEG_PANSS-P_1 -10.6300
## li, 2024 - a_ITBS_10-20EEG_PANSS-N_1 1.7800
## li, 2024 - a_ITBS_10-20EEG_PANSS-G_1 3.4900
## li-b-lpc, 2024_ITBS_NEURONAV_PS_MCCB_1 -7.8600
## li-b-lpc, 2024_ITBS_NEURONAV_AV_MCCB_1 -5.2100
## li-b-lpc, 2024_ITBS_NEURONAV_WM_MCCB_1 3.4400
## li-b-lpc, 2024_ITBS_NEURONAV_VerL_MCCB_1 -7.7300
## li-b-lpc, 2024_ITBS_NEURONAV_VisL_MCCB_1 -3.9100
## li-b-lpc, 2024_ITBS_NEURONAV_RPS_MCCB_1 2.9800
## li-b-lpc, 2024_ITBS_NEURONAV_SC_MCCB_1 2.0300
## li-b-lpc, 2024_ITBS_NEURONAV_GC_MCCB_1 -4.2100
## li-b-dlpfc, 2024_ITBS_NEURONAV_PS_MCCB_1 -4.1200
## li-b-dlpfc, 2024_ITBS_NEURONAV_AV_MCCB_1 5.3600
## li-b-dlpfc, 2024_ITBS_NEURONAV_WM_MCCB_1 7.0100
## li-b-dlpfc, 2024_ITBS_NEURONAV_VerL_MCCB_1 -1.1600
## li-b-dlpfc, 2024_ITBS_NEURONAV_VisL_MCCB_1 -1.6100
## li-b-dlpfc, 2024_ITBS_NEURONAV_RPS_MCCB_1 0.1800
## li-b-dlpfc, 2024_ITBS_NEURONAV_SC_MCCB_1 -2.2700
## li-b-dlpfc, 2024_ITBS_NEURONAV_GC_MCCB_1 -0.0400
## lindenmayer, 2019_TDCS_10-20EEG_AHRS_1 -2.6100
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-T_1 -5.8700
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-P_1 -0.7800
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-N_1 -0.5500
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-G_1 0.0100
## lindenmayer, 2019_TDCS_10-20EEG_GC_MCCB_1 -1.5200
## lindenmayer, 2019_TDCS_10-20EEG_PS_MCCB_1 1.4800
## lindenmayer, 2019_TDCS_10-20EEG_AV_MCCB_1 -1.2200
## lindenmayer, 2019_TDCS_10-20EEG_WM_MCCB_1 -5.1000
## lindenmayer, 2019_TDCS_10-20EEG_VerL_MCCB_1 -0.0200
## lindenmayer, 2019_TDCS_10-20EEG_VisL_MCCB_1 0.0500
## lindenmayer, 2019_TDCS_10-20EEG_RPN_MCCB_1 -3.7200
## lindenmayer, 2019_TDCS_10-20EEG_SC_MCCB_1 -1.4700
## lisoni, 2022_TDCS_10-20 EEG_PANSS-P_1 -0.4400
## lisoni, 2022_TDCS_10-20 EEG_PANSS-N_1 -5.3200
## lisoni, 2022_TDCS_10-20 EEG_PANSS-T_1 -9.7600
## lisoni, 2022_TDCS_10-20 EEG_PANSS-G_1 -4.0000
## lisoni, 2022_TDCS_10-20 EEG_GC_BACS (Composite z-scores)_1 -0.0100
## lisoni, 2022_TDCS_10-20 EEG_VerL_BACS z-scores (Verbal memory)_1 2.9600
## lisoni, 2022_TDCS_10-20 EEG_WM_BACS z-scores (Digit sequencing)_1 -1.2400
## lisoni, 2022_TDCS_10-20 EEG_PS_BACS z-scores (Verbal fluency)_1 0.5600
## lisoni, 2022_TDCS_10-20 EEG_PS_BACS z-scores (Symbol coding)_1 -2.4000
## lisoni, 2022_TDCS_10-20 EEG_RPS_BACS z-scores (Tower of London)_1 -0.6000
## liu, 2024_HF-RTMS_NA_T_PANSS_1 2.1800
## liu, 2024_HF-RTMS_NA_P_PANSS_1 -0.2100
## liu, 2024_HF-RTMS_NA_N_PANSS_1 1.5000
## liu, 2024_HF-RTMS_NA_G_PANSS_1 0.8800
## liu, 2024_HF-RTMS_NA_VerL_RBANS (Immediate memory)_1 3.6900
## liu, 2024_HF-RTMS_NA_VisL_RBANS (Visual spatial structure)_1 -1.1000
## liu, 2024_HF-RTMS_NA_PS_RBANS (Speech function)_1 3.5800
## liu, 2024_HF-RTMS_NA_WM_RBANS (Attention)_1 0.8700
## liu, 2024_HF-RTMS_NA_Visl_RBANS (Delayed memory)_1 0.6400
## lyu, 2024_TDCS_10-20EEG_T_PANSS_1 3.6000
## lyu, 2024_TDCS_10-20EEG_P_PANSS_1 -0.1300
## lyu, 2024_TDCS_10-20EEG_N_PANSS_1 1.6800
## lyu, 2024_TDCS_10-20EEG_G_PANSS_1 2.0500
## lyu, 2024_TDCS_10-20EEG_N_SANS_1 0.5300
## mao, 2023_HF-RTMS_CM_GC_RBANS_1 5.6200
## mao, 2023_HF-RTMS_CM_VerL_RBANS-Immediate Memory_1 10.5800
## mao, 2023_HF-RTMS_CM_RBANS-Visuospatial_1 5.8000
## mao, 2023_HF-RTMS_CM_VerL_RBANS-Language_1 -1.7000
## mao, 2023_HF-RTMS_CM_WM_RBANS-Attention_1 -1.5200
## mao, 2023_HF-RTMS_CM_VerL_RBANS-Delayed memory_1 -0.3200
## mao, 2023_HF-RTMS_CM_P_AHRS_1 0.2600
## mao, 2023_HF-RTMS_CM_T_PANSS_1 4.8000
## marquardt, 2022_TDCS_10-20EEG_P_PANSS_1 3.8700
## marquardt, 2022_TDCS_10-20EEG_N_PANSS_1 1.7300
## marquardt, 2022_TDCS_10-20EEG_P_AHRS_1 0.2600
## marquardt, 2022_TDCS_10-20EEG_RPS_Stroop 3 (s/RT)_1 -7.1400
## marquardt, 2022_TDCS_10-20EEG_RPS_Stroop 4 (s/RT)_1 6.8400
## marquardt, 2022_TDCS_10-20EEG_PS_TMT-A_1 -3.4600
## marquardt, 2022_TDCS_10-20EEG_RPS_TMT-B_1 10.9900
## mcintosh, 2004_LF-RTMS_10-20EEG_P_PANSS_1 2.1300
## mcintosh, 2004_LF-RTMS_10-20EEG_N_PANSS_1 0.2500
## mcintosh, 2004_LF-RTMS_10-20EEG_VerL_AVLT_1 -2.2500
## meiron, 2021_TDCS_10-20EEG_T_PANSS_1 -10.9670
## meiron, 2021_TDCS_10-20EEG_WM_(verbal) WM - Accuracy_1 -12.7500
## meiron, 2021_TDCS_10-20EEG_WM_(verbal) WM - RT_1 118.3600
## meiron, 2024_TDCS_10-20EEG_T_PANSS_1 -10.1400
## meiron, 2024_TDCS_10-20EEG_WM_2-BACK Acc_1 -11.0800
## meiron, 2024_TDCS_10-20EEG_WM_2-BACK RT_1 46.3700
## mellin-tacs, 2018_TACS_10-20EEG_P_AHRS_1 -1.4700
## mellin-tacs, 2018_TACS_10-20EEG_T_PANSS-T_1 0.2100
## mellin-tacs, 2018_TACS_10-20EEG_P_PANSS-P_1 0.8100
## mellin-tacs, 2018_TACS_10-20EEG_N_PANSS-N_1 -1.0900
## mellin-tacs, 2018_TACS_10-20EEG_G_PANSS-G_1 0.0700
## mellin-tacs, 2018_TACS_10-20EEG_GC_BACS_1 2.2000
## mellin-tdcs, 2018_TDCS_10-20EEG_P_AHRS_1 1.1400
## mellin-tdcs, 2018_TDCS_10-20EEG_T_PANSS_1 -2.4400
## mellin-tdcs, 2018_TDCS_10-20EEG_P_PANSS_1 -0.7400
## mellin-tdcs, 2018_TDCS_10-20EEG_N_PANSS_1 -1.4200
## mellin-tdcs, 2018_TDCS_10-20EEG_G_PANSS_1 -0.1500
## mellin-tdcs, 2018_TDCS_10-20EEG_GC_BACS_1 -1.2200
## moeller, 2022_DTMS_CM_T_PANSS_1 5.3000
## moeller, 2022_DTMS_CM_P_PANSS_1 2.2000
## moeller, 2022_DTMS_CM_N_PANSS_1 4.1000
## mogg, 2007_HF-RTMS_CM_VerL_HVLT immediate recall_1 0.7000
## mogg, 2007_HF-RTMS_CM_VerL_HVLT delayed recall_1 0.4000
## mogg, 2007_HF-RTMS_CM_PS_COWAT (number)_1 1.0000
## mogg, 2007_HF-RTMS_CM_RPS_Stroop RT (seconds)_1 21.2000
## mondino, 2015_TDCS_10-20EG_P_PANSS_1 -0.2000
## mondino, 2015_TDCS_10-20EG_N_PANSS_1 -3.0000
## mondino, 2015_TDCS_10-20EG_G_PANSS_1 -2.3000
## mondino, 2015_TDCS_10-20EG_P_AHRS_1 -5.2000
## novak, 2006_HF-RTMS_CM_T_PANSS_1 -4.3750
## novak, 2006_HF-RTMS_CM_P_PANSS_1 -0.5000
## novak, 2006_HF-RTMS_CM_N_PANSS_1 -0.8750
## novak, 2006_HF-RTMS_CM_G_PANSS_1 -3.0000
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_SAPS_1 -4.7300
## paillere-martinot, 2017_LF-RTMS_NEURONAV_N_SANS_1 -2.6300
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_AHRS_1 -2.9900
## palm, 2016_TDCS_10-20EEG_T_PANSS_1 -2.1000
## palm, 2016_TDCS_10-20EEG_P_PANSS_1 0.1000
## palm, 2016_TDCS_10-20EEG_N_PANSS_1 -1.2000
## palm, 2016_TDCS_10-20EEG_N_SANS_1 -9.7000
## palm, 2016_TDCS_10-20EEG_WM_SOPT_1 1.0000
## palm, 2016_TDCS_10-20EEG_PS_TMT-A_1 3.3000
## palm, 2016_TDCS_10-20EEG_RPS_TMT-B_1 22.5000
## prikryl, 2007_HF-RTMS_CM_T_PANSS_1 4.9100
## prikryl, 2007_HF-RTMS_CM_P_PANSS_1 -0.1900
## prikryl, 2007_HF-RTMS_CM_N_PANSS_1 4.3600
## prikryl, 2007_HF-RTMS_CM_N_SANS_1 24.9900
## prikryl, 2007_HF-RTMS_CM_P_SAPS_1 0.1800
## prikryl, 2012_HF-RTMS_CM_P_PANSS_1 0.5500
## prikryl, 2012_HF-RTMS_CM_N_PANSS_1 6.1700
## prikryl, 2012_HF-RTMS_CM_G_PANSS_1 2.9400
## prikryl, 2012_HF-RTMS_CM_T_PANSS_1 9.6600
## prikryl, 2012_HF-RTMS_CM_PS_VFT_1 0.7300
## prikryl, 2014_HF-RTMS_CM_T_PANSS_1 10.0800
## prikryl, 2014_HF-RTMS_CM_P_PANSS_1 0.4100
## prikryl, 2014_HF-RTMS_CM_N_PANSS_1 5.2300
## prikryl, 2014_HF-RTMS_CM_G_PANSS_1 4.4300
## prikryl, 2013_HF-RTMS_CM_N_SANS_1 23.6000
## prikryl, 2013_HF-RTMS_CM_P_SAPS_1 -0.5700
## quan, 2015_HF-RTMS_CM_T_PANSS_1 4.9200
## quan, 2015_HF-RTMS_CM_P_PANSS_1 0.3100
## quan, 2015_HF-RTMS_CM_N_PANSS_1 1.7800
## quan, 2015_HF-RTMS_CM_G_PANSS_1 2.4300
## quan, 2015_HF-RTMS_CM_N_SANS_1 5.2900
## rabany, 2014_DTMS_CM_T_PANSS_1 3.6000
## rabany, 2014_DTMS_CM_N_PANSS_1 -0.2000
## rabany, 2014_DTMS_CM_N_SANS_1 7.3000
## rabany, 2014_DTMS_CM_AV_RVP-A_1 0.0000
## rabany, 2014_DTMS_CM_AV_RVP-B_1 0.0000
## rabany, 2014_DTMS_CM_WM_SWM (Total between search errors)_1 4.7000
## rabany, 2014_DTMS_CM_WM_SWM (Strategy score)_1 9.8000
## rabany, 2014_DTMS_CM_RPS_SOC (Minimum move solutions for test trials)_1 -1.4000
## rabany, 2014_DTMS_CM_RPS_SOC (Initial times for 5 move problems)_1 5148.0000
## rabany, 2014_DTMS_CM_RPS_SOC (Subsequent times for 5 move problems)_1 1079.7000
## rabany, 2014_DTMS_CM_PS_RTI (Mean reaction time, stages 4 and 5)_1 65.3000
## rabany, 2014_DTMS_CM_PS_RTI (Mean movement time, stages 4 and 5)_1 56.0000
## rollnik, 2000_HF-RTMS_CM_T_BPRS_1 13.6000
## rollnik, 2000_HF-RTMS_CM_PS_NCT (seconds)_1 -19.7000
## rosa, 2007_LF-RTMS_10-20EEG_T_PANSS_1 0.7300
## rosa, 2007_LF-RTMS_10-20EEG_P_PANSS_1 -0.4300
## rosa, 2007_LF-RTMS_10-20EEG_N_PANSS_1 -1.3000
## rosa, 2007_LF-RTMS_10-20EEG_G_PANSS_1 2.4700
## rosenberg, 2012_LF-RTMS_CM_P_AHRS_1 -0.6000
## saba, 2006_LF-RTMS_CM_T_PANSS_1 -7.0800
## saba, 2006_LF-RTMS_CM_P_PANSS_1 -0.3100
## saba, 2006_LF-RTMS_CM_N_PANSS_1 -3.7500
## saba, 2006_LF-RTMS_CM_G_PANSS_1 -4.1300
## schilling, 2021_TDCS_10-20EEG_WM_Verbal Working Memory Reaction Time (t-score)_1 3.0000
## schilling, 2021_TDCS_10-20EEG_WM_Verbal Working Memory d-prime (z-score)_1 -0.1800
## schilling, 2021_TDCS_10-20EEG_RPS_Response Inhibition Reaction Time (t-score)_1 -2.0000
## schilling, 2021_TDCS_10-20EEG_RPS_Response Inhibition Errors (t-scores)_1 -3.1700
## schilling, 2021_TDCS_10-20EEG_RPS_Problem solving t-score_1 2.7200
## schilling, 2021_TDCS_10-20EEG_RPS_Mental Flexibility Speed (t-score)_1 -2.3600
## schilling, 2021_TDCS_10-20EEG_RPS_Mental Flexibility Accuracy (t-score)_1 -0.3200
## singh, 2020_HF-RTMS_CM_P_PANSS_1 -0.3900
## singh, 2020_HF-RTMS_CM_N_PANSS_1 0.7400
## singh, 2020_HF-RTMS_CM_N_SANS_1 5.7900
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_AHRS_1 0.7000
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_PANSS_1 -1.3000
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_AHRS_1 0.0000
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_PANSS_1 -1.9000
## smith, 2015_TDCS_10-20EEG_GC_MCCB_1 -4.3500
## smith, 2015_TDCS_10-20EEG_WM_MCCB_1 -7.6600
## smith, 2015_TDCS_10-20EEG_AV_MCCB_1 -6.1700
## smith, 2015_TDCS_10-20EEG_RPS_MCCB_1 -3.1500
## smith, 2015_TDCS_10-20EEG_VerL_MCCB_1 -1.9300
## smith, 2015_TDCS_10-20EEG_VisL_MCCB_1 -1.8400
## smith, 2015_TDCS_10-20EEG_PS_MCCB_1 2.6000
## smith, 2015_TDCS_10-20EEG_SC_MCCB_1 -5.1100
## smith, 2015_TDCS_10-20EEG_T_PANSS_1 3.7000
## smith, 2015_TDCS_10-20EEG_P_PANSS_1 0.6600
## smith, 2015_TDCS_10-20EEG_N_PANSS_1 2.4000
## smith, 2015_TDCS_10-20EEG_G_PANSS_1 2.2300
## smith, 2020_TDCS_10-20EEG_GC_MCCB_1 1.2300
## smith, 2020_TDCS_10-20EEG_PS_MCCB_1 -1.4700
## smith, 2020_TDCS_10-20EEG_AV_MCCB_1 0.0500
## smith, 2020_TDCS_10-20EEG_WM_MCCB_1 4.0000
## smith, 2020_TDCS_10-20EEG_VerL_MCCB_1 7.0100
## smith, 2020_TDCS_10-20EEG_VisL_MCCB_1 -3.1000
## smith, 2020_TDCS_10-20EEG_RPS_MCCB_1 -0.8700
## smith, 2020_TDCS_10-20EEG_SC_MCCB_1 -1.4800
## smith, 2020_TDCS_10-20EEG_AV_PASAT (Number Correct)_1 0.1600
## smith, 2020_TDCS_10-20EEG_T_PANSS_1 1.0900
## smith, 2020_TDCS_10-20EEG_P_PANSS_1 -0.2500
## smith, 2020_TDCS_10-20EEG_N_PANSS_1 -0.2500
## su, 2023b_HF-RTMS_NEURONAV_T_PANSS_1 0.1000
## su, 2023b_HF-RTMS_NEURONAV_P_PANSS_1 0.3000
## su, 2023b_HF-RTMS_NEURONAV_N_PANSS_1 -0.1000
## su, 2023b_HF-RTMS_NEURONAV_G_PANSS_1 -0.3000
## su, 2022_HF-RTMS_NEURONAV_T_PANSS_1 0.2000
## su, 2022_HF-RTMS_NEURONAV_P_PANSS_1 0.4000
## su, 2022_HF-RTMS_NEURONAV_N_PANSS_1 -0.1000
## su, 2022_HF-RTMS_NEURONAV_G_PANSS_1 -0.1000
## tikka, 2017_CTBS_NEURONAV_P_PANSS_1 0.8500
## tikka, 2017_CTBS_NEURONAV_N_PANSS_1 1.0200
## tikka, 2017_CTBS_NEURONAV_G_PANSS_1 -2.0900
## tikka, 2017_CTBS_NEURONAV_T_PANSS_1 -0.2100
## tikka, 2017_CTBS_NEURONAV_RPS_Self-Monitoring Task_1 -0.1500
## tikka, 2017_CTBS_NEURONAV_WM_Visual Memory Task_1 -0.4400
## tyagi, 2022_CTBS_10-20EEG_P_PANSS_1 1.1800
## tyagi, 2022_CTBS_10-20EEG_N_PANSS_1 0.3200
## tyagi, 2022_CTBS_10-20EEG_T_PANSS_1 2.1100
## tyagi, 2022_CTBS_10-20EEG_G_PANSS_1 0.7200
## tyagi, 2022_CTBS_10-20EEG_P_AVHRS_1 -1.7200
## tyagi, 2022_CTBS_10-20EEG_P_PSYRAT-AH_1 -1.4700
## valiengo, 2020_TDCS_10-20EEG_N_PANSS_1 -0.7400
## valiengo, 2020_TDCS_10-20EEG_P_PANSS_1 -0.0400
## valiengo, 2020_TDCS_10-20EEG_T_PANSS_1 -2.2800
## valiengo, 2020_TDCS_10-20EEG_G_PANSS_1 -1.6000
## valiengo, 2020_TDCS_10-20EEG_P_AVHRS_1 0.8400
## vercammen, 2011_TDCS_10-20EEG_RPS_Weather Prediction Test_1 -1.0350
## vergallito, 2024_ITBS_10-20EEG_T_PANSS_1 18.8100
## vergallito, 2024_ITBS_10-20EEG_P_PANSS_1 0.8600
## vergallito, 2024_ITBS_10-20EEG_N_PANSS_1 -0.7100
## vergallito, 2024_ITBS_10-20EEG_N_BNSS_1 -15.1400
## vergallito, 2024_ITBS_10-20EEG_GC_MCCB_1 1.5700
## vergallito, 2024_ITBS_10-20EEG_PS_MCCB_1 3.0000
## vergallito, 2024_ITBS_10-20EEG_AV_MCCB_1 -2.3800
## vergallito, 2024_ITBS_10-20EEG_WM_MCCB_1 -0.6200
## vergallito, 2024_ITBS_10-20EEG_VerL_MCCB_1 -2.1400
## vergallito, 2024_ITBS_10-20EEG_VisL_MCCB_1 1.9000
## vergallito, 2024_ITBS_10-20EEG_RPS_MCCB_1 6.7600
## vergallito, 2024_ITBS_10-20EEG_SC_MCCB_1 -1.9000
## walther-lft, 2024_UNKNOWN_STANDARD_T_PANSS_1 -2.4000
## walther-lft, 2024_UNKNOWN_STANDARD_P_PANSS_1 -1.5000
## walther-lft, 2024_UNKNOWN_STANDARD_N_PANSS_1 0.5000
## walther-lft, 2024_UNKNOWN_STANDARD_G_PANSS_1 -1.3000
## walther-lft, 2024_UNKNOWN_STANDARD_N_BNSS_1 -1.7000
## walther-itbs, 2024_ITBS_CM_T_PANSS_1 5.1000
## walther-itbs, 2024_ITBS_CM_P_PANSS_1 1.7000
## walther-itbs, 2024_ITBS_CM_N_PANSS_1 0.5000
## walther-itbs, 2024_ITBS_CM_G_PANSS_1 2.7000
## walther-itbs, 2024_ITBS_CM_N_BNSS_1 -0.5000
## wang, 2020_ITBS_NEURONAV_T_PANSS_1 11.6900
## wang, 2020_ITBS_NEURONAV_P_PANSS_1 1.3200
## wang, 2020_ITBS_NEURONAV_N_PANSS_1 2.4400
## wang, 2020_ITBS_NEURONAV_G_PANSS_1 3.1200
## wang, 2020_ITBS_NEURONAV_P_SAPS_1 5.7200
## wang, 2020_ITBS_NEURONAV_N_SANS_1 10.1600
## wang, 2020_ITBS_NEURONAV_GC_MoCA_1 0.2200
## wang, 2020_ITBS_NEURONAV_PS_VFT_1 -1.4200
## wang, 2020_ITBS_NEURONAV_WM_Digit span (forward)_1 -0.2100
## wang, 2020_ITBS_NEURONAV_WM_Digit span (backward)_1 0.0600
## wang, 2020_ITBS_NEURONAV_RPS_Stroop Color Test_1 -0.9900
## wang, 2020_ITBS_NEURONAV_RPS_Stroop Word Test_1 -0.0300
## wang, 2020_ITBS_NEURONAV_RPS_Stroop Interference Test_1 -2.8200
## wang, 2020_ITBS_NEURONAV_PS_TMT-A_1 7.0000
## wang, 2020_ITBS_NEURONAV_RPS_TMT-B_1 2.5900
## wang, 2022_ITBS_NEURONAV_P_PANSS_1 3.5520
## wang, 2022_ITBS_NEURONAV_N_PANSS_1 4.3400
## wang, 2022_ITBS_NEURONAV_G_PANSS_1 4.9550
## wang, 2022_ITBS_NEURONAV_T_PANSS_1 13.7010
## wang, 2022_ITBS_NEURONAV_P_SAPS_1 8.4730
## wang, 2022_ITBS_NEURONAV_N_SANS_1 11.5610
## wang, 2022_ITBS_NEURONAV_GC_MoCA_1 0.1590
## wang, 2022_ITBS_NEURONAV_WM_3-back RT_1 20.2270
## weickert, 2019_TDCS_10-20EEG_T_PANSS_1 1.6000
## weickert, 2019_TDCS_10-20EEG_P_PANSS_1 -0.3000
## weickert, 2019_TDCS_10-20EEG_N_PANSS_1 1.7000
## weickert, 2019_TDCS_10-20EEG_G_PANSS_1 0.3000
## weickert, 2019_TDCS_10-20EEG_P_AHRS_1 5.0000
## weickert, 2019_TDCS_10-20EEG_PS_BACS sc_1 -2.2000
## weickert, 2019_TDCS_10-20EEG_PS_TMT-A_1 2.4000
## weickert, 2019_TDCS_10-20EEG_WM_LNS_1 0.3000
## weickert, 2019_TDCS_10-20EEG_VerL_HVLTr_1 1.9000
## weickert, 2019_TDCS_10-20EEG_VisL_BVMT_1 6.0000
## weickert, 2019_TDCS_10-20EEG_RPS_NAB maze_1 5.2000
## weickert, 2019_TDCS_10-20EEG_PS_fluency_1 -3.9000
## wen, 2021_HF-RTMS_CM_T_PANSS_1 -4.2000
## wen, 2021_HF-RTMS_CM_P_PANSS_1 0.6000
## wen, 2021_HF-RTMS_CM_N_PANSS_1 -1.1000
## wen, 2021_HF-RTMS_CM_G_PANSS_1 -1.3000
## wen, 2021_HF-RTMS_CM_GC_RBANS-T_1 8.1000
## wen, 2021_HF-RTMS_CM_VerL_RBANS\r\nImmediate memory_1 10.6000
## wen, 2021_HF-RTMS_CM_WM_RBANS\r\nAttention_1 8.6000
## wen, 2021_HF-RTMS_CM_VisL_RBANS\r\nVisuospatial_1 -0.9000
## wen, 2021_HF-RTMS_CM_VisL_RBANS\r\nDelayed memory_1 15.3000
## wen, 2021_HF-RTMS_CM_VerL_RBANS\r\nLanguage_1 7.1000
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n1 word (s)_1 -0.1000
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n2 word (s)_1 -10.1000
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n3 word (s)_1 -0.9000
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n3 color (s)_1 -3.3000
## wobrock, 2015_HF-RTMS_10-20EEG_T_PANSS_1 2.1000
## wobrock, 2015_HF-RTMS_10-20EEG_P_PANSS_1 1.3000
## wobrock, 2015_HF-RTMS_10-20EEG_N_PANSS_1 0.5000
## xie, 2023-a_LF-RTMS_10-20EEG_T_PANSS_1 11.9800
## xie, 2023-a_LF-RTMS_10-20EEG_P_PANSS_1 6.6600
## xie, 2023-a_LF-RTMS_10-20EEG_N_PANSS_1 1.0000
## xie, 2023-a_LF-RTMS_10-20EEG_G_PANSS_1 6.2700
## xie, 2023-a_LF-RTMS_10-20EEG_P_AHRS_1 13.5000
## xiu-10hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 -8.1000
## xiu-10hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 0.6000
## xiu-10hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 3.4000
## xiu-10hz, 2020_HF-RTMS_NEURONAV_G_PANSS_1 1.8000
## xiu-10hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 0.1000
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nImmediate memory_1 2.4000
## xiu-10hz, 2020_HF-RTMS_NEURONAV_WM_RBANS\r\nAttention_1 -8.0000
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nVisuospatial_1 1.2000
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nDelayed memory_1 5.5000
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nLanguage_1 -3.9000
## xiu-20hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 2.2000
## xiu-20hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 1.7000
## xiu-20hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 0.4000
## xiu-20hz, 2020_HF-RTMS_NEURONAV_G_PANSS_1 4.3000
## xiu-20hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 4.5000
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nImmediate memory_1 9.8000
## xiu-20hz, 2020_HF-RTMS_NEURONAV_WM_RBANS\r\nAttention_1 -2.0000
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nVisuospatial_1 0.9000
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nDelayed memory_1 11.0000
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nLanguage_1 -5.2000
## xu, 2023_HD-TDCS_10-20EEG_T_PANSS_1 4.6400
## xu, 2023_HD-TDCS_10-20EEG_P_PANSS_1 1.2800
## xu, 2023_HD-TDCS_10-20EEG_N_PANSS_1 0.3200
## xu, 2023_HD-TDCS_10-20EEG_G_PANSS_1 2.2700
## xu, 2023_HD-TDCS_10-20EEG_GC_RBANS_1 0.4100
## ye-20hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 1.7000
## ye-20hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Immediate memory_1 9.2000
## ye-20hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Visuospatial_1 0.5000
## ye-20hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Language_1 -4.8000
## ye-20hz, 2024_HF-RTMS_NEURONAV_WM_RBANS - Attention_1 -0.7000
## ye-20hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Delayed memory_1 2.2000
## ye-10hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 1.0000
## ye-10hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Immediate memory_1 4.2000
## ye-10hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Visuospatial_1 0.9000
## ye-10hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Language_1 -2.6000
## ye-10hz, 2024_HF-RTMS_NEURONAV_WM_RBANS - Attention_1 0.0000
## ye-10hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Delayed memory_1 -12.7000
## yuanjun, 2024_LF-RTMS_10-20EEG_T_PANSS_1 12.0700
## yuanjun, 2024_LF-RTMS_10-20EEG_P_PANSS_1 6.2200
## yuanjun, 2024_LF-RTMS_10-20EEG_N_PANSS_1 1.3700
## yuanjun, 2024_LF-RTMS_10-20EEG_G_PANSS_1 5.9500
## yuanjun, 2024_LF-RTMS_10-20EEG_P_AHRS_1 14.7000
## zhai-a, 2023_HF-RTMS_NA_T_PANSS_1 -1.6000
## zhang, 2022_TACS_10-20EEG_T_PANSS_1 -3.2300
## zhang, 2022_TACS_10-20EEG_P_PANSS_1 -0.2800
## zhang, 2022_TACS_10-20EEG_N_PANSS_1 -0.0900
## zhang, 2022_TACS_10-20EEG_P_AHRS_1 0.6000
## zhao-tbs, 2014_ITBS_10-20EEG_T_PANSS_1 15.3000
## zhao-tbs, 2014_ITBS_10-20EEG_P_PANSS_1 -3.8000
## zhao-tbs, 2014_ITBS_10-20EEG_N_PANSS_1 15.8000
## zhao-tbs, 2014_ITBS_10-20EEG_G_PANSS_1 3.8000
## zhao-tbs, 2014_ITBS_10-20EEG_N_SANS_1 19.7000
## zhao-20hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 11.4000
## zhao-20hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 0.7000
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 10.3000
## zhao-20hz, 2014_HF-RTMS_10-20EEG_G_PANSS_1 0.6000
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 14.8000
## zhao-10hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 12.4000
## zhao-10hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 -0.2000
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 7.2000
## zhao-10hz, 2014_HF-RTMS_10-20EEG_G_PANSS_1 4.9000
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 10.8000
## zhou, 2024_HF-RTMS_10-20EEG_P_PANSS_1 0.5000
## zhou, 2024_HF-RTMS_10-20EEG_N_PANSS_1 4.5000
## zhou, 2024_HF-RTMS_10-20EEG_T_PANSS_1 11.3000
## zhou, 2024_HF-RTMS_10-20EEG_G_PANSS_1 6.6000
## zhou, 2024_HF-RTMS_10-20EEG_GC_RBANS-T_1 7.6000
## zhou, 2024_HF-RTMS_10-20EEG_VerL_RBANS\r\nImmediate memory_1 6.1000
## zhou, 2024_HF-RTMS_10-20EEG_VisL_RBANS\r\nVisuospatial_1 3.5000
## zhou, 2024_HF-RTMS_10-20EEG_VerL_RBANS\r\nLanguage_1 8.0000
## zhou, 2024_HF-RTMS_10-20EEG_WM_RBANS\r\nAttention_1 10.0000
## zhou, 2024_HF-RTMS_10-20EEG_VisL_RBANS\r\nDelayed memory_1 3.9000
## zhou, 2024_HF-RTMS_10-20EEG_RPS_SCWT \r\nInference scores_1 -35.5000
## zhou, 2023_TDCS_10-20EEG_T_PANSS_1 4.1900
## zhou, 2023_TDCS_10-20EEG_N_SANS_1 -0.4600
## zhou, 2023_TDCS_10-20EEG_RPS_IED total errors_1 -12.0000
## zhu, 2021_ITBS_CM_N_PANSS_1 1.6600
## zhuo, 2019_HF-RTMS_10-20EEG_T_PANSS_1 3.4900
## zhuo, 2019_HF-RTMS_10-20EEG_P_PANSS_1 -0.0400
## zhuo, 2019_HF-RTMS_10-20EEG_N_PANSS_1 1.7200
## zhuo, 2019_HF-RTMS_10-20EEG_G_PANSS_1 1.8300
## zhuo, 2019_HF-RTMS_10-20EEG_N_SANS_1 4.8500
## zhuo, 2019_HF-RTMS_10-20EEG_PS_MCCB TMT-A_1 -2.4500
## zhuo, 2019_HF-RTMS_10-20EEG_PS_MCCB BACS_1 -3.2000
## zhuo, 2019_HF-RTMS_10-20EEG_PS_MCCB Fluency_1 -0.0000
## zhuo, 2019_HF-RTMS_10-20EEG_WM_MCCB Working memory (WMS-SS)_1 -1.4800
## zhuo, 2019_HF-RTMS_10-20EEG_VerL_MCCB Verbal learning (HVLT-R)_1 -1.9200
## zhuo, 2019_HF-RTMS_10-20EEG_VisL_MCCB Visual learning (BVMT-R)_1 0.6100
## zhuo, 2019_HF-RTMS_10-20EEG_RPS_MCCB Reasoning/problem solving (NAB)_1 -2.0200
## zhuo, 2019_HF-RTMS_10-20EEG_SC_MCCB Social cognition (MSCEIT)_1 -4.5400
## zhuo, 2019_HF-RTMS_10-20EEG_GC_MCCB Composite score_1 -2.5300
## seTE
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANSS_1 1.3255
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANSS_1 1.3607
## bais, 2014 - l_LF-RTMS_10-20EEG_G_PANSS_1 2.4242
## bais, 2014 - l_LF-RTMS_10-20EEG_P_AHRS_1 2.0973
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANAS_1 2.5683
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANAS_1 2.8163
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANSS_1 1.1614
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANSS_1 1.4143
## bais, 2014 - bi_LF-RTMS_10-20EEG_G_PANSS_1 2.0798
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_AHRS_1 2.2660
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANAS_1 2.3828
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANAS_1 3.1294
## barr, 2011_HF-RTMS_NEURONAV_WM_1-back RT ms_1 75.4189
## barr, 2011_HF-RTMS_NEURONAV_WM_2-back RT ms_1 108.7401
## barr, 2011_HF-RTMS_NEURONAV_WM_3-back RT ms_1 87.3820
## barr, 2013_HF-RTMS_NEURONAV_WM_1-back RT ms Target Correct_1 80.7983
## barr, 2013_HF-RTMS_NEURONAV_WM_1-back RT ms Non Target Correct_1 71.4112
## barr, 2013_HF-RTMS_NEURONAV_WM_3-back RT ms Target Correct_1 97.7274
## barr, 2013_HF-RTMS_NEURONAV_WM_3-back RT ms Non Target Correct_1 95.7702
## barr, 2012_HF-RTMS_NEURONAV_P_PANSS_1 1.6327
## barr, 2012_HF-RTMS_NEURONAV_N_PANSS_1 2.2399
## barr, 2012_HF-RTMS_NEURONAV_N_SANS_1 4.2609
## basavaraju, 2021_ITBS_NEURONAV_N_SANS_1 2.6652
## basavaraju, 2021_ITBS_NEURONAV_P_SAPS_1 1.4690
## basavaraju, 2021_ITBS_NEURONAV_VerL_AVLT Hits_1 0.7284
## basavaraju, 2021_ITBS_NEURONAV_VisL_CFT copying_1 1.2737
## basavaraju, 2021_ITBS_NEURONAV_VisL_CFT Immediate Recall_1 1.8320
## basavaraju, 2021_ITBS_NEURONAV_VisL_CFT Delayed Recall_1 1.7876
## basavaraju, 2021_ITBS_NEURONAV_PS_DSST time (sec)_1 46.5630
## basavaraju, 2021_ITBS_NEURONAV_PS_DSST errors_1 0.4008
## basavaraju, 2021_ITBS_NEURONAV_AV_DVT time (sec)_1 66.7226
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-A time (sec)_1 19.5874
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-A errors_1 0.1621
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-B time (sec)_1 42.4899
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-B errors_1 0.4817
## basavaraju, 2021_ITBS_NEURONAV_WM_1back verbal Hits_1 0.4753
## basavaraju, 2021_ITBS_NEURONAV_WM_1back verbal Errors_1 0.5608
## basavaraju, 2021_ITBS_NEURONAV_WM_2back verbal Hits_1 0.4953
## basavaraju, 2021_ITBS_NEURONAV_WM_2back verbal Errors_1 0.7173
## basavaraju, 2021_ITBS_NEURONAV_WM_Spatial Span total_1 0.7745
## basavaraju, 2021_ITBS_NEURONAV_RPS_FAS_1 1.7150
## basavaraju, 2021_ITBS_NEURONAV_RPS_Stroop Effect score_1 25.9578
## basavaraju, 2021_ITBS_NEURONAV_SC_FOT index_1 0.0498
## basavaraju, 2021_ITBS_NEURONAV_SC_SOT index_1 0.0554
## basavaraju, 2021_ITBS_NEURONAV_SC_Faux Pax CI_1 0.0399
## basavaraju, 2021_ITBS_NEURONAV_SC_Personalizing Bias Index_1 0.0835
## basavaraju, 2021_ITBS_NEURONAV_SC_Social Perception Index_1 0.0247
## basavaraju, 2021_ITBS_NEURONAV_SC_Emotion Recognition Index_1 0.0329
## battion, 2021_ITBS_CM_T_PANSS_1 4.6224
## battion, 2021_ITBS_CM_N_SANS_1 6.1623
## blumberger, 2012_LF-RTMS_NEURONAV_P_PSYRATS_1 1.8025
## blumberger, 2012_LF-RTMS_NEURONAV_T_PANSS_1 4.3848
## blumberger, 2012_LF-RTMS_NEURONAV_P_PANSS_1 1.1321
## blumberger, 2012_LF-RTMS_NEURONAV_P_AHRS_1 2.1992
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PSYRATS_1 1.7663
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_T_PANSS_1 4.7186
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PANSS_1 1.1092
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_AHRS_1 2.2547
## bodén, 2021_ITBS_CM_N_CAIN_1 3.7960
## bose, 2018_TDCS_10-20EEG_P_SAPS_1 4.0637
## bose, 2018_TDCS_10-20EEG_N_SANS_1 5.2239
## bose, 2018_TDCS_10-20EEG_P_AHRS_1 1.2546
## brunelin, 2012_TDCS_10-20EEG_P_AHRS_1 1.8797
## brunelin, 2012_TDCS_10-20EEG_T_PANSS_1 4.2712
## brunelin, 2006_LF-RTMS_10-20EEG_P_AHRS_1 2.8113
## brunelin, 2006_LF-RTMS_10-20EEG_P_SAPS_1 7.6631
## brunelin, 2006_LF-RTMS_10-20EEG_WM_MonitorSourceTask_1 0.5610
## bulubas, 2021_TDCS_10-20EEG_VisL_PFMT Total Correct Responses_1 0.8127
## bulubas, 2021_TDCS_10-20EEG_VerL_PWMT Total Correct Responses_1 0.8291
## bulubas, 2021_TDCS_10-20EEG_SC_EMI Correct Responses_1 0.9001
## bulubas, 2021_TDCS_10-20EEG_WM_PLNB 0-back True Positive Responses_1 0.2052
## bulubas, 2021_TDCS_10-20EEG_WM_PLNB 1-back True Positive Responses_1 0.3105
## bulubas, 2021_TDCS_10-20EEG_WM_PLNB 2-back True Positive Responses_1 0.3542
## bulubas, 2021_TDCS_10-20EEG_RPS_PCET Number Correct Responses_1 2.5512
## bulubas, 2021_TDCS_10-20EEG_VisL_Short VOLT Total Correct_1 0.4235
## chang-a, 2021_TACS_10-20EEG_T_PANSS_1 2.3647
## chang-a, 2021_TACS_10-20EEG_N_PANSS_1 1.0428
## chang-a, 2021_TACS_10-20EEG_N_SANS_1 3.0199
## chauhan, 2021_ITBS_10-20EEG_P_PANSS_1 0.6438
## chauhan, 2021_ITBS_10-20EEG_N_PANSS_1 0.9270
## chauhan, 2021_ITBS_10-20EEG_G_PANSS_1 1.5532
## chauhan, 2021_ITBS_10-20EEG_T_PANSS_1 2.2750
## chauhan, 2021_ITBS_10-20EEG_T_BPRS_1 1.5994
## de jesus, 2011_LF-RTMS_10-20EEG_T_BPRS_1 2.9621
## de jesus, 2011_LF-RTMS_10-20EEG_P_BPRS_1 1.3133
## de jesus, 2011_LF-RTMS_10-20EEG_N_BPRS_1 0.9318
## de jesus, 2011_LF-RTMS_10-20EEG_P_AHRS_1 2.4688
## dharani, 2021_HD-TDCS_10-10EEG_P_PANSS_1 0.7670
## dharani, 2021_HD-TDCS_10-10EEG_N_PANSS_1 2.5493
## dharani, 2021_HD-TDCS_10-10EEG_G_PANSS_1 1.4817
## dharani, 2021_HD-TDCS_10-10EEG_N_SANS_1 7.3548
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_SANS_1 4.9744
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_P_PANSS_1 1.3667
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_PANSS_1 1.2209
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_G_PANSS_1 1.7913
## dolfus, 2018_HF-RTMS_NEURONAV_P_AHRS_1 1.3188
## du, 2024_HF-RTMS_NEURONAV_T_BPRS_1 3.5496
## du, 2024_HF-RTMS_NEURONAV_P_BPRS_1 1.7912
## du, 2024_HF-RTMS_NEURONAV_N_BPRS_1 1.6458
## du, 2022_HF-RTMS_10-20EEG_VisL_PRM number correct_1 0.9779
## du, 2022_HF-RTMS_10-20EEG_N_SANS_1 4.5982
## du, 2022_HF-RTMS_10-20EEG_T_PANSS_1 3.7481
## du, 2022_HF-RTMS_10-20EEG_P_PANSS_1 0.9283
## du, 2022_HF-RTMS_10-20EEG_N_PANSS_1 1.8788
## du, 2022_HF-RTMS_10-20EEG_G_PANSS_1 1.4790
## farhang, 2024_TDCS_10-20EEG_WM_ letter-number sequencing_1 0.5070
## fitzerald, 2008_LF-RTMS_CM_N_SANS_1 3.6051
## fitzerald, 2008_LF-RTMS_CM_P_PANSS_1 1.8085
## fitzerald, 2008_LF-RTMS_CM_N_PANSS_1 1.6912
## fitzerald, 2008_LF-RTMS_CM_T_PANSS_1 3.8621
## fitzerald-l, 2014_TDCS_10-20EEG_P_PANSS_1 1.2507
## fitzerald-l, 2014_TDCS_10-20EEG_N_PANSS_1 1.4456
## fitzerald-l, 2014_TDCS_10-20EEG_T_PANSS_1 4.0027
## fitzerald-l, 2014_TDCS_10-20EEG_N_SANS_1 3.3060
## fitzerald-bi, 2014_TDCS_10-20EEG_P_PANSS_1 1.4911
## fitzerald-bi, 2014_TDCS_10-20EEG_N_PANSS_1 1.6702
## fitzerald-bi, 2014_TDCS_10-20EEG_T_PANSS_1 5.9961
## fitzerald-bi, 2014_TDCS_10-20EEG_N_SANS_1 5.1356
## francis, 2019_HF-RTMS_CM_VerL_BACS Verbal Memory_1 4.0872
## francis, 2019_HF-RTMS_CM_WM_BACS Digit Sequencing_1 3.9944
## francis, 2019_HF-RTMS_CM_PS_BACS Semantic and Letter Fluency_1 4.1688
## francis, 2019_HF-RTMS_CM_PS_BACS Symbol Coding_1 3.0905
## francis, 2019_HF-RTMS_CM_RPS_BACS Tower of London_1 6.1803
## francis, 2019_HF-RTMS_CM_GC_BACS Composite Score_1 4.0745
## frohlich, 2016_TDCS_10-20EEG_P_AHRS_1 2.7155
## frohlich, 2016_TDCS_10-20EEG_T_PANSS_1 4.5348
## frohlich, 2016_TDCS_10-20EEG_P_PANSS_1 1.6340
## frohlich, 2016_TDCS_10-20EEG_N_PANSS_1 2.0833
## frohlich, 2016_TDCS_10-20EEG_G_PANSS_1 2.1318
## gao, 2024_ITBS_10-20EEG_P_PANSS_1 0.2932
## gao, 2024_ITBS_10-20EEG_N_PANSS_1 0.5119
## gao, 2024_ITBS_10-20EEG_G_PANSS_1 0.4087
## gao, 2024_ITBS_10-20EEG_T_PANSS_1 0.7065
## gao, 2024_ITBS_10-20EEG_N_SANS_1 0.8153
## garcía-fernández, 2024_TDCS_10-20EEG_PS_MCCB_1 1.1703
## garcía-fernández, 2024_TDCS_10-20EEG_AV_MCCB_1 1.5414
## garcía-fernández, 2024_TDCS_10-20EEG_WM_MCCB_1 1.5468
## garcía-fernández, 2024_TDCS_10-20EEG_VerL_MCCB_1 1.6114
## garcía-fernández, 2024_TDCS_10-20EEG_VisL_MCCB_1 1.5510
## garcía-fernández, 2024_TDCS_10-20EEG_RPS_MCCB_1 1.4909
## garcía-fernández, 2024_TDCS_10-20EEG_SC_MCCB_1 1.7048
## garg, 2016_DTMS_CM_P_PANSS_1 1.4551
## garg, 2016_DTMS_CM_N_PANSS_1 2.0568
## garg, 2016_DTMS_CM_G_PANSS_1 2.2696
## garg, 2016_DTMS_CM_T_PANSS_1 4.2505
## gogler, 2017_TDCS_10-20EEG_PS_C_1 10.5187
## gogler, 2017_TDCS_10-20EEG_WM_K_1 0.2331
## gogler, 2017_TDCS_10-20EEG_AV_α_1 0.0627
## gomes, 2018_TDCS_10-20EEG_WM_MCCB_1 2.2674
## gomes, 2018_TDCS_10-20EEG_PS_MCCB_1 3.0671
## gomes, 2018_TDCS_10-20EEG_AV_MCCB_1 4.1078
## gomes, 2018_TDCS_10-20EEG_VerL_MCCB_1 4.3108
## gomes, 2018_TDCS_10-20EEG_VisL_MCCB_1 4.4957
## gomes, 2018_TDCS_10-20EEG_RPS_MCCB_1 2.3106
## gomes, 2018_TDCS_10-20EEG_P_PANSS_1 1.1160
## gomes, 2018_TDCS_10-20EEG_N_PANSS-N_1 2.1458
## gomes, 2018_TDCS_10-20EEG_G_PANSS_1 2.8832
## gomes, 2018_TDCS_10-20EEG_T_PANSS-T_1 5.5694
## guan, 2020_HF-RTMS_NEURONAV_T_PANSS-T_1 4.3134
## guan, 2020_HF-RTMS_NEURONAV_P_PANSS_1 0.9430
## guan, 2020_HF-RTMS_NEURONAV_N_PANSS-N_1 1.9514
## guan, 2020_HF-RTMS_NEURONAV_G_PANSS_1 2.1716
## guan, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nImmediate memory_1 4.9241
## guan, 2020_HF-RTMS_NEURONAV_WM_RBANS\r\nAttention_1 3.6204
## guan, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nVisuospatial/constructional_1 3.9573
## guan, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nDelayed memory_1 4.8573
## guan, 2020_HF-RTMS_NEURONAV_PS_RBANS\r\nLanguage_1 3.7152
## guan, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 3.4926
## guleken, 2020_HF-RTMS_CM_P_PANSS_1 2.9696
## guleken, 2020_HF-RTMS_CM_N_SANS_1 4.5186
## guleken, 2020_HF-RTMS_CM_RPS_WSCT total correct responses_1 6.1940
## guleken, 2020_HF-RTMS_CM_RPS_WSCT perseverative errors_1 5.3993
## guleken, 2020_HF-RTMS_CM_WM_DST forward_1 0.3249
## guleken, 2020_HF-RTMS_CM_WM_DST backwards_1 0.2606
## guleken, 2020_HF-RTMS_CM_RPS_Total time_1 11.6805
## guleken, 2020_HF-RTMS_CM_RPS_Total errors_1 1.8087
## guleken, 2020_HF-RTMS_CM_RPS_Stroop Interference_1 6.9339
## guse, 2013_HF-RTMS_10-20EEG_PS_TMT-A_1 2.5455
## guse, 2013_HF-RTMS_10-20EEG_RPS_TMT-B_1 6.1337
## guse, 2013_HF-RTMS_10-20EEG_RPS_WCST Accuracy_1 0.0310
## guse, 2013_HF-RTMS_10-20EEG_RPS_WCST RT_1 166.9516
## guse, 2013_HF-RTMS_10-20EEG_AV_Sel. Attention Accuracy_1 0.0319
## guse, 2013_HF-RTMS_10-20EEG_AV_Sel. Attention RT_1 18.5227
## guse, 2013_HF-RTMS_10-20EEG_AV_Div. Attention Accuracy_1 0.0479
## guse, 2013_HF-RTMS_10-20EEG_AV_Div. Attention RT_1 31.3059
## guse, 2013_HF-RTMS_10-20EEG_WM_0-back Accuracy_1 1.6901
## guse, 2013_HF-RTMS_10-20EEG_WM_0-back RT_1 40.4068
## guse, 2013_HF-RTMS_10-20EEG_WM_1-back Accuracy_1 2.6611
## guse, 2013_HF-RTMS_10-20EEG_WM_1-back RT_1 42.5158
## guse, 2013_HF-RTMS_10-20EEG_WM_2-back Accuracy_1 2.6173
## guse, 2013_HF-RTMS_10-20EEG_WM_2-back RT_1 54.0343
## hasan, 2016_HF-RTMS_10-20EEG_WM_DST z score_1 0.1603
## hasan, 2016_HF-RTMS_10-20EEG_WM_DST Forward_1 0.3265
## hasan, 2016_HF-RTMS_10-20EEG_WM_DST Backward_1 0.3130
## hasan, 2016_HF-RTMS_10-20EEG_PS_TMT-A time (s)_1 3.1493
## hasan, 2016_HF-RTMS_10-20EEG_RPS_TMT-B time (s)_1 7.9832
## hasan, 2016_HF-RTMS_10-20EEG_VerL_VLMT z score_1 0.1575
## hasan, 2016_HF-RTMS_10-20EEG_RPS_WCST z score_1 0.1863
## hasan, 2016_HF-RTMS_10-20EEG_RPS_WCST total correct score_1 1.3127
## hasan, 2016_HF-RTMS_10-20EEG_RPS_WCST total errors_1 1.2647
## hasan, 2016_HF-RTMS_10-20EEG_PS_RWT z score_1 1.1940
## holi, 2004_HF-RTMS_10-20EEG_T_PANSS_1 10.4397
## holi, 2004_HF-RTMS_10-20EEG_P_PANSS_1 2.8458
## holi, 2004_HF-RTMS_10-20EEG_N_PANSS_1 3.1039
## holi, 2004_HF-RTMS_10-20EEG_G_PANSS_1 5.7727
## hu, 2024_LF-RTMS_10-20EEG_T_PANSS_1 2.1748
## hu, 2024_LF-RTMS_10-20EEG_P_PANSS_1 0.7220
## hu, 2024_LF-RTMS_10-20EEG_N_PANSS_1 0.9296
## hu, 2024_LF-RTMS_10-20EEG_G_PANSS_1 0.9927
## hu, 2024_LF-RTMS_10-20EEG_PS_TMT-A_1 5.6658
## hu, 2024_LF-RTMS_10-20EEG_PS_BACS Symbol Coding_1 1.8463
## hu, 2024_LF-RTMS_10-20EEG_PS_Category Fluency_1 0.8984
## hu, 2024_LF-RTMS_10-20EEG_AV_CPT-IP_1 0.1374
## hu, 2024_LF-RTMS_10-20EEG_WM_WMS-3 spatial span_1 0.6494
## hu, 2024_LF-RTMS_10-20EEG_VerL_HVLT-R_1 1.0099
## hu, 2024_LF-RTMS_10-20EEG_VisL_BVMT-R_1 1.3216
## hu, 2024_LF-RTMS_10-20EEG_RPS_NAB_1 1.0986
## hu, 2023_LF-RTMS_10-10EEG_T_PANSS_1 2.1014
## hu, 2023_LF-RTMS_10-10EEG_P_PANSS_1 0.7056
## hu, 2023_LF-RTMS_10-10EEG_N_PANSS_1 0.9509
## hu, 2023_LF-RTMS_10-10EEG_G_PANSS_1 0.9478
## hu, 2023_LF-RTMS_10-10EEG_GC_MCCB-T_1 1.3586
## hu, 2023_LF-RTMS_10-10EEG_PS_MCCB_1 1.7635
## hu, 2023_LF-RTMS_10-10EEG_AV_MCCB_1 2.2458
## hu, 2023_LF-RTMS_10-10EEG_WM_MCCB_1 2.2771
## hu, 2023_LF-RTMS_10-10EEG_VerL_MCCB_1 1.7254
## hu, 2023_LF-RTMS_10-10EEG_VisL_MCCB_1 1.7587
## hu, 2023_LF-RTMS_10-10EEG_RPS_MCCB_1 1.6644
## hu, 2023_LF-RTMS_10-10EEG_SC_MCCB_1 1.0248
## huang, 2016_HF-RTMS_CM_P_PANSS_1 0.5152
## huang, 2016_HF-RTMS_CM_N_PANSS_1 1.2151
## huang, 2016_HF-RTMS_CM_G_PANSS_1 1.3877
## huang, 2016_HF-RTMS_CM_T_PANSS_1 3.2654
## huang, 2016_HF-RTMS_CM_RPS_WSCT total errors_1 1.8621
## jeon, 2018_TDCS_10-20EEG_P_PANSS_1 1.2663
## jeon, 2018_TDCS_10-20EEG_N_PANSS_1 1.3627
## jeon, 2018_TDCS_10-20EEG_G_PANSS_1 2.2182
## jeon, 2018_TDCS_10-20EEG_T_PANSS_1 5.0319
## jeon, 2018_TDCS_10-20EEG_PS_MCCB_1 2.8516
## jeon, 2018_TDCS_10-20EEG_AV_MCCB_1 2.9885
## jeon, 2018_TDCS_10-20EEG_WM_MCCB_1 3.1216
## jeon, 2018_TDCS_10-20EEG_VerL_MCCB_1 2.3644
## jeon, 2018_TDCS_10-20EEG_VisL_MCCB_1 3.6417
## jeon, 2018_TDCS_10-20EEG_RPS_MCCB_1 1.9589
## jeon, 2018_TDCS_10-20EEG_SC_MCCB_1 2.4294
## jeon, 2018_TDCS_10-20EEG_GC_MCCB Composite Score_1 3.2747
## jeon, 2018_TDCS_10-20EEG_RPS_WCST Perservative Responses_1 3.1643
## jeon, 2018_TDCS_10-20EEG_RPS_WCST Perservative Errors_1 3.0119
## jeon, 2018_TDCS_10-20EEG_RPS_WCST Categoris number_1 0.4353
## jin, 2023_ITBS_NA_SC_FERT_1 0.0690
## jin, 2023_ITBS_NA_SC_HT_1 0.4247
## jin, 2023_ITBS_NA_T_PANSS_1 0.9427
## jin, 2023_ITBS_NA_P_PANSS_1 0.5304
## jin, 2023_ITBS_NA_N_PANSS_1 0.5874
## jin, 2023_ITBS_NA_G_PANSS_1 0.6695
## kang, 2024_CTBS_CM_T_PANSS_1 3.8512
## kang, 2024_CTBS_CM_P_PANSS_1 1.3518
## kang, 2024_CTBS_CM_N_PANSS_1 1.6566
## kang, 2024_CTBS_CM_G_PANSS_1 1.8567
## kang, 2024_CTBS_CM_P_AHRS_1 3.1187
## kantrowitz, 2019_TDCS_10-20EEG_P_AHRS_1 1.6017
## kimura, 2016_HF-RTMS_10-20EEG_P_AHRS_1 2.6065
## klein, 1999_LF-RTMS_CM_P_PANSS_1 1.7339
## klein, 1999_LF-RTMS_CM_N_PANSS_1 1.5868
## klein, 1999_LF-RTMS_CM_G_PANSS_1 2.5139
## klein, 1999_LF-RTMS_CM_T_BPRS_1 2.7293
## koops, 2018_TDCS_10-20EEG_P_AHRS_1 1.4537
## koops, 2018_TDCS_10-20EEG_T_PANSS_1 3.5113
## koops, 2018_TDCS_10-20EEG_P_PANSS_1 1.1593
## koops, 2018_TDCS_10-20EEG_N_PANSS_1 1.1318
## koops, 2018_TDCS_10-20EEG_RPS_Stroop Interference_1 9.9266
## koops, 2018_TDCS_10-20EEG_PS_TMT-A_1 7.3338
## koops, 2018_TDCS_10-20EEG_RPS_TMT-B_1 13.5933
## koops, 2016_CTBS_10-20EEG_P_PANSS_1 1.1347
## koops, 2016_CTBS_10-20EEG_P_AHRS_1 1.0897
## koops, 2016_CTBS_10-20EEG_P_PSYRATS_1 1.0695
## kos, 2024_TDCS_10-20EEG_N_SANS_1 4.2701
## kos, 2024_TDCS_10-20EEG_N_AES_1 2.0038
## kumar, 2020_HF-RTMS_CM_PANSS-N_1 0.7730
## kumar, 2020_HF-RTMS_CM_PANSS-G_1 0.8309
## li, 2024 - a_ITBS_10-20EEG_GC_MCCB_1 6.6703
## li, 2024 - a_ITBS_10-20EEG_WM_MCCB_1 2.1240
## li, 2024 - a_ITBS_10-20EEG_PANSS-P_1 0.6732
## li, 2024 - a_ITBS_10-20EEG_PANSS-N_1 3.2083
## li, 2024 - a_ITBS_10-20EEG_PANSS-G_1 1.0148
## li-b-lpc, 2024_ITBS_NEURONAV_PS_MCCB_1 2.3184
## li-b-lpc, 2024_ITBS_NEURONAV_AV_MCCB_1 2.2911
## li-b-lpc, 2024_ITBS_NEURONAV_WM_MCCB_1 2.1660
## li-b-lpc, 2024_ITBS_NEURONAV_VerL_MCCB_1 3.0433
## li-b-lpc, 2024_ITBS_NEURONAV_VisL_MCCB_1 2.3306
## li-b-lpc, 2024_ITBS_NEURONAV_RPS_MCCB_1 2.8123
## li-b-lpc, 2024_ITBS_NEURONAV_SC_MCCB_1 2.5013
## li-b-lpc, 2024_ITBS_NEURONAV_GC_MCCB_1 2.6909
## li-b-dlpfc, 2024_ITBS_NEURONAV_PS_MCCB_1 2.4377
## li-b-dlpfc, 2024_ITBS_NEURONAV_AV_MCCB_1 2.5133
## li-b-dlpfc, 2024_ITBS_NEURONAV_WM_MCCB_1 2.5377
## li-b-dlpfc, 2024_ITBS_NEURONAV_VerL_MCCB_1 3.1132
## li-b-dlpfc, 2024_ITBS_NEURONAV_VisL_MCCB_1 2.3955
## li-b-dlpfc, 2024_ITBS_NEURONAV_RPS_MCCB_1 2.7421
## li-b-dlpfc, 2024_ITBS_NEURONAV_SC_MCCB_1 2.4502
## li-b-dlpfc, 2024_ITBS_NEURONAV_GC_MCCB_1 2.8427
## lindenmayer, 2019_TDCS_10-20EEG_AHRS_1 2.1329
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-T_1 2.8919
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-P_1 0.9729
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-N_1 0.7487
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-G_1 1.2034
## lindenmayer, 2019_TDCS_10-20EEG_GC_MCCB_1 6.0027
## lindenmayer, 2019_TDCS_10-20EEG_PS_MCCB_1 6.0651
## lindenmayer, 2019_TDCS_10-20EEG_AV_MCCB_1 5.1344
## lindenmayer, 2019_TDCS_10-20EEG_WM_MCCB_1 3.8050
## lindenmayer, 2019_TDCS_10-20EEG_VerL_MCCB_1 2.0036
## lindenmayer, 2019_TDCS_10-20EEG_VisL_MCCB_1 5.4185
## lindenmayer, 2019_TDCS_10-20EEG_RPN_MCCB_1 4.0055
## lindenmayer, 2019_TDCS_10-20EEG_SC_MCCB_1 4.3809
## lisoni, 2022_TDCS_10-20 EEG_PANSS-P_1 0.9756
## lisoni, 2022_TDCS_10-20 EEG_PANSS-N_1 0.8533
## lisoni, 2022_TDCS_10-20 EEG_PANSS-T_1 2.9335
## lisoni, 2022_TDCS_10-20 EEG_PANSS-G_1 1.5354
## lisoni, 2022_TDCS_10-20 EEG_GC_BACS (Composite z-scores)_1 0.1978
## lisoni, 2022_TDCS_10-20 EEG_VerL_BACS z-scores (Verbal memory)_1 2.2373
## lisoni, 2022_TDCS_10-20 EEG_WM_BACS z-scores (Digit sequencing)_1 0.9304
## lisoni, 2022_TDCS_10-20 EEG_PS_BACS z-scores (Verbal fluency)_1 2.5189
## lisoni, 2022_TDCS_10-20 EEG_PS_BACS z-scores (Symbol coding)_1 2.9969
## lisoni, 2022_TDCS_10-20 EEG_RPS_BACS z-scores (Tower of London)_1 0.8989
## liu, 2024_HF-RTMS_NA_T_PANSS_1 3.7598
## liu, 2024_HF-RTMS_NA_P_PANSS_1 1.5038
## liu, 2024_HF-RTMS_NA_N_PANSS_1 1.4242
## liu, 2024_HF-RTMS_NA_G_PANSS_1 1.4823
## liu, 2024_HF-RTMS_NA_VerL_RBANS (Immediate memory)_1 3.0632
## liu, 2024_HF-RTMS_NA_VisL_RBANS (Visual spatial structure)_1 2.9514
## liu, 2024_HF-RTMS_NA_PS_RBANS (Speech function)_1 3.2434
## liu, 2024_HF-RTMS_NA_WM_RBANS (Attention)_1 3.1881
## liu, 2024_HF-RTMS_NA_Visl_RBANS (Delayed memory)_1 4.4263
## lyu, 2024_TDCS_10-20EEG_T_PANSS_1 2.7562
## lyu, 2024_TDCS_10-20EEG_P_PANSS_1 1.0278
## lyu, 2024_TDCS_10-20EEG_N_PANSS_1 1.4341
## lyu, 2024_TDCS_10-20EEG_G_PANSS_1 1.3107
## lyu, 2024_TDCS_10-20EEG_N_SANS_1 3.6185
## mao, 2023_HF-RTMS_CM_GC_RBANS_1 2.6465
## mao, 2023_HF-RTMS_CM_VerL_RBANS-Immediate Memory_1 3.2726
## mao, 2023_HF-RTMS_CM_RBANS-Visuospatial_1 3.0234
## mao, 2023_HF-RTMS_CM_VerL_RBANS-Language_1 3.0340
## mao, 2023_HF-RTMS_CM_WM_RBANS-Attention_1 3.3970
## mao, 2023_HF-RTMS_CM_VerL_RBANS-Delayed memory_1 4.0535
## mao, 2023_HF-RTMS_CM_P_AHRS_1 0.8545
## mao, 2023_HF-RTMS_CM_T_PANSS_1 2.6283
## marquardt, 2022_TDCS_10-20EEG_P_PANSS_1 2.6330
## marquardt, 2022_TDCS_10-20EEG_N_PANSS_1 2.7908
## marquardt, 2022_TDCS_10-20EEG_P_AHRS_1 2.4844
## marquardt, 2022_TDCS_10-20EEG_RPS_Stroop 3 (s/RT)_1 8.2469
## marquardt, 2022_TDCS_10-20EEG_RPS_Stroop 4 (s/RT)_1 12.2104
## marquardt, 2022_TDCS_10-20EEG_PS_TMT-A_1 6.4724
## marquardt, 2022_TDCS_10-20EEG_RPS_TMT-B_1 19.3186
## mcintosh, 2004_LF-RTMS_10-20EEG_P_PANSS_1 2.0684
## mcintosh, 2004_LF-RTMS_10-20EEG_N_PANSS_1 2.3243
## mcintosh, 2004_LF-RTMS_10-20EEG_VerL_AVLT_1 3.7810
## meiron, 2021_TDCS_10-20EEG_T_PANSS_1 6.7916
## meiron, 2021_TDCS_10-20EEG_WM_(verbal) WM - Accuracy_1 10.0107
## meiron, 2021_TDCS_10-20EEG_WM_(verbal) WM - RT_1 49.3885
## meiron, 2024_TDCS_10-20EEG_T_PANSS_1 5.8477
## meiron, 2024_TDCS_10-20EEG_WM_2-BACK Acc_1 7.8156
## meiron, 2024_TDCS_10-20EEG_WM_2-BACK RT_1 42.7029
## mellin-tacs, 2018_TACS_10-20EEG_P_AHRS_1 2.3049
## mellin-tacs, 2018_TACS_10-20EEG_T_PANSS-T_1 4.0421
## mellin-tacs, 2018_TACS_10-20EEG_P_PANSS-P_1 1.7592
## mellin-tacs, 2018_TACS_10-20EEG_N_PANSS-N_1 1.7024
## mellin-tacs, 2018_TACS_10-20EEG_G_PANSS-G_1 2.4414
## mellin-tacs, 2018_TACS_10-20EEG_GC_BACS_1 3.2983
## mellin-tdcs, 2018_TDCS_10-20EEG_P_AHRS_1 2.9478
## mellin-tdcs, 2018_TDCS_10-20EEG_T_PANSS_1 4.9888
## mellin-tdcs, 2018_TDCS_10-20EEG_P_PANSS_1 1.5366
## mellin-tdcs, 2018_TDCS_10-20EEG_N_PANSS_1 2.2279
## mellin-tdcs, 2018_TDCS_10-20EEG_G_PANSS_1 2.6773
## mellin-tdcs, 2018_TDCS_10-20EEG_GC_BACS_1 3.9736
## moeller, 2022_DTMS_CM_T_PANSS_1 4.3705
## moeller, 2022_DTMS_CM_P_PANSS_1 1.7880
## moeller, 2022_DTMS_CM_N_PANSS_1 2.1254
## mogg, 2007_HF-RTMS_CM_VerL_HVLT immediate recall_1 0.6929
## mogg, 2007_HF-RTMS_CM_VerL_HVLT delayed recall_1 0.9608
## mogg, 2007_HF-RTMS_CM_PS_COWAT (number)_1 1.7925
## mogg, 2007_HF-RTMS_CM_RPS_Stroop RT (seconds)_1 7.2172
## mondino, 2015_TDCS_10-20EG_P_PANSS_1 1.3530
## mondino, 2015_TDCS_10-20EG_N_PANSS_1 1.8472
## mondino, 2015_TDCS_10-20EG_G_PANSS_1 2.2933
## mondino, 2015_TDCS_10-20EG_P_AHRS_1 2.6696
## novak, 2006_HF-RTMS_CM_T_PANSS_1 6.7943
## novak, 2006_HF-RTMS_CM_P_PANSS_1 1.7379
## novak, 2006_HF-RTMS_CM_N_PANSS_1 2.4678
## novak, 2006_HF-RTMS_CM_G_PANSS_1 3.5073
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_SAPS_1 7.6626
## paillere-martinot, 2017_LF-RTMS_NEURONAV_N_SANS_1 8.1293
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_AHRS_1 3.0737
## palm, 2016_TDCS_10-20EEG_T_PANSS_1 5.2636
## palm, 2016_TDCS_10-20EEG_P_PANSS_1 1.3441
## palm, 2016_TDCS_10-20EEG_N_PANSS_1 1.6956
## palm, 2016_TDCS_10-20EEG_N_SANS_1 6.4075
## palm, 2016_TDCS_10-20EEG_WM_SOPT_1 1.4252
## palm, 2016_TDCS_10-20EEG_PS_TMT-A_1 7.0516
## palm, 2016_TDCS_10-20EEG_RPS_TMT-B_1 25.7229
## prikryl, 2007_HF-RTMS_CM_T_PANSS_1 3.4590
## prikryl, 2007_HF-RTMS_CM_P_PANSS_1 0.5493
## prikryl, 2007_HF-RTMS_CM_N_PANSS_1 1.7147
## prikryl, 2007_HF-RTMS_CM_N_SANS_1 5.7979
## prikryl, 2007_HF-RTMS_CM_P_SAPS_1 0.9915
## prikryl, 2012_HF-RTMS_CM_P_PANSS_1 0.5810
## prikryl, 2012_HF-RTMS_CM_N_PANSS_1 1.3747
## prikryl, 2012_HF-RTMS_CM_G_PANSS_1 1.4854
## prikryl, 2012_HF-RTMS_CM_T_PANSS_1 3.1738
## prikryl, 2012_HF-RTMS_CM_PS_VFT_1 3.6151
## prikryl, 2014_HF-RTMS_CM_T_PANSS_1 2.5604
## prikryl, 2014_HF-RTMS_CM_P_PANSS_1 0.5266
## prikryl, 2014_HF-RTMS_CM_N_PANSS_1 1.2594
## prikryl, 2014_HF-RTMS_CM_G_PANSS_1 1.3967
## prikryl, 2013_HF-RTMS_CM_N_SANS_1 4.5538
## prikryl, 2013_HF-RTMS_CM_P_SAPS_1 0.6823
## quan, 2015_HF-RTMS_CM_T_PANSS_1 1.8186
## quan, 2015_HF-RTMS_CM_P_PANSS_1 0.7982
## quan, 2015_HF-RTMS_CM_N_PANSS_1 0.7792
## quan, 2015_HF-RTMS_CM_G_PANSS_1 0.8378
## quan, 2015_HF-RTMS_CM_N_SANS_1 2.0632
## rabany, 2014_DTMS_CM_T_PANSS_1 6.7610
## rabany, 2014_DTMS_CM_N_PANSS_1 1.2658
## rabany, 2014_DTMS_CM_N_SANS_1 5.4064
## rabany, 2014_DTMS_CM_AV_RVP-A_1 0.0171
## rabany, 2014_DTMS_CM_AV_RVP-B_1 0.0478
## rabany, 2014_DTMS_CM_WM_SWM (Total between search errors)_1 9.1405
## rabany, 2014_DTMS_CM_WM_SWM (Strategy score)_1 9.3620
## rabany, 2014_DTMS_CM_RPS_SOC (Minimum move solutions for test trials)_1 0.6119
## rabany, 2014_DTMS_CM_RPS_SOC (Initial times for 5 move problems)_1 4940.4157
## rabany, 2014_DTMS_CM_RPS_SOC (Subsequent times for 5 move problems)_1 439.6646
## rabany, 2014_DTMS_CM_PS_RTI (Mean reaction time, stages 4 and 5)_1 91.1443
## rabany, 2014_DTMS_CM_PS_RTI (Mean movement time, stages 4 and 5)_1 41.0022
## rollnik, 2000_HF-RTMS_CM_T_BPRS_1 5.0598
## rollnik, 2000_HF-RTMS_CM_PS_NCT (seconds)_1 15.0615
## rosa, 2007_LF-RTMS_10-20EEG_T_PANSS_1 5.4841
## rosa, 2007_LF-RTMS_10-20EEG_P_PANSS_1 2.0184
## rosa, 2007_LF-RTMS_10-20EEG_N_PANSS_1 1.7696
## rosa, 2007_LF-RTMS_10-20EEG_G_PANSS_1 3.3970
## rosenberg, 2012_LF-RTMS_CM_P_AHRS_1 2.2944
## saba, 2006_LF-RTMS_CM_T_PANSS_1 6.0568
## saba, 2006_LF-RTMS_CM_P_PANSS_1 1.8520
## saba, 2006_LF-RTMS_CM_N_PANSS_1 2.0245
## saba, 2006_LF-RTMS_CM_G_PANSS_1 3.1842
## schilling, 2021_TDCS_10-20EEG_WM_Verbal Working Memory Reaction Time (t-score)_1 2.1854
## schilling, 2021_TDCS_10-20EEG_WM_Verbal Working Memory d-prime (z-score)_1 0.2201
## schilling, 2021_TDCS_10-20EEG_RPS_Response Inhibition Reaction Time (t-score)_1 2.1348
## schilling, 2021_TDCS_10-20EEG_RPS_Response Inhibition Errors (t-scores)_1 2.2199
## schilling, 2021_TDCS_10-20EEG_RPS_Problem solving t-score_1 2.2289
## schilling, 2021_TDCS_10-20EEG_RPS_Mental Flexibility Speed (t-score)_1 2.0339
## schilling, 2021_TDCS_10-20EEG_RPS_Mental Flexibility Accuracy (t-score)_1 2.1956
## singh, 2020_HF-RTMS_CM_P_PANSS_1 0.8812
## singh, 2020_HF-RTMS_CM_N_PANSS_1 1.4935
## singh, 2020_HF-RTMS_CM_N_SANS_1 5.5172
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_AHRS_1 1.7910
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_PANSS_1 1.1814
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_AHRS_1 1.7037
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_PANSS_1 1.0081
## smith, 2015_TDCS_10-20EEG_GC_MCCB_1 4.1163
## smith, 2015_TDCS_10-20EEG_WM_MCCB_1 4.3606
## smith, 2015_TDCS_10-20EEG_AV_MCCB_1 4.0105
## smith, 2015_TDCS_10-20EEG_RPS_MCCB_1 2.2320
## smith, 2015_TDCS_10-20EEG_VerL_MCCB_1 2.7491
## smith, 2015_TDCS_10-20EEG_VisL_MCCB_1 3.4338
## smith, 2015_TDCS_10-20EEG_PS_MCCB_1 4.0134
## smith, 2015_TDCS_10-20EEG_SC_MCCB_1 2.7381
## smith, 2015_TDCS_10-20EEG_T_PANSS_1 4.8768
## smith, 2015_TDCS_10-20EEG_P_PANSS_1 1.7653
## smith, 2015_TDCS_10-20EEG_N_PANSS_1 2.0675
## smith, 2015_TDCS_10-20EEG_G_PANSS_1 2.3318
## smith, 2020_TDCS_10-20EEG_GC_MCCB_1 2.1095
## smith, 2020_TDCS_10-20EEG_PS_MCCB_1 2.4169
## smith, 2020_TDCS_10-20EEG_AV_MCCB_1 2.1997
## smith, 2020_TDCS_10-20EEG_WM_MCCB_1 2.7234
## smith, 2020_TDCS_10-20EEG_VerL_MCCB_1 2.4889
## smith, 2020_TDCS_10-20EEG_VisL_MCCB_1 2.6274
## smith, 2020_TDCS_10-20EEG_RPS_MCCB_1 1.8769
## smith, 2020_TDCS_10-20EEG_SC_MCCB_1 1.4940
## smith, 2020_TDCS_10-20EEG_AV_PASAT (Number Correct)_1 2.7218
## smith, 2020_TDCS_10-20EEG_T_PANSS_1 3.3744
## smith, 2020_TDCS_10-20EEG_P_PANSS_1 1.0846
## smith, 2020_TDCS_10-20EEG_N_PANSS_1 1.2865
## su, 2023b_HF-RTMS_NEURONAV_T_PANSS_1 5.6387
## su, 2023b_HF-RTMS_NEURONAV_P_PANSS_1 1.9428
## su, 2023b_HF-RTMS_NEURONAV_N_PANSS_1 2.1384
## su, 2023b_HF-RTMS_NEURONAV_G_PANSS_1 2.2246
## su, 2022_HF-RTMS_NEURONAV_T_PANSS_1 5.2345
## su, 2022_HF-RTMS_NEURONAV_P_PANSS_1 1.8284
## su, 2022_HF-RTMS_NEURONAV_N_PANSS_1 2.0019
## su, 2022_HF-RTMS_NEURONAV_G_PANSS_1 2.1026
## tikka, 2017_CTBS_NEURONAV_P_PANSS_1 1.4881
## tikka, 2017_CTBS_NEURONAV_N_PANSS_1 2.0779
## tikka, 2017_CTBS_NEURONAV_G_PANSS_1 3.0817
## tikka, 2017_CTBS_NEURONAV_T_PANSS_1 4.8631
## tikka, 2017_CTBS_NEURONAV_RPS_Self-Monitoring Task_1 1.1066
## tikka, 2017_CTBS_NEURONAV_WM_Visual Memory Task_1 0.3194
## tyagi, 2022_CTBS_10-20EEG_P_PANSS_1 0.8044
## tyagi, 2022_CTBS_10-20EEG_N_PANSS_1 1.0987
## tyagi, 2022_CTBS_10-20EEG_T_PANSS_1 2.3342
## tyagi, 2022_CTBS_10-20EEG_G_PANSS_1 1.1383
## tyagi, 2022_CTBS_10-20EEG_P_AVHRS_1 1.5987
## tyagi, 2022_CTBS_10-20EEG_P_PSYRAT-AH_1 1.0437
## valiengo, 2020_TDCS_10-20EEG_N_PANSS_1 0.6836
## valiengo, 2020_TDCS_10-20EEG_P_PANSS_1 0.7269
## valiengo, 2020_TDCS_10-20EEG_T_PANSS_1 2.4152
## valiengo, 2020_TDCS_10-20EEG_G_PANSS_1 1.4844
## valiengo, 2020_TDCS_10-20EEG_P_AVHRS_1 1.9181
## vercammen, 2011_TDCS_10-20EEG_RPS_Weather Prediction Test_1 2.4477
## vergallito, 2024_ITBS_10-20EEG_T_PANSS_1 10.2981
## vergallito, 2024_ITBS_10-20EEG_P_PANSS_1 2.0579
## vergallito, 2024_ITBS_10-20EEG_N_PANSS_1 5.2587
## vergallito, 2024_ITBS_10-20EEG_N_BNSS_1 7.8701
## vergallito, 2024_ITBS_10-20EEG_GC_MCCB_1 5.0091
## vergallito, 2024_ITBS_10-20EEG_PS_MCCB_1 5.5219
## vergallito, 2024_ITBS_10-20EEG_AV_MCCB_1 5.5574
## vergallito, 2024_ITBS_10-20EEG_WM_MCCB_1 4.5233
## vergallito, 2024_ITBS_10-20EEG_VerL_MCCB_1 6.7228
## vergallito, 2024_ITBS_10-20EEG_VisL_MCCB_1 5.6025
## vergallito, 2024_ITBS_10-20EEG_RPS_MCCB_1 4.4531
## vergallito, 2024_ITBS_10-20EEG_SC_MCCB_1 6.1784
## walther-lft, 2024_UNKNOWN_STANDARD_T_PANSS_1 0.9811
## walther-lft, 2024_UNKNOWN_STANDARD_P_PANSS_1 0.2928
## walther-lft, 2024_UNKNOWN_STANDARD_N_PANSS_1 0.3482
## walther-lft, 2024_UNKNOWN_STANDARD_G_PANSS_1 0.5141
## walther-lft, 2024_UNKNOWN_STANDARD_N_BNSS_1 0.7000
## walther-itbs, 2024_ITBS_CM_T_PANSS_1 0.9466
## walther-itbs, 2024_ITBS_CM_P_PANSS_1 0.2745
## walther-itbs, 2024_ITBS_CM_N_PANSS_1 0.3334
## walther-itbs, 2024_ITBS_CM_G_PANSS_1 0.5023
## walther-itbs, 2024_ITBS_CM_N_BNSS_1 0.6720
## wang, 2020_ITBS_NEURONAV_T_PANSS_1 3.2783
## wang, 2020_ITBS_NEURONAV_P_PANSS_1 1.2092
## wang, 2020_ITBS_NEURONAV_N_PANSS_1 0.9863
## wang, 2020_ITBS_NEURONAV_G_PANSS_1 1.5704
## wang, 2020_ITBS_NEURONAV_P_SAPS_1 2.4192
## wang, 2020_ITBS_NEURONAV_N_SANS_1 2.5127
## wang, 2020_ITBS_NEURONAV_GC_MoCA_1 0.4892
## wang, 2020_ITBS_NEURONAV_PS_VFT_1 0.9011
## wang, 2020_ITBS_NEURONAV_WM_Digit span (forward)_1 0.2067
## wang, 2020_ITBS_NEURONAV_WM_Digit span (backward)_1 0.3023
## wang, 2020_ITBS_NEURONAV_RPS_Stroop Color Test_1 1.2457
## wang, 2020_ITBS_NEURONAV_RPS_Stroop Word Test_1 1.5818
## wang, 2020_ITBS_NEURONAV_RPS_Stroop Interference Test_1 2.0667
## wang, 2020_ITBS_NEURONAV_PS_TMT-A_1 4.3409
## wang, 2020_ITBS_NEURONAV_RPS_TMT-B_1 7.4228
## wang, 2022_ITBS_NEURONAV_P_PANSS_1 1.3926
## wang, 2022_ITBS_NEURONAV_N_PANSS_1 0.8893
## wang, 2022_ITBS_NEURONAV_G_PANSS_1 1.6062
## wang, 2022_ITBS_NEURONAV_T_PANSS_1 3.6723
## wang, 2022_ITBS_NEURONAV_P_SAPS_1 3.6999
## wang, 2022_ITBS_NEURONAV_N_SANS_1 2.5920
## wang, 2022_ITBS_NEURONAV_GC_MoCA_1 0.4986
## wang, 2022_ITBS_NEURONAV_WM_3-back RT_1 36.7997
## weickert, 2019_TDCS_10-20EEG_T_PANSS_1 6.3705
## weickert, 2019_TDCS_10-20EEG_P_PANSS_1 2.3094
## weickert, 2019_TDCS_10-20EEG_N_PANSS_1 1.7952
## weickert, 2019_TDCS_10-20EEG_G_PANSS_1 4.4682
## weickert, 2019_TDCS_10-20EEG_P_AHRS_1 5.3424
## weickert, 2019_TDCS_10-20EEG_PS_BACS sc_1 4.2086
## weickert, 2019_TDCS_10-20EEG_PS_TMT-A_1 4.4513
## weickert, 2019_TDCS_10-20EEG_WM_LNS_1 1.7529
## weickert, 2019_TDCS_10-20EEG_VerL_HVLTr_1 2.9596
## weickert, 2019_TDCS_10-20EEG_VisL_BVMT_1 3.7922
## weickert, 2019_TDCS_10-20EEG_RPS_NAB maze_1 3.9833
## weickert, 2019_TDCS_10-20EEG_PS_fluency_1 3.4473
## wen, 2021_HF-RTMS_CM_T_PANSS_1 2.4856
## wen, 2021_HF-RTMS_CM_P_PANSS_1 0.8888
## wen, 2021_HF-RTMS_CM_N_PANSS_1 0.8401
## wen, 2021_HF-RTMS_CM_G_PANSS_1 1.8948
## wen, 2021_HF-RTMS_CM_GC_RBANS-T_1 2.8165
## wen, 2021_HF-RTMS_CM_VerL_RBANS\r\nImmediate memory_1 2.9066
## wen, 2021_HF-RTMS_CM_WM_RBANS\r\nAttention_1 3.5799
## wen, 2021_HF-RTMS_CM_VisL_RBANS\r\nVisuospatial_1 4.1277
## wen, 2021_HF-RTMS_CM_VisL_RBANS\r\nDelayed memory_1 4.2220
## wen, 2021_HF-RTMS_CM_VerL_RBANS\r\nLanguage_1 3.3327
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n1 word (s)_1 2.4902
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n2 word (s)_1 2.6969
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n3 word (s)_1 3.0930
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n3 color (s)_1 1.9671
## wobrock, 2015_HF-RTMS_10-20EEG_T_PANSS_1 2.3178
## wobrock, 2015_HF-RTMS_10-20EEG_P_PANSS_1 0.5978
## wobrock, 2015_HF-RTMS_10-20EEG_N_PANSS_1 0.7602
## xie, 2023-a_LF-RTMS_10-20EEG_T_PANSS_1 1.9406
## xie, 2023-a_LF-RTMS_10-20EEG_P_PANSS_1 0.8203
## xie, 2023-a_LF-RTMS_10-20EEG_N_PANSS_1 0.8569
## xie, 2023-a_LF-RTMS_10-20EEG_G_PANSS_1 1.2197
## xie, 2023-a_LF-RTMS_10-20EEG_P_AHRS_1 1.2347
## xiu-10hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 3.2142
## xiu-10hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 0.9447
## xiu-10hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 1.1028
## xiu-10hz, 2020_HF-RTMS_NEURONAV_G_PANSS_1 1.6339
## xiu-10hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 2.6031
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nImmediate memory_1 2.7509
## xiu-10hz, 2020_HF-RTMS_NEURONAV_WM_RBANS\r\nAttention_1 2.9166
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nVisuospatial_1 2.4311
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nDelayed memory_1 3.8428
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nLanguage_1 2.8890
## xiu-20hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 3.1952
## xiu-20hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 0.7855
## xiu-20hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 1.5069
## xiu-20hz, 2020_HF-RTMS_NEURONAV_G_PANSS_1 1.5832
## xiu-20hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 2.7838
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nImmediate memory_1 2.8514
## xiu-20hz, 2020_HF-RTMS_NEURONAV_WM_RBANS\r\nAttention_1 2.8668
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nVisuospatial_1 3.1442
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nDelayed memory_1 3.8584
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nLanguage_1 2.8917
## xu, 2023_HD-TDCS_10-20EEG_T_PANSS_1 4.1812
## xu, 2023_HD-TDCS_10-20EEG_P_PANSS_1 1.4000
## xu, 2023_HD-TDCS_10-20EEG_N_PANSS_1 1.3468
## xu, 2023_HD-TDCS_10-20EEG_G_PANSS_1 1.9758
## xu, 2023_HD-TDCS_10-20EEG_GC_RBANS_1 2.5523
## ye-20hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 3.1723
## ye-20hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Immediate memory_1 4.0206
## ye-20hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Visuospatial_1 3.5691
## ye-20hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Language_1 5.8635
## ye-20hz, 2024_HF-RTMS_NEURONAV_WM_RBANS - Attention_1 3.0343
## ye-20hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Delayed memory_1 4.6007
## ye-10hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 2.8245
## ye-10hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Immediate memory_1 3.7730
## ye-10hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Visuospatial_1 2.9414
## ye-10hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Language_1 3.2777
## ye-10hz, 2024_HF-RTMS_NEURONAV_WM_RBANS - Attention_1 2.8800
## ye-10hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Delayed memory_1 3.8406
## yuanjun, 2024_LF-RTMS_10-20EEG_T_PANSS_1 1.9958
## yuanjun, 2024_LF-RTMS_10-20EEG_P_PANSS_1 0.8576
## yuanjun, 2024_LF-RTMS_10-20EEG_N_PANSS_1 0.8569
## yuanjun, 2024_LF-RTMS_10-20EEG_G_PANSS_1 1.2559
## yuanjun, 2024_LF-RTMS_10-20EEG_P_AHRS_1 1.2685
## zhai-a, 2023_HF-RTMS_NA_T_PANSS_1 1.0572
## zhang, 2022_TACS_10-20EEG_T_PANSS_1 4.9937
## zhang, 2022_TACS_10-20EEG_P_PANSS_1 1.3451
## zhang, 2022_TACS_10-20EEG_N_PANSS_1 1.6392
## zhang, 2022_TACS_10-20EEG_P_AHRS_1 2.1433
## zhao-tbs, 2014_ITBS_10-20EEG_T_PANSS_1 1.9638
## zhao-tbs, 2014_ITBS_10-20EEG_P_PANSS_1 0.7147
## zhao-tbs, 2014_ITBS_10-20EEG_N_PANSS_1 1.3317
## zhao-tbs, 2014_ITBS_10-20EEG_G_PANSS_1 0.6516
## zhao-tbs, 2014_ITBS_10-20EEG_N_SANS_1 2.3221
## zhao-20hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 1.8042
## zhao-20hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 0.9163
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 1.4214
## zhao-20hz, 2014_HF-RTMS_10-20EEG_G_PANSS_1 0.8058
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 2.3276
## zhao-10hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 1.9376
## zhao-10hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 0.4153
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 1.1441
## zhao-10hz, 2014_HF-RTMS_10-20EEG_G_PANSS_1 0.7019
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 2.1682
## zhou, 2024_HF-RTMS_10-20EEG_P_PANSS_1 0.4355
## zhou, 2024_HF-RTMS_10-20EEG_N_PANSS_1 0.8641
## zhou, 2024_HF-RTMS_10-20EEG_T_PANSS_1 2.4709
## zhou, 2024_HF-RTMS_10-20EEG_G_PANSS_1 1.3371
## zhou, 2024_HF-RTMS_10-20EEG_GC_RBANS-T_1 2.0139
## zhou, 2024_HF-RTMS_10-20EEG_VerL_RBANS\r\nImmediate memory_1 2.4148
## zhou, 2024_HF-RTMS_10-20EEG_VisL_RBANS\r\nVisuospatial_1 1.1103
## zhou, 2024_HF-RTMS_10-20EEG_VerL_RBANS\r\nLanguage_1 2.9843
## zhou, 2024_HF-RTMS_10-20EEG_WM_RBANS\r\nAttention_1 3.0463
## zhou, 2024_HF-RTMS_10-20EEG_VisL_RBANS\r\nDelayed memory_1 1.8616
## zhou, 2024_HF-RTMS_10-20EEG_RPS_SCWT \r\nInference scores_1 9.4745
## zhou, 2023_TDCS_10-20EEG_T_PANSS_1 2.8841
## zhou, 2023_TDCS_10-20EEG_N_SANS_1 4.2033
## zhou, 2023_TDCS_10-20EEG_RPS_IED total errors_1 18.4819
## zhu, 2021_ITBS_CM_N_PANSS_1 1.5094
## zhuo, 2019_HF-RTMS_10-20EEG_T_PANSS_1 1.4391
## zhuo, 2019_HF-RTMS_10-20EEG_P_PANSS_1 0.5742
## zhuo, 2019_HF-RTMS_10-20EEG_N_PANSS_1 0.7287
## zhuo, 2019_HF-RTMS_10-20EEG_G_PANSS_1 0.7308
## zhuo, 2019_HF-RTMS_10-20EEG_N_SANS_1 2.3424
## zhuo, 2019_HF-RTMS_10-20EEG_PS_MCCB TMT-A_1 1.9501
## zhuo, 2019_HF-RTMS_10-20EEG_PS_MCCB BACS_1 1.5587
## zhuo, 2019_HF-RTMS_10-20EEG_PS_MCCB Fluency_1 2.6635
## zhuo, 2019_HF-RTMS_10-20EEG_WM_MCCB Working memory (WMS-SS)_1 2.1307
## zhuo, 2019_HF-RTMS_10-20EEG_VerL_MCCB Verbal learning (HVLT-R)_1 1.8186
## zhuo, 2019_HF-RTMS_10-20EEG_VisL_MCCB Visual learning (BVMT-R)_1 2.0971
## zhuo, 2019_HF-RTMS_10-20EEG_RPS_MCCB Reasoning/problem solving (NAB)_1 1.8657
## zhuo, 2019_HF-RTMS_10-20EEG_SC_MCCB Social cognition (MSCEIT)_1 2.2760
## zhuo, 2019_HF-RTMS_10-20EEG_GC_MCCB Composite score_1 1.5850
##
## Number of treatment arms (by study):
## narms
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANSS_1 2
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANSS_1 2
## bais, 2014 - l_LF-RTMS_10-20EEG_G_PANSS_1 2
## bais, 2014 - l_LF-RTMS_10-20EEG_P_AHRS_1 2
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANAS_1 2
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANAS_1 2
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANSS_1 2
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANSS_1 2
## bais, 2014 - bi_LF-RTMS_10-20EEG_G_PANSS_1 2
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_AHRS_1 2
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANAS_1 2
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANAS_1 2
## barr, 2011_HF-RTMS_NEURONAV_WM_1-back RT ms_1 2
## barr, 2011_HF-RTMS_NEURONAV_WM_2-back RT ms_1 2
## barr, 2011_HF-RTMS_NEURONAV_WM_3-back RT ms_1 2
## barr, 2013_HF-RTMS_NEURONAV_WM_1-back RT ms Target Correct_1 2
## barr, 2013_HF-RTMS_NEURONAV_WM_1-back RT ms Non Target Correct_1 2
## barr, 2013_HF-RTMS_NEURONAV_WM_3-back RT ms Target Correct_1 2
## barr, 2013_HF-RTMS_NEURONAV_WM_3-back RT ms Non Target Correct_1 2
## barr, 2012_HF-RTMS_NEURONAV_P_PANSS_1 2
## barr, 2012_HF-RTMS_NEURONAV_N_PANSS_1 2
## barr, 2012_HF-RTMS_NEURONAV_N_SANS_1 2
## basavaraju, 2021_ITBS_NEURONAV_N_SANS_1 2
## basavaraju, 2021_ITBS_NEURONAV_P_SAPS_1 2
## basavaraju, 2021_ITBS_NEURONAV_VerL_AVLT Hits_1 2
## basavaraju, 2021_ITBS_NEURONAV_VisL_CFT copying_1 2
## basavaraju, 2021_ITBS_NEURONAV_VisL_CFT Immediate Recall_1 2
## basavaraju, 2021_ITBS_NEURONAV_VisL_CFT Delayed Recall_1 2
## basavaraju, 2021_ITBS_NEURONAV_PS_DSST time (sec)_1 2
## basavaraju, 2021_ITBS_NEURONAV_PS_DSST errors_1 2
## basavaraju, 2021_ITBS_NEURONAV_AV_DVT time (sec)_1 2
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-A time (sec)_1 2
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-A errors_1 2
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-B time (sec)_1 2
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-B errors_1 2
## basavaraju, 2021_ITBS_NEURONAV_WM_1back verbal Hits_1 2
## basavaraju, 2021_ITBS_NEURONAV_WM_1back verbal Errors_1 2
## basavaraju, 2021_ITBS_NEURONAV_WM_2back verbal Hits_1 2
## basavaraju, 2021_ITBS_NEURONAV_WM_2back verbal Errors_1 2
## basavaraju, 2021_ITBS_NEURONAV_WM_Spatial Span total_1 2
## basavaraju, 2021_ITBS_NEURONAV_RPS_FAS_1 2
## basavaraju, 2021_ITBS_NEURONAV_RPS_Stroop Effect score_1 2
## basavaraju, 2021_ITBS_NEURONAV_SC_FOT index_1 2
## basavaraju, 2021_ITBS_NEURONAV_SC_SOT index_1 2
## basavaraju, 2021_ITBS_NEURONAV_SC_Faux Pax CI_1 2
## basavaraju, 2021_ITBS_NEURONAV_SC_Personalizing Bias Index_1 2
## basavaraju, 2021_ITBS_NEURONAV_SC_Social Perception Index_1 2
## basavaraju, 2021_ITBS_NEURONAV_SC_Emotion Recognition Index_1 2
## battion, 2021_ITBS_CM_T_PANSS_1 2
## battion, 2021_ITBS_CM_N_SANS_1 2
## blumberger, 2012_LF-RTMS_NEURONAV_P_PSYRATS_1 2
## blumberger, 2012_LF-RTMS_NEURONAV_T_PANSS_1 2
## blumberger, 2012_LF-RTMS_NEURONAV_P_PANSS_1 2
## blumberger, 2012_LF-RTMS_NEURONAV_P_AHRS_1 2
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PSYRATS_1 2
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_T_PANSS_1 2
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PANSS_1 2
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_AHRS_1 2
## bodén, 2021_ITBS_CM_N_CAIN_1 2
## bose, 2018_TDCS_10-20EEG_P_SAPS_1 2
## bose, 2018_TDCS_10-20EEG_N_SANS_1 2
## bose, 2018_TDCS_10-20EEG_P_AHRS_1 2
## brunelin, 2012_TDCS_10-20EEG_P_AHRS_1 2
## brunelin, 2012_TDCS_10-20EEG_T_PANSS_1 2
## brunelin, 2006_LF-RTMS_10-20EEG_P_AHRS_1 2
## brunelin, 2006_LF-RTMS_10-20EEG_P_SAPS_1 2
## brunelin, 2006_LF-RTMS_10-20EEG_WM_MonitorSourceTask_1 2
## bulubas, 2021_TDCS_10-20EEG_VisL_PFMT Total Correct Responses_1 2
## bulubas, 2021_TDCS_10-20EEG_VerL_PWMT Total Correct Responses_1 2
## bulubas, 2021_TDCS_10-20EEG_SC_EMI Correct Responses_1 2
## bulubas, 2021_TDCS_10-20EEG_WM_PLNB 0-back True Positive Responses_1 2
## bulubas, 2021_TDCS_10-20EEG_WM_PLNB 1-back True Positive Responses_1 2
## bulubas, 2021_TDCS_10-20EEG_WM_PLNB 2-back True Positive Responses_1 2
## bulubas, 2021_TDCS_10-20EEG_RPS_PCET Number Correct Responses_1 2
## bulubas, 2021_TDCS_10-20EEG_VisL_Short VOLT Total Correct_1 2
## chang-a, 2021_TACS_10-20EEG_T_PANSS_1 2
## chang-a, 2021_TACS_10-20EEG_N_PANSS_1 2
## chang-a, 2021_TACS_10-20EEG_N_SANS_1 2
## chauhan, 2021_ITBS_10-20EEG_P_PANSS_1 2
## chauhan, 2021_ITBS_10-20EEG_N_PANSS_1 2
## chauhan, 2021_ITBS_10-20EEG_G_PANSS_1 2
## chauhan, 2021_ITBS_10-20EEG_T_PANSS_1 2
## chauhan, 2021_ITBS_10-20EEG_T_BPRS_1 2
## de jesus, 2011_LF-RTMS_10-20EEG_T_BPRS_1 2
## de jesus, 2011_LF-RTMS_10-20EEG_P_BPRS_1 2
## de jesus, 2011_LF-RTMS_10-20EEG_N_BPRS_1 2
## de jesus, 2011_LF-RTMS_10-20EEG_P_AHRS_1 2
## dharani, 2021_HD-TDCS_10-10EEG_P_PANSS_1 2
## dharani, 2021_HD-TDCS_10-10EEG_N_PANSS_1 2
## dharani, 2021_HD-TDCS_10-10EEG_G_PANSS_1 2
## dharani, 2021_HD-TDCS_10-10EEG_N_SANS_1 2
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_SANS_1 2
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_P_PANSS_1 2
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_PANSS_1 2
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_G_PANSS_1 2
## dolfus, 2018_HF-RTMS_NEURONAV_P_AHRS_1 2
## du, 2024_HF-RTMS_NEURONAV_T_BPRS_1 2
## du, 2024_HF-RTMS_NEURONAV_P_BPRS_1 2
## du, 2024_HF-RTMS_NEURONAV_N_BPRS_1 2
## du, 2022_HF-RTMS_10-20EEG_VisL_PRM number correct_1 2
## du, 2022_HF-RTMS_10-20EEG_N_SANS_1 2
## du, 2022_HF-RTMS_10-20EEG_T_PANSS_1 2
## du, 2022_HF-RTMS_10-20EEG_P_PANSS_1 2
## du, 2022_HF-RTMS_10-20EEG_N_PANSS_1 2
## du, 2022_HF-RTMS_10-20EEG_G_PANSS_1 2
## farhang, 2024_TDCS_10-20EEG_WM_ letter-number sequencing_1 2
## fitzerald, 2008_LF-RTMS_CM_N_SANS_1 2
## fitzerald, 2008_LF-RTMS_CM_P_PANSS_1 2
## fitzerald, 2008_LF-RTMS_CM_N_PANSS_1 2
## fitzerald, 2008_LF-RTMS_CM_T_PANSS_1 2
## fitzerald-l, 2014_TDCS_10-20EEG_P_PANSS_1 2
## fitzerald-l, 2014_TDCS_10-20EEG_N_PANSS_1 2
## fitzerald-l, 2014_TDCS_10-20EEG_T_PANSS_1 2
## fitzerald-l, 2014_TDCS_10-20EEG_N_SANS_1 2
## fitzerald-bi, 2014_TDCS_10-20EEG_P_PANSS_1 2
## fitzerald-bi, 2014_TDCS_10-20EEG_N_PANSS_1 2
## fitzerald-bi, 2014_TDCS_10-20EEG_T_PANSS_1 2
## fitzerald-bi, 2014_TDCS_10-20EEG_N_SANS_1 2
## francis, 2019_HF-RTMS_CM_VerL_BACS Verbal Memory_1 2
## francis, 2019_HF-RTMS_CM_WM_BACS Digit Sequencing_1 2
## francis, 2019_HF-RTMS_CM_PS_BACS Semantic and Letter Fluency_1 2
## francis, 2019_HF-RTMS_CM_PS_BACS Symbol Coding_1 2
## francis, 2019_HF-RTMS_CM_RPS_BACS Tower of London_1 2
## francis, 2019_HF-RTMS_CM_GC_BACS Composite Score_1 2
## frohlich, 2016_TDCS_10-20EEG_P_AHRS_1 2
## frohlich, 2016_TDCS_10-20EEG_T_PANSS_1 2
## frohlich, 2016_TDCS_10-20EEG_P_PANSS_1 2
## frohlich, 2016_TDCS_10-20EEG_N_PANSS_1 2
## frohlich, 2016_TDCS_10-20EEG_G_PANSS_1 2
## gao, 2024_ITBS_10-20EEG_P_PANSS_1 2
## gao, 2024_ITBS_10-20EEG_N_PANSS_1 2
## gao, 2024_ITBS_10-20EEG_G_PANSS_1 2
## gao, 2024_ITBS_10-20EEG_T_PANSS_1 2
## gao, 2024_ITBS_10-20EEG_N_SANS_1 2
## garcía-fernández, 2024_TDCS_10-20EEG_PS_MCCB_1 2
## garcía-fernández, 2024_TDCS_10-20EEG_AV_MCCB_1 2
## garcía-fernández, 2024_TDCS_10-20EEG_WM_MCCB_1 2
## garcía-fernández, 2024_TDCS_10-20EEG_VerL_MCCB_1 2
## garcía-fernández, 2024_TDCS_10-20EEG_VisL_MCCB_1 2
## garcía-fernández, 2024_TDCS_10-20EEG_RPS_MCCB_1 2
## garcía-fernández, 2024_TDCS_10-20EEG_SC_MCCB_1 2
## garg, 2016_DTMS_CM_P_PANSS_1 2
## garg, 2016_DTMS_CM_N_PANSS_1 2
## garg, 2016_DTMS_CM_G_PANSS_1 2
## garg, 2016_DTMS_CM_T_PANSS_1 2
## gogler, 2017_TDCS_10-20EEG_PS_C_1 2
## gogler, 2017_TDCS_10-20EEG_WM_K_1 2
## gogler, 2017_TDCS_10-20EEG_AV_α_1 2
## gomes, 2018_TDCS_10-20EEG_WM_MCCB_1 2
## gomes, 2018_TDCS_10-20EEG_PS_MCCB_1 2
## gomes, 2018_TDCS_10-20EEG_AV_MCCB_1 2
## gomes, 2018_TDCS_10-20EEG_VerL_MCCB_1 2
## gomes, 2018_TDCS_10-20EEG_VisL_MCCB_1 2
## gomes, 2018_TDCS_10-20EEG_RPS_MCCB_1 2
## gomes, 2018_TDCS_10-20EEG_P_PANSS_1 2
## gomes, 2018_TDCS_10-20EEG_N_PANSS-N_1 2
## gomes, 2018_TDCS_10-20EEG_G_PANSS_1 2
## gomes, 2018_TDCS_10-20EEG_T_PANSS-T_1 2
## guan, 2020_HF-RTMS_NEURONAV_T_PANSS-T_1 2
## guan, 2020_HF-RTMS_NEURONAV_P_PANSS_1 2
## guan, 2020_HF-RTMS_NEURONAV_N_PANSS-N_1 2
## guan, 2020_HF-RTMS_NEURONAV_G_PANSS_1 2
## guan, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nImmediate memory_1 2
## guan, 2020_HF-RTMS_NEURONAV_WM_RBANS\r\nAttention_1 2
## guan, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nVisuospatial/constructional_1 2
## guan, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nDelayed memory_1 2
## guan, 2020_HF-RTMS_NEURONAV_PS_RBANS\r\nLanguage_1 2
## guan, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 2
## guleken, 2020_HF-RTMS_CM_P_PANSS_1 2
## guleken, 2020_HF-RTMS_CM_N_SANS_1 2
## guleken, 2020_HF-RTMS_CM_RPS_WSCT total correct responses_1 2
## guleken, 2020_HF-RTMS_CM_RPS_WSCT perseverative errors_1 2
## guleken, 2020_HF-RTMS_CM_WM_DST forward_1 2
## guleken, 2020_HF-RTMS_CM_WM_DST backwards_1 2
## guleken, 2020_HF-RTMS_CM_RPS_Total time_1 2
## guleken, 2020_HF-RTMS_CM_RPS_Total errors_1 2
## guleken, 2020_HF-RTMS_CM_RPS_Stroop Interference_1 2
## guse, 2013_HF-RTMS_10-20EEG_PS_TMT-A_1 2
## guse, 2013_HF-RTMS_10-20EEG_RPS_TMT-B_1 2
## guse, 2013_HF-RTMS_10-20EEG_RPS_WCST Accuracy_1 2
## guse, 2013_HF-RTMS_10-20EEG_RPS_WCST RT_1 2
## guse, 2013_HF-RTMS_10-20EEG_AV_Sel. Attention Accuracy_1 2
## guse, 2013_HF-RTMS_10-20EEG_AV_Sel. Attention RT_1 2
## guse, 2013_HF-RTMS_10-20EEG_AV_Div. Attention Accuracy_1 2
## guse, 2013_HF-RTMS_10-20EEG_AV_Div. Attention RT_1 2
## guse, 2013_HF-RTMS_10-20EEG_WM_0-back Accuracy_1 2
## guse, 2013_HF-RTMS_10-20EEG_WM_0-back RT_1 2
## guse, 2013_HF-RTMS_10-20EEG_WM_1-back Accuracy_1 2
## guse, 2013_HF-RTMS_10-20EEG_WM_1-back RT_1 2
## guse, 2013_HF-RTMS_10-20EEG_WM_2-back Accuracy_1 2
## guse, 2013_HF-RTMS_10-20EEG_WM_2-back RT_1 2
## hasan, 2016_HF-RTMS_10-20EEG_WM_DST z score_1 2
## hasan, 2016_HF-RTMS_10-20EEG_WM_DST Forward_1 2
## hasan, 2016_HF-RTMS_10-20EEG_WM_DST Backward_1 2
## hasan, 2016_HF-RTMS_10-20EEG_PS_TMT-A time (s)_1 2
## hasan, 2016_HF-RTMS_10-20EEG_RPS_TMT-B time (s)_1 2
## hasan, 2016_HF-RTMS_10-20EEG_VerL_VLMT z score_1 2
## hasan, 2016_HF-RTMS_10-20EEG_RPS_WCST z score_1 2
## hasan, 2016_HF-RTMS_10-20EEG_RPS_WCST total correct score_1 2
## hasan, 2016_HF-RTMS_10-20EEG_RPS_WCST total errors_1 2
## hasan, 2016_HF-RTMS_10-20EEG_PS_RWT z score_1 2
## holi, 2004_HF-RTMS_10-20EEG_T_PANSS_1 2
## holi, 2004_HF-RTMS_10-20EEG_P_PANSS_1 2
## holi, 2004_HF-RTMS_10-20EEG_N_PANSS_1 2
## holi, 2004_HF-RTMS_10-20EEG_G_PANSS_1 2
## hu, 2024_LF-RTMS_10-20EEG_T_PANSS_1 2
## hu, 2024_LF-RTMS_10-20EEG_P_PANSS_1 2
## hu, 2024_LF-RTMS_10-20EEG_N_PANSS_1 2
## hu, 2024_LF-RTMS_10-20EEG_G_PANSS_1 2
## hu, 2024_LF-RTMS_10-20EEG_PS_TMT-A_1 2
## hu, 2024_LF-RTMS_10-20EEG_PS_BACS Symbol Coding_1 2
## hu, 2024_LF-RTMS_10-20EEG_PS_Category Fluency_1 2
## hu, 2024_LF-RTMS_10-20EEG_AV_CPT-IP_1 2
## hu, 2024_LF-RTMS_10-20EEG_WM_WMS-3 spatial span_1 2
## hu, 2024_LF-RTMS_10-20EEG_VerL_HVLT-R_1 2
## hu, 2024_LF-RTMS_10-20EEG_VisL_BVMT-R_1 2
## hu, 2024_LF-RTMS_10-20EEG_RPS_NAB_1 2
## hu, 2023_LF-RTMS_10-10EEG_T_PANSS_1 2
## hu, 2023_LF-RTMS_10-10EEG_P_PANSS_1 2
## hu, 2023_LF-RTMS_10-10EEG_N_PANSS_1 2
## hu, 2023_LF-RTMS_10-10EEG_G_PANSS_1 2
## hu, 2023_LF-RTMS_10-10EEG_GC_MCCB-T_1 2
## hu, 2023_LF-RTMS_10-10EEG_PS_MCCB_1 2
## hu, 2023_LF-RTMS_10-10EEG_AV_MCCB_1 2
## hu, 2023_LF-RTMS_10-10EEG_WM_MCCB_1 2
## hu, 2023_LF-RTMS_10-10EEG_VerL_MCCB_1 2
## hu, 2023_LF-RTMS_10-10EEG_VisL_MCCB_1 2
## hu, 2023_LF-RTMS_10-10EEG_RPS_MCCB_1 2
## hu, 2023_LF-RTMS_10-10EEG_SC_MCCB_1 2
## huang, 2016_HF-RTMS_CM_P_PANSS_1 2
## huang, 2016_HF-RTMS_CM_N_PANSS_1 2
## huang, 2016_HF-RTMS_CM_G_PANSS_1 2
## huang, 2016_HF-RTMS_CM_T_PANSS_1 2
## huang, 2016_HF-RTMS_CM_RPS_WSCT total errors_1 2
## jeon, 2018_TDCS_10-20EEG_P_PANSS_1 2
## jeon, 2018_TDCS_10-20EEG_N_PANSS_1 2
## jeon, 2018_TDCS_10-20EEG_G_PANSS_1 2
## jeon, 2018_TDCS_10-20EEG_T_PANSS_1 2
## jeon, 2018_TDCS_10-20EEG_PS_MCCB_1 2
## jeon, 2018_TDCS_10-20EEG_AV_MCCB_1 2
## jeon, 2018_TDCS_10-20EEG_WM_MCCB_1 2
## jeon, 2018_TDCS_10-20EEG_VerL_MCCB_1 2
## jeon, 2018_TDCS_10-20EEG_VisL_MCCB_1 2
## jeon, 2018_TDCS_10-20EEG_RPS_MCCB_1 2
## jeon, 2018_TDCS_10-20EEG_SC_MCCB_1 2
## jeon, 2018_TDCS_10-20EEG_GC_MCCB Composite Score_1 2
## jeon, 2018_TDCS_10-20EEG_RPS_WCST Perservative Responses_1 2
## jeon, 2018_TDCS_10-20EEG_RPS_WCST Perservative Errors_1 2
## jeon, 2018_TDCS_10-20EEG_RPS_WCST Categoris number_1 2
## jin, 2023_ITBS_NA_SC_FERT_1 2
## jin, 2023_ITBS_NA_SC_HT_1 2
## jin, 2023_ITBS_NA_T_PANSS_1 2
## jin, 2023_ITBS_NA_P_PANSS_1 2
## jin, 2023_ITBS_NA_N_PANSS_1 2
## jin, 2023_ITBS_NA_G_PANSS_1 2
## kang, 2024_CTBS_CM_T_PANSS_1 2
## kang, 2024_CTBS_CM_P_PANSS_1 2
## kang, 2024_CTBS_CM_N_PANSS_1 2
## kang, 2024_CTBS_CM_G_PANSS_1 2
## kang, 2024_CTBS_CM_P_AHRS_1 2
## kantrowitz, 2019_TDCS_10-20EEG_P_AHRS_1 2
## kimura, 2016_HF-RTMS_10-20EEG_P_AHRS_1 2
## klein, 1999_LF-RTMS_CM_P_PANSS_1 2
## klein, 1999_LF-RTMS_CM_N_PANSS_1 2
## klein, 1999_LF-RTMS_CM_G_PANSS_1 2
## klein, 1999_LF-RTMS_CM_T_BPRS_1 2
## koops, 2018_TDCS_10-20EEG_P_AHRS_1 2
## koops, 2018_TDCS_10-20EEG_T_PANSS_1 2
## koops, 2018_TDCS_10-20EEG_P_PANSS_1 2
## koops, 2018_TDCS_10-20EEG_N_PANSS_1 2
## koops, 2018_TDCS_10-20EEG_RPS_Stroop Interference_1 2
## koops, 2018_TDCS_10-20EEG_PS_TMT-A_1 2
## koops, 2018_TDCS_10-20EEG_RPS_TMT-B_1 2
## koops, 2016_CTBS_10-20EEG_P_PANSS_1 2
## koops, 2016_CTBS_10-20EEG_P_AHRS_1 2
## koops, 2016_CTBS_10-20EEG_P_PSYRATS_1 2
## kos, 2024_TDCS_10-20EEG_N_SANS_1 2
## kos, 2024_TDCS_10-20EEG_N_AES_1 2
## kumar, 2020_HF-RTMS_CM_PANSS-N_1 2
## kumar, 2020_HF-RTMS_CM_PANSS-G_1 2
## li, 2024 - a_ITBS_10-20EEG_GC_MCCB_1 2
## li, 2024 - a_ITBS_10-20EEG_WM_MCCB_1 2
## li, 2024 - a_ITBS_10-20EEG_PANSS-P_1 2
## li, 2024 - a_ITBS_10-20EEG_PANSS-N_1 2
## li, 2024 - a_ITBS_10-20EEG_PANSS-G_1 2
## li-b-lpc, 2024_ITBS_NEURONAV_PS_MCCB_1 2
## li-b-lpc, 2024_ITBS_NEURONAV_AV_MCCB_1 2
## li-b-lpc, 2024_ITBS_NEURONAV_WM_MCCB_1 2
## li-b-lpc, 2024_ITBS_NEURONAV_VerL_MCCB_1 2
## li-b-lpc, 2024_ITBS_NEURONAV_VisL_MCCB_1 2
## li-b-lpc, 2024_ITBS_NEURONAV_RPS_MCCB_1 2
## li-b-lpc, 2024_ITBS_NEURONAV_SC_MCCB_1 2
## li-b-lpc, 2024_ITBS_NEURONAV_GC_MCCB_1 2
## li-b-dlpfc, 2024_ITBS_NEURONAV_PS_MCCB_1 2
## li-b-dlpfc, 2024_ITBS_NEURONAV_AV_MCCB_1 2
## li-b-dlpfc, 2024_ITBS_NEURONAV_WM_MCCB_1 2
## li-b-dlpfc, 2024_ITBS_NEURONAV_VerL_MCCB_1 2
## li-b-dlpfc, 2024_ITBS_NEURONAV_VisL_MCCB_1 2
## li-b-dlpfc, 2024_ITBS_NEURONAV_RPS_MCCB_1 2
## li-b-dlpfc, 2024_ITBS_NEURONAV_SC_MCCB_1 2
## li-b-dlpfc, 2024_ITBS_NEURONAV_GC_MCCB_1 2
## lindenmayer, 2019_TDCS_10-20EEG_AHRS_1 2
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-T_1 2
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-P_1 2
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-N_1 2
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-G_1 2
## lindenmayer, 2019_TDCS_10-20EEG_GC_MCCB_1 2
## lindenmayer, 2019_TDCS_10-20EEG_PS_MCCB_1 2
## lindenmayer, 2019_TDCS_10-20EEG_AV_MCCB_1 2
## lindenmayer, 2019_TDCS_10-20EEG_WM_MCCB_1 2
## lindenmayer, 2019_TDCS_10-20EEG_VerL_MCCB_1 2
## lindenmayer, 2019_TDCS_10-20EEG_VisL_MCCB_1 2
## lindenmayer, 2019_TDCS_10-20EEG_RPN_MCCB_1 2
## lindenmayer, 2019_TDCS_10-20EEG_SC_MCCB_1 2
## lisoni, 2022_TDCS_10-20 EEG_PANSS-P_1 2
## lisoni, 2022_TDCS_10-20 EEG_PANSS-N_1 2
## lisoni, 2022_TDCS_10-20 EEG_PANSS-T_1 2
## lisoni, 2022_TDCS_10-20 EEG_PANSS-G_1 2
## lisoni, 2022_TDCS_10-20 EEG_GC_BACS (Composite z-scores)_1 2
## lisoni, 2022_TDCS_10-20 EEG_VerL_BACS z-scores (Verbal memory)_1 2
## lisoni, 2022_TDCS_10-20 EEG_WM_BACS z-scores (Digit sequencing)_1 2
## lisoni, 2022_TDCS_10-20 EEG_PS_BACS z-scores (Verbal fluency)_1 2
## lisoni, 2022_TDCS_10-20 EEG_PS_BACS z-scores (Symbol coding)_1 2
## lisoni, 2022_TDCS_10-20 EEG_RPS_BACS z-scores (Tower of London)_1 2
## liu, 2024_HF-RTMS_NA_T_PANSS_1 2
## liu, 2024_HF-RTMS_NA_P_PANSS_1 2
## liu, 2024_HF-RTMS_NA_N_PANSS_1 2
## liu, 2024_HF-RTMS_NA_G_PANSS_1 2
## liu, 2024_HF-RTMS_NA_VerL_RBANS (Immediate memory)_1 2
## liu, 2024_HF-RTMS_NA_VisL_RBANS (Visual spatial structure)_1 2
## liu, 2024_HF-RTMS_NA_PS_RBANS (Speech function)_1 2
## liu, 2024_HF-RTMS_NA_WM_RBANS (Attention)_1 2
## liu, 2024_HF-RTMS_NA_Visl_RBANS (Delayed memory)_1 2
## lyu, 2024_TDCS_10-20EEG_T_PANSS_1 2
## lyu, 2024_TDCS_10-20EEG_P_PANSS_1 2
## lyu, 2024_TDCS_10-20EEG_N_PANSS_1 2
## lyu, 2024_TDCS_10-20EEG_G_PANSS_1 2
## lyu, 2024_TDCS_10-20EEG_N_SANS_1 2
## mao, 2023_HF-RTMS_CM_GC_RBANS_1 2
## mao, 2023_HF-RTMS_CM_VerL_RBANS-Immediate Memory_1 2
## mao, 2023_HF-RTMS_CM_RBANS-Visuospatial_1 2
## mao, 2023_HF-RTMS_CM_VerL_RBANS-Language_1 2
## mao, 2023_HF-RTMS_CM_WM_RBANS-Attention_1 2
## mao, 2023_HF-RTMS_CM_VerL_RBANS-Delayed memory_1 2
## mao, 2023_HF-RTMS_CM_P_AHRS_1 2
## mao, 2023_HF-RTMS_CM_T_PANSS_1 2
## marquardt, 2022_TDCS_10-20EEG_P_PANSS_1 2
## marquardt, 2022_TDCS_10-20EEG_N_PANSS_1 2
## marquardt, 2022_TDCS_10-20EEG_P_AHRS_1 2
## marquardt, 2022_TDCS_10-20EEG_RPS_Stroop 3 (s/RT)_1 2
## marquardt, 2022_TDCS_10-20EEG_RPS_Stroop 4 (s/RT)_1 2
## marquardt, 2022_TDCS_10-20EEG_PS_TMT-A_1 2
## marquardt, 2022_TDCS_10-20EEG_RPS_TMT-B_1 2
## mcintosh, 2004_LF-RTMS_10-20EEG_P_PANSS_1 2
## mcintosh, 2004_LF-RTMS_10-20EEG_N_PANSS_1 2
## mcintosh, 2004_LF-RTMS_10-20EEG_VerL_AVLT_1 2
## meiron, 2021_TDCS_10-20EEG_T_PANSS_1 2
## meiron, 2021_TDCS_10-20EEG_WM_(verbal) WM - Accuracy_1 2
## meiron, 2021_TDCS_10-20EEG_WM_(verbal) WM - RT_1 2
## meiron, 2024_TDCS_10-20EEG_T_PANSS_1 2
## meiron, 2024_TDCS_10-20EEG_WM_2-BACK Acc_1 2
## meiron, 2024_TDCS_10-20EEG_WM_2-BACK RT_1 2
## mellin-tacs, 2018_TACS_10-20EEG_P_AHRS_1 2
## mellin-tacs, 2018_TACS_10-20EEG_T_PANSS-T_1 2
## mellin-tacs, 2018_TACS_10-20EEG_P_PANSS-P_1 2
## mellin-tacs, 2018_TACS_10-20EEG_N_PANSS-N_1 2
## mellin-tacs, 2018_TACS_10-20EEG_G_PANSS-G_1 2
## mellin-tacs, 2018_TACS_10-20EEG_GC_BACS_1 2
## mellin-tdcs, 2018_TDCS_10-20EEG_P_AHRS_1 2
## mellin-tdcs, 2018_TDCS_10-20EEG_T_PANSS_1 2
## mellin-tdcs, 2018_TDCS_10-20EEG_P_PANSS_1 2
## mellin-tdcs, 2018_TDCS_10-20EEG_N_PANSS_1 2
## mellin-tdcs, 2018_TDCS_10-20EEG_G_PANSS_1 2
## mellin-tdcs, 2018_TDCS_10-20EEG_GC_BACS_1 2
## moeller, 2022_DTMS_CM_T_PANSS_1 2
## moeller, 2022_DTMS_CM_P_PANSS_1 2
## moeller, 2022_DTMS_CM_N_PANSS_1 2
## mogg, 2007_HF-RTMS_CM_VerL_HVLT immediate recall_1 2
## mogg, 2007_HF-RTMS_CM_VerL_HVLT delayed recall_1 2
## mogg, 2007_HF-RTMS_CM_PS_COWAT (number)_1 2
## mogg, 2007_HF-RTMS_CM_RPS_Stroop RT (seconds)_1 2
## mondino, 2015_TDCS_10-20EG_P_PANSS_1 2
## mondino, 2015_TDCS_10-20EG_N_PANSS_1 2
## mondino, 2015_TDCS_10-20EG_G_PANSS_1 2
## mondino, 2015_TDCS_10-20EG_P_AHRS_1 2
## novak, 2006_HF-RTMS_CM_T_PANSS_1 2
## novak, 2006_HF-RTMS_CM_P_PANSS_1 2
## novak, 2006_HF-RTMS_CM_N_PANSS_1 2
## novak, 2006_HF-RTMS_CM_G_PANSS_1 2
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_SAPS_1 2
## paillere-martinot, 2017_LF-RTMS_NEURONAV_N_SANS_1 2
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_AHRS_1 2
## palm, 2016_TDCS_10-20EEG_T_PANSS_1 2
## palm, 2016_TDCS_10-20EEG_P_PANSS_1 2
## palm, 2016_TDCS_10-20EEG_N_PANSS_1 2
## palm, 2016_TDCS_10-20EEG_N_SANS_1 2
## palm, 2016_TDCS_10-20EEG_WM_SOPT_1 2
## palm, 2016_TDCS_10-20EEG_PS_TMT-A_1 2
## palm, 2016_TDCS_10-20EEG_RPS_TMT-B_1 2
## prikryl, 2007_HF-RTMS_CM_T_PANSS_1 2
## prikryl, 2007_HF-RTMS_CM_P_PANSS_1 2
## prikryl, 2007_HF-RTMS_CM_N_PANSS_1 2
## prikryl, 2007_HF-RTMS_CM_N_SANS_1 2
## prikryl, 2007_HF-RTMS_CM_P_SAPS_1 2
## prikryl, 2012_HF-RTMS_CM_P_PANSS_1 2
## prikryl, 2012_HF-RTMS_CM_N_PANSS_1 2
## prikryl, 2012_HF-RTMS_CM_G_PANSS_1 2
## prikryl, 2012_HF-RTMS_CM_T_PANSS_1 2
## prikryl, 2012_HF-RTMS_CM_PS_VFT_1 2
## prikryl, 2014_HF-RTMS_CM_T_PANSS_1 2
## prikryl, 2014_HF-RTMS_CM_P_PANSS_1 2
## prikryl, 2014_HF-RTMS_CM_N_PANSS_1 2
## prikryl, 2014_HF-RTMS_CM_G_PANSS_1 2
## prikryl, 2013_HF-RTMS_CM_N_SANS_1 2
## prikryl, 2013_HF-RTMS_CM_P_SAPS_1 2
## quan, 2015_HF-RTMS_CM_T_PANSS_1 2
## quan, 2015_HF-RTMS_CM_P_PANSS_1 2
## quan, 2015_HF-RTMS_CM_N_PANSS_1 2
## quan, 2015_HF-RTMS_CM_G_PANSS_1 2
## quan, 2015_HF-RTMS_CM_N_SANS_1 2
## rabany, 2014_DTMS_CM_T_PANSS_1 2
## rabany, 2014_DTMS_CM_N_PANSS_1 2
## rabany, 2014_DTMS_CM_N_SANS_1 2
## rabany, 2014_DTMS_CM_AV_RVP-A_1 2
## rabany, 2014_DTMS_CM_AV_RVP-B_1 2
## rabany, 2014_DTMS_CM_WM_SWM (Total between search errors)_1 2
## rabany, 2014_DTMS_CM_WM_SWM (Strategy score)_1 2
## rabany, 2014_DTMS_CM_RPS_SOC (Minimum move solutions for test trials)_1 2
## rabany, 2014_DTMS_CM_RPS_SOC (Initial times for 5 move problems)_1 2
## rabany, 2014_DTMS_CM_RPS_SOC (Subsequent times for 5 move problems)_1 2
## rabany, 2014_DTMS_CM_PS_RTI (Mean reaction time, stages 4 and 5)_1 2
## rabany, 2014_DTMS_CM_PS_RTI (Mean movement time, stages 4 and 5)_1 2
## rollnik, 2000_HF-RTMS_CM_T_BPRS_1 2
## rollnik, 2000_HF-RTMS_CM_PS_NCT (seconds)_1 2
## rosa, 2007_LF-RTMS_10-20EEG_T_PANSS_1 2
## rosa, 2007_LF-RTMS_10-20EEG_P_PANSS_1 2
## rosa, 2007_LF-RTMS_10-20EEG_N_PANSS_1 2
## rosa, 2007_LF-RTMS_10-20EEG_G_PANSS_1 2
## rosenberg, 2012_LF-RTMS_CM_P_AHRS_1 2
## saba, 2006_LF-RTMS_CM_T_PANSS_1 2
## saba, 2006_LF-RTMS_CM_P_PANSS_1 2
## saba, 2006_LF-RTMS_CM_N_PANSS_1 2
## saba, 2006_LF-RTMS_CM_G_PANSS_1 2
## schilling, 2021_TDCS_10-20EEG_WM_Verbal Working Memory Reaction Time (t-score)_1 2
## schilling, 2021_TDCS_10-20EEG_WM_Verbal Working Memory d-prime (z-score)_1 2
## schilling, 2021_TDCS_10-20EEG_RPS_Response Inhibition Reaction Time (t-score)_1 2
## schilling, 2021_TDCS_10-20EEG_RPS_Response Inhibition Errors (t-scores)_1 2
## schilling, 2021_TDCS_10-20EEG_RPS_Problem solving t-score_1 2
## schilling, 2021_TDCS_10-20EEG_RPS_Mental Flexibility Speed (t-score)_1 2
## schilling, 2021_TDCS_10-20EEG_RPS_Mental Flexibility Accuracy (t-score)_1 2
## singh, 2020_HF-RTMS_CM_P_PANSS_1 2
## singh, 2020_HF-RTMS_CM_N_PANSS_1 2
## singh, 2020_HF-RTMS_CM_N_SANS_1 2
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_AHRS_1 2
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_PANSS_1 2
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_AHRS_1 2
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_PANSS_1 2
## smith, 2015_TDCS_10-20EEG_GC_MCCB_1 2
## smith, 2015_TDCS_10-20EEG_WM_MCCB_1 2
## smith, 2015_TDCS_10-20EEG_AV_MCCB_1 2
## smith, 2015_TDCS_10-20EEG_RPS_MCCB_1 2
## smith, 2015_TDCS_10-20EEG_VerL_MCCB_1 2
## smith, 2015_TDCS_10-20EEG_VisL_MCCB_1 2
## smith, 2015_TDCS_10-20EEG_PS_MCCB_1 2
## smith, 2015_TDCS_10-20EEG_SC_MCCB_1 2
## smith, 2015_TDCS_10-20EEG_T_PANSS_1 2
## smith, 2015_TDCS_10-20EEG_P_PANSS_1 2
## smith, 2015_TDCS_10-20EEG_N_PANSS_1 2
## smith, 2015_TDCS_10-20EEG_G_PANSS_1 2
## smith, 2020_TDCS_10-20EEG_GC_MCCB_1 2
## smith, 2020_TDCS_10-20EEG_PS_MCCB_1 2
## smith, 2020_TDCS_10-20EEG_AV_MCCB_1 2
## smith, 2020_TDCS_10-20EEG_WM_MCCB_1 2
## smith, 2020_TDCS_10-20EEG_VerL_MCCB_1 2
## smith, 2020_TDCS_10-20EEG_VisL_MCCB_1 2
## smith, 2020_TDCS_10-20EEG_RPS_MCCB_1 2
## smith, 2020_TDCS_10-20EEG_SC_MCCB_1 2
## smith, 2020_TDCS_10-20EEG_AV_PASAT (Number Correct)_1 2
## smith, 2020_TDCS_10-20EEG_T_PANSS_1 2
## smith, 2020_TDCS_10-20EEG_P_PANSS_1 2
## smith, 2020_TDCS_10-20EEG_N_PANSS_1 2
## su, 2023b_HF-RTMS_NEURONAV_T_PANSS_1 2
## su, 2023b_HF-RTMS_NEURONAV_P_PANSS_1 2
## su, 2023b_HF-RTMS_NEURONAV_N_PANSS_1 2
## su, 2023b_HF-RTMS_NEURONAV_G_PANSS_1 2
## su, 2022_HF-RTMS_NEURONAV_T_PANSS_1 2
## su, 2022_HF-RTMS_NEURONAV_P_PANSS_1 2
## su, 2022_HF-RTMS_NEURONAV_N_PANSS_1 2
## su, 2022_HF-RTMS_NEURONAV_G_PANSS_1 2
## tikka, 2017_CTBS_NEURONAV_P_PANSS_1 2
## tikka, 2017_CTBS_NEURONAV_N_PANSS_1 2
## tikka, 2017_CTBS_NEURONAV_G_PANSS_1 2
## tikka, 2017_CTBS_NEURONAV_T_PANSS_1 2
## tikka, 2017_CTBS_NEURONAV_RPS_Self-Monitoring Task_1 2
## tikka, 2017_CTBS_NEURONAV_WM_Visual Memory Task_1 2
## tyagi, 2022_CTBS_10-20EEG_P_PANSS_1 2
## tyagi, 2022_CTBS_10-20EEG_N_PANSS_1 2
## tyagi, 2022_CTBS_10-20EEG_T_PANSS_1 2
## tyagi, 2022_CTBS_10-20EEG_G_PANSS_1 2
## tyagi, 2022_CTBS_10-20EEG_P_AVHRS_1 2
## tyagi, 2022_CTBS_10-20EEG_P_PSYRAT-AH_1 2
## valiengo, 2020_TDCS_10-20EEG_N_PANSS_1 2
## valiengo, 2020_TDCS_10-20EEG_P_PANSS_1 2
## valiengo, 2020_TDCS_10-20EEG_T_PANSS_1 2
## valiengo, 2020_TDCS_10-20EEG_G_PANSS_1 2
## valiengo, 2020_TDCS_10-20EEG_P_AVHRS_1 2
## vercammen, 2011_TDCS_10-20EEG_RPS_Weather Prediction Test_1 2
## vergallito, 2024_ITBS_10-20EEG_T_PANSS_1 2
## vergallito, 2024_ITBS_10-20EEG_P_PANSS_1 2
## vergallito, 2024_ITBS_10-20EEG_N_PANSS_1 2
## vergallito, 2024_ITBS_10-20EEG_N_BNSS_1 2
## vergallito, 2024_ITBS_10-20EEG_GC_MCCB_1 2
## vergallito, 2024_ITBS_10-20EEG_PS_MCCB_1 2
## vergallito, 2024_ITBS_10-20EEG_AV_MCCB_1 2
## vergallito, 2024_ITBS_10-20EEG_WM_MCCB_1 2
## vergallito, 2024_ITBS_10-20EEG_VerL_MCCB_1 2
## vergallito, 2024_ITBS_10-20EEG_VisL_MCCB_1 2
## vergallito, 2024_ITBS_10-20EEG_RPS_MCCB_1 2
## vergallito, 2024_ITBS_10-20EEG_SC_MCCB_1 2
## walther-lft, 2024_UNKNOWN_STANDARD_T_PANSS_1 2
## walther-lft, 2024_UNKNOWN_STANDARD_P_PANSS_1 2
## walther-lft, 2024_UNKNOWN_STANDARD_N_PANSS_1 2
## walther-lft, 2024_UNKNOWN_STANDARD_G_PANSS_1 2
## walther-lft, 2024_UNKNOWN_STANDARD_N_BNSS_1 2
## walther-itbs, 2024_ITBS_CM_T_PANSS_1 2
## walther-itbs, 2024_ITBS_CM_P_PANSS_1 2
## walther-itbs, 2024_ITBS_CM_N_PANSS_1 2
## walther-itbs, 2024_ITBS_CM_G_PANSS_1 2
## walther-itbs, 2024_ITBS_CM_N_BNSS_1 2
## wang, 2020_ITBS_NEURONAV_T_PANSS_1 2
## wang, 2020_ITBS_NEURONAV_P_PANSS_1 2
## wang, 2020_ITBS_NEURONAV_N_PANSS_1 2
## wang, 2020_ITBS_NEURONAV_G_PANSS_1 2
## wang, 2020_ITBS_NEURONAV_P_SAPS_1 2
## wang, 2020_ITBS_NEURONAV_N_SANS_1 2
## wang, 2020_ITBS_NEURONAV_GC_MoCA_1 2
## wang, 2020_ITBS_NEURONAV_PS_VFT_1 2
## wang, 2020_ITBS_NEURONAV_WM_Digit span (forward)_1 2
## wang, 2020_ITBS_NEURONAV_WM_Digit span (backward)_1 2
## wang, 2020_ITBS_NEURONAV_RPS_Stroop Color Test_1 2
## wang, 2020_ITBS_NEURONAV_RPS_Stroop Word Test_1 2
## wang, 2020_ITBS_NEURONAV_RPS_Stroop Interference Test_1 2
## wang, 2020_ITBS_NEURONAV_PS_TMT-A_1 2
## wang, 2020_ITBS_NEURONAV_RPS_TMT-B_1 2
## wang, 2022_ITBS_NEURONAV_P_PANSS_1 2
## wang, 2022_ITBS_NEURONAV_N_PANSS_1 2
## wang, 2022_ITBS_NEURONAV_G_PANSS_1 2
## wang, 2022_ITBS_NEURONAV_T_PANSS_1 2
## wang, 2022_ITBS_NEURONAV_P_SAPS_1 2
## wang, 2022_ITBS_NEURONAV_N_SANS_1 2
## wang, 2022_ITBS_NEURONAV_GC_MoCA_1 2
## wang, 2022_ITBS_NEURONAV_WM_3-back RT_1 2
## weickert, 2019_TDCS_10-20EEG_T_PANSS_1 2
## weickert, 2019_TDCS_10-20EEG_P_PANSS_1 2
## weickert, 2019_TDCS_10-20EEG_N_PANSS_1 2
## weickert, 2019_TDCS_10-20EEG_G_PANSS_1 2
## weickert, 2019_TDCS_10-20EEG_P_AHRS_1 2
## weickert, 2019_TDCS_10-20EEG_PS_BACS sc_1 2
## weickert, 2019_TDCS_10-20EEG_PS_TMT-A_1 2
## weickert, 2019_TDCS_10-20EEG_WM_LNS_1 2
## weickert, 2019_TDCS_10-20EEG_VerL_HVLTr_1 2
## weickert, 2019_TDCS_10-20EEG_VisL_BVMT_1 2
## weickert, 2019_TDCS_10-20EEG_RPS_NAB maze_1 2
## weickert, 2019_TDCS_10-20EEG_PS_fluency_1 2
## wen, 2021_HF-RTMS_CM_T_PANSS_1 2
## wen, 2021_HF-RTMS_CM_P_PANSS_1 2
## wen, 2021_HF-RTMS_CM_N_PANSS_1 2
## wen, 2021_HF-RTMS_CM_G_PANSS_1 2
## wen, 2021_HF-RTMS_CM_GC_RBANS-T_1 2
## wen, 2021_HF-RTMS_CM_VerL_RBANS\r\nImmediate memory_1 2
## wen, 2021_HF-RTMS_CM_WM_RBANS\r\nAttention_1 2
## wen, 2021_HF-RTMS_CM_VisL_RBANS\r\nVisuospatial_1 2
## wen, 2021_HF-RTMS_CM_VisL_RBANS\r\nDelayed memory_1 2
## wen, 2021_HF-RTMS_CM_VerL_RBANS\r\nLanguage_1 2
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n1 word (s)_1 2
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n2 word (s)_1 2
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n3 word (s)_1 2
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n3 color (s)_1 2
## wobrock, 2015_HF-RTMS_10-20EEG_T_PANSS_1 2
## wobrock, 2015_HF-RTMS_10-20EEG_P_PANSS_1 2
## wobrock, 2015_HF-RTMS_10-20EEG_N_PANSS_1 2
## xie, 2023-a_LF-RTMS_10-20EEG_T_PANSS_1 2
## xie, 2023-a_LF-RTMS_10-20EEG_P_PANSS_1 2
## xie, 2023-a_LF-RTMS_10-20EEG_N_PANSS_1 2
## xie, 2023-a_LF-RTMS_10-20EEG_G_PANSS_1 2
## xie, 2023-a_LF-RTMS_10-20EEG_P_AHRS_1 2
## xiu-10hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 2
## xiu-10hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 2
## xiu-10hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 2
## xiu-10hz, 2020_HF-RTMS_NEURONAV_G_PANSS_1 2
## xiu-10hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 2
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nImmediate memory_1 2
## xiu-10hz, 2020_HF-RTMS_NEURONAV_WM_RBANS\r\nAttention_1 2
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nVisuospatial_1 2
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nDelayed memory_1 2
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nLanguage_1 2
## xiu-20hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 2
## xiu-20hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 2
## xiu-20hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 2
## xiu-20hz, 2020_HF-RTMS_NEURONAV_G_PANSS_1 2
## xiu-20hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 2
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nImmediate memory_1 2
## xiu-20hz, 2020_HF-RTMS_NEURONAV_WM_RBANS\r\nAttention_1 2
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nVisuospatial_1 2
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nDelayed memory_1 2
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nLanguage_1 2
## xu, 2023_HD-TDCS_10-20EEG_T_PANSS_1 2
## xu, 2023_HD-TDCS_10-20EEG_P_PANSS_1 2
## xu, 2023_HD-TDCS_10-20EEG_N_PANSS_1 2
## xu, 2023_HD-TDCS_10-20EEG_G_PANSS_1 2
## xu, 2023_HD-TDCS_10-20EEG_GC_RBANS_1 2
## ye-20hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 2
## ye-20hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Immediate memory_1 2
## ye-20hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Visuospatial_1 2
## ye-20hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Language_1 2
## ye-20hz, 2024_HF-RTMS_NEURONAV_WM_RBANS - Attention_1 2
## ye-20hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Delayed memory_1 2
## ye-10hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 2
## ye-10hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Immediate memory_1 2
## ye-10hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Visuospatial_1 2
## ye-10hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Language_1 2
## ye-10hz, 2024_HF-RTMS_NEURONAV_WM_RBANS - Attention_1 2
## ye-10hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Delayed memory_1 2
## yuanjun, 2024_LF-RTMS_10-20EEG_T_PANSS_1 2
## yuanjun, 2024_LF-RTMS_10-20EEG_P_PANSS_1 2
## yuanjun, 2024_LF-RTMS_10-20EEG_N_PANSS_1 2
## yuanjun, 2024_LF-RTMS_10-20EEG_G_PANSS_1 2
## yuanjun, 2024_LF-RTMS_10-20EEG_P_AHRS_1 2
## zhai-a, 2023_HF-RTMS_NA_T_PANSS_1 2
## zhang, 2022_TACS_10-20EEG_T_PANSS_1 2
## zhang, 2022_TACS_10-20EEG_P_PANSS_1 2
## zhang, 2022_TACS_10-20EEG_N_PANSS_1 2
## zhang, 2022_TACS_10-20EEG_P_AHRS_1 2
## zhao-tbs, 2014_ITBS_10-20EEG_T_PANSS_1 2
## zhao-tbs, 2014_ITBS_10-20EEG_P_PANSS_1 2
## zhao-tbs, 2014_ITBS_10-20EEG_N_PANSS_1 2
## zhao-tbs, 2014_ITBS_10-20EEG_G_PANSS_1 2
## zhao-tbs, 2014_ITBS_10-20EEG_N_SANS_1 2
## zhao-20hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 2
## zhao-20hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 2
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 2
## zhao-20hz, 2014_HF-RTMS_10-20EEG_G_PANSS_1 2
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 2
## zhao-10hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 2
## zhao-10hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 2
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 2
## zhao-10hz, 2014_HF-RTMS_10-20EEG_G_PANSS_1 2
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 2
## zhou, 2024_HF-RTMS_10-20EEG_P_PANSS_1 2
## zhou, 2024_HF-RTMS_10-20EEG_N_PANSS_1 2
## zhou, 2024_HF-RTMS_10-20EEG_T_PANSS_1 2
## zhou, 2024_HF-RTMS_10-20EEG_G_PANSS_1 2
## zhou, 2024_HF-RTMS_10-20EEG_GC_RBANS-T_1 2
## zhou, 2024_HF-RTMS_10-20EEG_VerL_RBANS\r\nImmediate memory_1 2
## zhou, 2024_HF-RTMS_10-20EEG_VisL_RBANS\r\nVisuospatial_1 2
## zhou, 2024_HF-RTMS_10-20EEG_VerL_RBANS\r\nLanguage_1 2
## zhou, 2024_HF-RTMS_10-20EEG_WM_RBANS\r\nAttention_1 2
## zhou, 2024_HF-RTMS_10-20EEG_VisL_RBANS\r\nDelayed memory_1 2
## zhou, 2024_HF-RTMS_10-20EEG_RPS_SCWT \r\nInference scores_1 2
## zhou, 2023_TDCS_10-20EEG_T_PANSS_1 2
## zhou, 2023_TDCS_10-20EEG_N_SANS_1 2
## zhou, 2023_TDCS_10-20EEG_RPS_IED total errors_1 2
## zhu, 2021_ITBS_CM_N_PANSS_1 2
## zhuo, 2019_HF-RTMS_10-20EEG_T_PANSS_1 2
## zhuo, 2019_HF-RTMS_10-20EEG_P_PANSS_1 2
## zhuo, 2019_HF-RTMS_10-20EEG_N_PANSS_1 2
## zhuo, 2019_HF-RTMS_10-20EEG_G_PANSS_1 2
## zhuo, 2019_HF-RTMS_10-20EEG_N_SANS_1 2
## zhuo, 2019_HF-RTMS_10-20EEG_PS_MCCB TMT-A_1 2
## zhuo, 2019_HF-RTMS_10-20EEG_PS_MCCB BACS_1 2
## zhuo, 2019_HF-RTMS_10-20EEG_PS_MCCB Fluency_1 2
## zhuo, 2019_HF-RTMS_10-20EEG_WM_MCCB Working memory (WMS-SS)_1 2
## zhuo, 2019_HF-RTMS_10-20EEG_VerL_MCCB Verbal learning (HVLT-R)_1 2
## zhuo, 2019_HF-RTMS_10-20EEG_VisL_MCCB Visual learning (BVMT-R)_1 2
## zhuo, 2019_HF-RTMS_10-20EEG_RPS_MCCB Reasoning/problem solving (NAB)_1 2
## zhuo, 2019_HF-RTMS_10-20EEG_SC_MCCB Social cognition (MSCEIT)_1 2
## zhuo, 2019_HF-RTMS_10-20EEG_GC_MCCB Composite score_1 2
##
## Results (random effects model):
##
## treat1
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## bais, 2014 - l_LF-RTMS_10-20EEG_G_PANSS_1 LF-RTMS_10-20EEG
## bais, 2014 - l_LF-RTMS_10-20EEG_P_AHRS_1 LF-RTMS_10-20EEG
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANAS_1 LF-RTMS_10-20EEG
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANAS_1 LF-RTMS_10-20EEG
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## bais, 2014 - bi_LF-RTMS_10-20EEG_G_PANSS_1 LF-RTMS_10-20EEG
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_AHRS_1 LF-RTMS_10-20EEG
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANAS_1 LF-RTMS_10-20EEG
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANAS_1 LF-RTMS_10-20EEG
## barr, 2011_HF-RTMS_NEURONAV_WM_1-back RT ms_1 HF-RTMS_NEURONAV
## barr, 2011_HF-RTMS_NEURONAV_WM_2-back RT ms_1 HF-RTMS_NEURONAV
## barr, 2011_HF-RTMS_NEURONAV_WM_3-back RT ms_1 HF-RTMS_NEURONAV
## barr, 2013_HF-RTMS_NEURONAV_WM_1-back RT ms Target Correct_1 HF-RTMS_NEURONAV
## barr, 2013_HF-RTMS_NEURONAV_WM_1-back RT ms Non Target Correct_1 HF-RTMS_NEURONAV
## barr, 2013_HF-RTMS_NEURONAV_WM_3-back RT ms Target Correct_1 HF-RTMS_NEURONAV
## barr, 2013_HF-RTMS_NEURONAV_WM_3-back RT ms Non Target Correct_1 HF-RTMS_NEURONAV
## barr, 2012_HF-RTMS_NEURONAV_P_PANSS_1 HF-RTMS_NEURONAV
## barr, 2012_HF-RTMS_NEURONAV_N_PANSS_1 HF-RTMS_NEURONAV
## barr, 2012_HF-RTMS_NEURONAV_N_SANS_1 HF-RTMS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_N_SANS_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_P_SAPS_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_VerL_AVLT Hits_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_VisL_CFT copying_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_VisL_CFT Immediate Recall_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_VisL_CFT Delayed Recall_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_PS_DSST time (sec)_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_PS_DSST errors_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_AV_DVT time (sec)_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-A time (sec)_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-A errors_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-B time (sec)_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-B errors_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_WM_1back verbal Hits_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_WM_1back verbal Errors_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_WM_2back verbal Hits_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_WM_2back verbal Errors_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_WM_Spatial Span total_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_RPS_FAS_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_RPS_Stroop Effect score_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_SC_FOT index_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_SC_SOT index_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_SC_Faux Pax CI_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_SC_Personalizing Bias Index_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_SC_Social Perception Index_1 ITBS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_SC_Emotion Recognition Index_1 ITBS_NEURONAV
## battion, 2021_ITBS_CM_T_PANSS_1 ITBS_CM
## battion, 2021_ITBS_CM_N_SANS_1 ITBS_CM
## blumberger, 2012_LF-RTMS_NEURONAV_P_PSYRATS_1 LF-RTMS_NEURONAV
## blumberger, 2012_LF-RTMS_NEURONAV_T_PANSS_1 LF-RTMS_NEURONAV
## blumberger, 2012_LF-RTMS_NEURONAV_P_PANSS_1 LF-RTMS_NEURONAV
## blumberger, 2012_LF-RTMS_NEURONAV_P_AHRS_1 LF-RTMS_NEURONAV
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PSYRATS_1 PRM-RTMS_NEURONAV
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_T_PANSS_1 PRM-RTMS_NEURONAV
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PANSS_1 PRM-RTMS_NEURONAV
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_AHRS_1 PRM-RTMS_NEURONAV
## bodén, 2021_ITBS_CM_N_CAIN_1 ITBS_CM
## bose, 2018_TDCS_10-20EEG_P_SAPS_1 SHAM
## bose, 2018_TDCS_10-20EEG_N_SANS_1 SHAM
## bose, 2018_TDCS_10-20EEG_P_AHRS_1 SHAM
## brunelin, 2012_TDCS_10-20EEG_P_AHRS_1 SHAM
## brunelin, 2012_TDCS_10-20EEG_T_PANSS_1 SHAM
## brunelin, 2006_LF-RTMS_10-20EEG_P_AHRS_1 LF-RTMS_10-20EEG
## brunelin, 2006_LF-RTMS_10-20EEG_P_SAPS_1 LF-RTMS_10-20EEG
## brunelin, 2006_LF-RTMS_10-20EEG_WM_MonitorSourceTask_1 LF-RTMS_10-20EEG
## bulubas, 2021_TDCS_10-20EEG_VisL_PFMT Total Correct Responses_1 SHAM
## bulubas, 2021_TDCS_10-20EEG_VerL_PWMT Total Correct Responses_1 SHAM
## bulubas, 2021_TDCS_10-20EEG_SC_EMI Correct Responses_1 SHAM
## bulubas, 2021_TDCS_10-20EEG_WM_PLNB 0-back True Positive Responses_1 SHAM
## bulubas, 2021_TDCS_10-20EEG_WM_PLNB 1-back True Positive Responses_1 SHAM
## bulubas, 2021_TDCS_10-20EEG_WM_PLNB 2-back True Positive Responses_1 SHAM
## bulubas, 2021_TDCS_10-20EEG_RPS_PCET Number Correct Responses_1 SHAM
## bulubas, 2021_TDCS_10-20EEG_VisL_Short VOLT Total Correct_1 SHAM
## chang-a, 2021_TACS_10-20EEG_T_PANSS_1 SHAM
## chang-a, 2021_TACS_10-20EEG_N_PANSS_1 SHAM
## chang-a, 2021_TACS_10-20EEG_N_SANS_1 SHAM
## chauhan, 2021_ITBS_10-20EEG_P_PANSS_1 ITBS_10-20EEG
## chauhan, 2021_ITBS_10-20EEG_N_PANSS_1 ITBS_10-20EEG
## chauhan, 2021_ITBS_10-20EEG_G_PANSS_1 ITBS_10-20EEG
## chauhan, 2021_ITBS_10-20EEG_T_PANSS_1 ITBS_10-20EEG
## chauhan, 2021_ITBS_10-20EEG_T_BPRS_1 ITBS_10-20EEG
## de jesus, 2011_LF-RTMS_10-20EEG_T_BPRS_1 LF-RTMS_10-20EEG
## de jesus, 2011_LF-RTMS_10-20EEG_P_BPRS_1 LF-RTMS_10-20EEG
## de jesus, 2011_LF-RTMS_10-20EEG_N_BPRS_1 LF-RTMS_10-20EEG
## de jesus, 2011_LF-RTMS_10-20EEG_P_AHRS_1 LF-RTMS_10-20EEG
## dharani, 2021_HD-TDCS_10-10EEG_P_PANSS_1 HD-TDCS_10-10EEG
## dharani, 2021_HD-TDCS_10-10EEG_N_PANSS_1 HD-TDCS_10-10EEG
## dharani, 2021_HD-TDCS_10-10EEG_G_PANSS_1 HD-TDCS_10-10EEG
## dharani, 2021_HD-TDCS_10-10EEG_N_SANS_1 HD-TDCS_10-10EEG
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_SANS_1 LF-RTMS_10-20EEG
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_G_PANSS_1 LF-RTMS_10-20EEG
## dolfus, 2018_HF-RTMS_NEURONAV_P_AHRS_1 HF-RTMS_NEURONAV
## du, 2024_HF-RTMS_NEURONAV_T_BPRS_1 HF-RTMS_NEURONAV
## du, 2024_HF-RTMS_NEURONAV_P_BPRS_1 HF-RTMS_NEURONAV
## du, 2024_HF-RTMS_NEURONAV_N_BPRS_1 HF-RTMS_NEURONAV
## du, 2022_HF-RTMS_10-20EEG_VisL_PRM number correct_1 HF-RTMS_10-20EEG
## du, 2022_HF-RTMS_10-20EEG_N_SANS_1 HF-RTMS_10-20EEG
## du, 2022_HF-RTMS_10-20EEG_T_PANSS_1 HF-RTMS_10-20EEG
## du, 2022_HF-RTMS_10-20EEG_P_PANSS_1 HF-RTMS_10-20EEG
## du, 2022_HF-RTMS_10-20EEG_N_PANSS_1 HF-RTMS_10-20EEG
## du, 2022_HF-RTMS_10-20EEG_G_PANSS_1 HF-RTMS_10-20EEG
## farhang, 2024_TDCS_10-20EEG_WM_ letter-number sequencing_1 SHAM
## fitzerald, 2008_LF-RTMS_CM_N_SANS_1 LF-RTMS_CM
## fitzerald, 2008_LF-RTMS_CM_P_PANSS_1 LF-RTMS_CM
## fitzerald, 2008_LF-RTMS_CM_N_PANSS_1 LF-RTMS_CM
## fitzerald, 2008_LF-RTMS_CM_T_PANSS_1 LF-RTMS_CM
## fitzerald-l, 2014_TDCS_10-20EEG_P_PANSS_1 SHAM
## fitzerald-l, 2014_TDCS_10-20EEG_N_PANSS_1 SHAM
## fitzerald-l, 2014_TDCS_10-20EEG_T_PANSS_1 SHAM
## fitzerald-l, 2014_TDCS_10-20EEG_N_SANS_1 SHAM
## fitzerald-bi, 2014_TDCS_10-20EEG_P_PANSS_1 SHAM
## fitzerald-bi, 2014_TDCS_10-20EEG_N_PANSS_1 SHAM
## fitzerald-bi, 2014_TDCS_10-20EEG_T_PANSS_1 SHAM
## fitzerald-bi, 2014_TDCS_10-20EEG_N_SANS_1 SHAM
## francis, 2019_HF-RTMS_CM_VerL_BACS Verbal Memory_1 HF-RTMS_CM
## francis, 2019_HF-RTMS_CM_WM_BACS Digit Sequencing_1 HF-RTMS_CM
## francis, 2019_HF-RTMS_CM_PS_BACS Semantic and Letter Fluency_1 HF-RTMS_CM
## francis, 2019_HF-RTMS_CM_PS_BACS Symbol Coding_1 HF-RTMS_CM
## francis, 2019_HF-RTMS_CM_RPS_BACS Tower of London_1 HF-RTMS_CM
## francis, 2019_HF-RTMS_CM_GC_BACS Composite Score_1 HF-RTMS_CM
## frohlich, 2016_TDCS_10-20EEG_P_AHRS_1 SHAM
## frohlich, 2016_TDCS_10-20EEG_T_PANSS_1 SHAM
## frohlich, 2016_TDCS_10-20EEG_P_PANSS_1 SHAM
## frohlich, 2016_TDCS_10-20EEG_N_PANSS_1 SHAM
## frohlich, 2016_TDCS_10-20EEG_G_PANSS_1 SHAM
## gao, 2024_ITBS_10-20EEG_P_PANSS_1 ITBS_10-20EEG
## gao, 2024_ITBS_10-20EEG_N_PANSS_1 ITBS_10-20EEG
## gao, 2024_ITBS_10-20EEG_G_PANSS_1 ITBS_10-20EEG
## gao, 2024_ITBS_10-20EEG_T_PANSS_1 ITBS_10-20EEG
## gao, 2024_ITBS_10-20EEG_N_SANS_1 ITBS_10-20EEG
## garcía-fernández, 2024_TDCS_10-20EEG_PS_MCCB_1 SHAM
## garcía-fernández, 2024_TDCS_10-20EEG_AV_MCCB_1 SHAM
## garcía-fernández, 2024_TDCS_10-20EEG_WM_MCCB_1 SHAM
## garcía-fernández, 2024_TDCS_10-20EEG_VerL_MCCB_1 SHAM
## garcía-fernández, 2024_TDCS_10-20EEG_VisL_MCCB_1 SHAM
## garcía-fernández, 2024_TDCS_10-20EEG_RPS_MCCB_1 SHAM
## garcía-fernández, 2024_TDCS_10-20EEG_SC_MCCB_1 SHAM
## garg, 2016_DTMS_CM_P_PANSS_1 DTMS_CM
## garg, 2016_DTMS_CM_N_PANSS_1 DTMS_CM
## garg, 2016_DTMS_CM_G_PANSS_1 DTMS_CM
## garg, 2016_DTMS_CM_T_PANSS_1 DTMS_CM
## gogler, 2017_TDCS_10-20EEG_PS_C_1 SHAM
## gogler, 2017_TDCS_10-20EEG_WM_K_1 SHAM
## gogler, 2017_TDCS_10-20EEG_AV_α_1 SHAM
## gomes, 2018_TDCS_10-20EEG_WM_MCCB_1 SHAM
## gomes, 2018_TDCS_10-20EEG_PS_MCCB_1 SHAM
## gomes, 2018_TDCS_10-20EEG_AV_MCCB_1 SHAM
## gomes, 2018_TDCS_10-20EEG_VerL_MCCB_1 SHAM
## gomes, 2018_TDCS_10-20EEG_VisL_MCCB_1 SHAM
## gomes, 2018_TDCS_10-20EEG_RPS_MCCB_1 SHAM
## gomes, 2018_TDCS_10-20EEG_P_PANSS_1 SHAM
## gomes, 2018_TDCS_10-20EEG_N_PANSS-N_1 SHAM
## gomes, 2018_TDCS_10-20EEG_G_PANSS_1 SHAM
## gomes, 2018_TDCS_10-20EEG_T_PANSS-T_1 SHAM
## guan, 2020_HF-RTMS_NEURONAV_T_PANSS-T_1 HF-RTMS_NEURONAV
## guan, 2020_HF-RTMS_NEURONAV_P_PANSS_1 HF-RTMS_NEURONAV
## guan, 2020_HF-RTMS_NEURONAV_N_PANSS-N_1 HF-RTMS_NEURONAV
## guan, 2020_HF-RTMS_NEURONAV_G_PANSS_1 HF-RTMS_NEURONAV
## guan, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nImmediate memory_1 HF-RTMS_NEURONAV
## guan, 2020_HF-RTMS_NEURONAV_WM_RBANS\r\nAttention_1 HF-RTMS_NEURONAV
## guan, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nVisuospatial/constructional_1 HF-RTMS_NEURONAV
## guan, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nDelayed memory_1 HF-RTMS_NEURONAV
## guan, 2020_HF-RTMS_NEURONAV_PS_RBANS\r\nLanguage_1 HF-RTMS_NEURONAV
## guan, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 HF-RTMS_NEURONAV
## guleken, 2020_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## guleken, 2020_HF-RTMS_CM_N_SANS_1 HF-RTMS_CM
## guleken, 2020_HF-RTMS_CM_RPS_WSCT total correct responses_1 HF-RTMS_CM
## guleken, 2020_HF-RTMS_CM_RPS_WSCT perseverative errors_1 HF-RTMS_CM
## guleken, 2020_HF-RTMS_CM_WM_DST forward_1 HF-RTMS_CM
## guleken, 2020_HF-RTMS_CM_WM_DST backwards_1 HF-RTMS_CM
## guleken, 2020_HF-RTMS_CM_RPS_Total time_1 HF-RTMS_CM
## guleken, 2020_HF-RTMS_CM_RPS_Total errors_1 HF-RTMS_CM
## guleken, 2020_HF-RTMS_CM_RPS_Stroop Interference_1 HF-RTMS_CM
## guse, 2013_HF-RTMS_10-20EEG_PS_TMT-A_1 HF-RTMS_10-20EEG
## guse, 2013_HF-RTMS_10-20EEG_RPS_TMT-B_1 HF-RTMS_10-20EEG
## guse, 2013_HF-RTMS_10-20EEG_RPS_WCST Accuracy_1 HF-RTMS_10-20EEG
## guse, 2013_HF-RTMS_10-20EEG_RPS_WCST RT_1 HF-RTMS_10-20EEG
## guse, 2013_HF-RTMS_10-20EEG_AV_Sel. Attention Accuracy_1 HF-RTMS_10-20EEG
## guse, 2013_HF-RTMS_10-20EEG_AV_Sel. Attention RT_1 HF-RTMS_10-20EEG
## guse, 2013_HF-RTMS_10-20EEG_AV_Div. Attention Accuracy_1 HF-RTMS_10-20EEG
## guse, 2013_HF-RTMS_10-20EEG_AV_Div. Attention RT_1 HF-RTMS_10-20EEG
## guse, 2013_HF-RTMS_10-20EEG_WM_0-back Accuracy_1 HF-RTMS_10-20EEG
## guse, 2013_HF-RTMS_10-20EEG_WM_0-back RT_1 HF-RTMS_10-20EEG
## guse, 2013_HF-RTMS_10-20EEG_WM_1-back Accuracy_1 HF-RTMS_10-20EEG
## guse, 2013_HF-RTMS_10-20EEG_WM_1-back RT_1 HF-RTMS_10-20EEG
## guse, 2013_HF-RTMS_10-20EEG_WM_2-back Accuracy_1 HF-RTMS_10-20EEG
## guse, 2013_HF-RTMS_10-20EEG_WM_2-back RT_1 HF-RTMS_10-20EEG
## hasan, 2016_HF-RTMS_10-20EEG_WM_DST z score_1 HF-RTMS_10-20EEG
## hasan, 2016_HF-RTMS_10-20EEG_WM_DST Forward_1 HF-RTMS_10-20EEG
## hasan, 2016_HF-RTMS_10-20EEG_WM_DST Backward_1 HF-RTMS_10-20EEG
## hasan, 2016_HF-RTMS_10-20EEG_PS_TMT-A time (s)_1 HF-RTMS_10-20EEG
## hasan, 2016_HF-RTMS_10-20EEG_RPS_TMT-B time (s)_1 HF-RTMS_10-20EEG
## hasan, 2016_HF-RTMS_10-20EEG_VerL_VLMT z score_1 HF-RTMS_10-20EEG
## hasan, 2016_HF-RTMS_10-20EEG_RPS_WCST z score_1 HF-RTMS_10-20EEG
## hasan, 2016_HF-RTMS_10-20EEG_RPS_WCST total correct score_1 HF-RTMS_10-20EEG
## hasan, 2016_HF-RTMS_10-20EEG_RPS_WCST total errors_1 HF-RTMS_10-20EEG
## hasan, 2016_HF-RTMS_10-20EEG_PS_RWT z score_1 HF-RTMS_10-20EEG
## holi, 2004_HF-RTMS_10-20EEG_T_PANSS_1 HF-RTMS_10-20EEG
## holi, 2004_HF-RTMS_10-20EEG_P_PANSS_1 HF-RTMS_10-20EEG
## holi, 2004_HF-RTMS_10-20EEG_N_PANSS_1 HF-RTMS_10-20EEG
## holi, 2004_HF-RTMS_10-20EEG_G_PANSS_1 HF-RTMS_10-20EEG
## hu, 2024_LF-RTMS_10-20EEG_T_PANSS_1 LF-RTMS_10-20EEG
## hu, 2024_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## hu, 2024_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## hu, 2024_LF-RTMS_10-20EEG_G_PANSS_1 LF-RTMS_10-20EEG
## hu, 2024_LF-RTMS_10-20EEG_PS_TMT-A_1 LF-RTMS_10-20EEG
## hu, 2024_LF-RTMS_10-20EEG_PS_BACS Symbol Coding_1 LF-RTMS_10-20EEG
## hu, 2024_LF-RTMS_10-20EEG_PS_Category Fluency_1 LF-RTMS_10-20EEG
## hu, 2024_LF-RTMS_10-20EEG_AV_CPT-IP_1 LF-RTMS_10-20EEG
## hu, 2024_LF-RTMS_10-20EEG_WM_WMS-3 spatial span_1 LF-RTMS_10-20EEG
## hu, 2024_LF-RTMS_10-20EEG_VerL_HVLT-R_1 LF-RTMS_10-20EEG
## hu, 2024_LF-RTMS_10-20EEG_VisL_BVMT-R_1 LF-RTMS_10-20EEG
## hu, 2024_LF-RTMS_10-20EEG_RPS_NAB_1 LF-RTMS_10-20EEG
## hu, 2023_LF-RTMS_10-10EEG_T_PANSS_1 LF-RTMS_10-10EEG
## hu, 2023_LF-RTMS_10-10EEG_P_PANSS_1 LF-RTMS_10-10EEG
## hu, 2023_LF-RTMS_10-10EEG_N_PANSS_1 LF-RTMS_10-10EEG
## hu, 2023_LF-RTMS_10-10EEG_G_PANSS_1 LF-RTMS_10-10EEG
## hu, 2023_LF-RTMS_10-10EEG_GC_MCCB-T_1 LF-RTMS_10-10EEG
## hu, 2023_LF-RTMS_10-10EEG_PS_MCCB_1 LF-RTMS_10-10EEG
## hu, 2023_LF-RTMS_10-10EEG_AV_MCCB_1 LF-RTMS_10-10EEG
## hu, 2023_LF-RTMS_10-10EEG_WM_MCCB_1 LF-RTMS_10-10EEG
## hu, 2023_LF-RTMS_10-10EEG_VerL_MCCB_1 LF-RTMS_10-10EEG
## hu, 2023_LF-RTMS_10-10EEG_VisL_MCCB_1 LF-RTMS_10-10EEG
## hu, 2023_LF-RTMS_10-10EEG_RPS_MCCB_1 LF-RTMS_10-10EEG
## hu, 2023_LF-RTMS_10-10EEG_SC_MCCB_1 LF-RTMS_10-10EEG
## huang, 2016_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## huang, 2016_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## huang, 2016_HF-RTMS_CM_G_PANSS_1 HF-RTMS_CM
## huang, 2016_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## huang, 2016_HF-RTMS_CM_RPS_WSCT total errors_1 HF-RTMS_CM
## jeon, 2018_TDCS_10-20EEG_P_PANSS_1 SHAM
## jeon, 2018_TDCS_10-20EEG_N_PANSS_1 SHAM
## jeon, 2018_TDCS_10-20EEG_G_PANSS_1 SHAM
## jeon, 2018_TDCS_10-20EEG_T_PANSS_1 SHAM
## jeon, 2018_TDCS_10-20EEG_PS_MCCB_1 SHAM
## jeon, 2018_TDCS_10-20EEG_AV_MCCB_1 SHAM
## jeon, 2018_TDCS_10-20EEG_WM_MCCB_1 SHAM
## jeon, 2018_TDCS_10-20EEG_VerL_MCCB_1 SHAM
## jeon, 2018_TDCS_10-20EEG_VisL_MCCB_1 SHAM
## jeon, 2018_TDCS_10-20EEG_RPS_MCCB_1 SHAM
## jeon, 2018_TDCS_10-20EEG_SC_MCCB_1 SHAM
## jeon, 2018_TDCS_10-20EEG_GC_MCCB Composite Score_1 SHAM
## jeon, 2018_TDCS_10-20EEG_RPS_WCST Perservative Responses_1 SHAM
## jeon, 2018_TDCS_10-20EEG_RPS_WCST Perservative Errors_1 SHAM
## jeon, 2018_TDCS_10-20EEG_RPS_WCST Categoris number_1 SHAM
## jin, 2023_ITBS_NA_SC_FERT_1 ITBS_NA
## jin, 2023_ITBS_NA_SC_HT_1 ITBS_NA
## jin, 2023_ITBS_NA_T_PANSS_1 ITBS_NA
## jin, 2023_ITBS_NA_P_PANSS_1 ITBS_NA
## jin, 2023_ITBS_NA_N_PANSS_1 ITBS_NA
## jin, 2023_ITBS_NA_G_PANSS_1 ITBS_NA
## kang, 2024_CTBS_CM_T_PANSS_1 CTBS_CM
## kang, 2024_CTBS_CM_P_PANSS_1 CTBS_CM
## kang, 2024_CTBS_CM_N_PANSS_1 CTBS_CM
## kang, 2024_CTBS_CM_G_PANSS_1 CTBS_CM
## kang, 2024_CTBS_CM_P_AHRS_1 CTBS_CM
## kantrowitz, 2019_TDCS_10-20EEG_P_AHRS_1 SHAM
## kimura, 2016_HF-RTMS_10-20EEG_P_AHRS_1 HF-RTMS_10-20EEG
## klein, 1999_LF-RTMS_CM_P_PANSS_1 LF-RTMS_CM
## klein, 1999_LF-RTMS_CM_N_PANSS_1 LF-RTMS_CM
## klein, 1999_LF-RTMS_CM_G_PANSS_1 LF-RTMS_CM
## klein, 1999_LF-RTMS_CM_T_BPRS_1 LF-RTMS_CM
## koops, 2018_TDCS_10-20EEG_P_AHRS_1 SHAM
## koops, 2018_TDCS_10-20EEG_T_PANSS_1 SHAM
## koops, 2018_TDCS_10-20EEG_P_PANSS_1 SHAM
## koops, 2018_TDCS_10-20EEG_N_PANSS_1 SHAM
## koops, 2018_TDCS_10-20EEG_RPS_Stroop Interference_1 SHAM
## koops, 2018_TDCS_10-20EEG_PS_TMT-A_1 SHAM
## koops, 2018_TDCS_10-20EEG_RPS_TMT-B_1 SHAM
## koops, 2016_CTBS_10-20EEG_P_PANSS_1 CTBS_10-20EEG
## koops, 2016_CTBS_10-20EEG_P_AHRS_1 CTBS_10-20EEG
## koops, 2016_CTBS_10-20EEG_P_PSYRATS_1 CTBS_10-20EEG
## kos, 2024_TDCS_10-20EEG_N_SANS_1 SHAM
## kos, 2024_TDCS_10-20EEG_N_AES_1 SHAM
## kumar, 2020_HF-RTMS_CM_PANSS-N_1 HF-RTMS_CM
## kumar, 2020_HF-RTMS_CM_PANSS-G_1 HF-RTMS_CM
## li, 2024 - a_ITBS_10-20EEG_GC_MCCB_1 ITBS_10-20EEG
## li, 2024 - a_ITBS_10-20EEG_WM_MCCB_1 ITBS_10-20EEG
## li, 2024 - a_ITBS_10-20EEG_PANSS-P_1 ITBS_10-20EEG
## li, 2024 - a_ITBS_10-20EEG_PANSS-N_1 ITBS_10-20EEG
## li, 2024 - a_ITBS_10-20EEG_PANSS-G_1 ITBS_10-20EEG
## li-b-lpc, 2024_ITBS_NEURONAV_PS_MCCB_1 ITBS_NEURONAV
## li-b-lpc, 2024_ITBS_NEURONAV_AV_MCCB_1 ITBS_NEURONAV
## li-b-lpc, 2024_ITBS_NEURONAV_WM_MCCB_1 ITBS_NEURONAV
## li-b-lpc, 2024_ITBS_NEURONAV_VerL_MCCB_1 ITBS_NEURONAV
## li-b-lpc, 2024_ITBS_NEURONAV_VisL_MCCB_1 ITBS_NEURONAV
## li-b-lpc, 2024_ITBS_NEURONAV_RPS_MCCB_1 ITBS_NEURONAV
## li-b-lpc, 2024_ITBS_NEURONAV_SC_MCCB_1 ITBS_NEURONAV
## li-b-lpc, 2024_ITBS_NEURONAV_GC_MCCB_1 ITBS_NEURONAV
## li-b-dlpfc, 2024_ITBS_NEURONAV_PS_MCCB_1 ITBS_NEURONAV
## li-b-dlpfc, 2024_ITBS_NEURONAV_AV_MCCB_1 ITBS_NEURONAV
## li-b-dlpfc, 2024_ITBS_NEURONAV_WM_MCCB_1 ITBS_NEURONAV
## li-b-dlpfc, 2024_ITBS_NEURONAV_VerL_MCCB_1 ITBS_NEURONAV
## li-b-dlpfc, 2024_ITBS_NEURONAV_VisL_MCCB_1 ITBS_NEURONAV
## li-b-dlpfc, 2024_ITBS_NEURONAV_RPS_MCCB_1 ITBS_NEURONAV
## li-b-dlpfc, 2024_ITBS_NEURONAV_SC_MCCB_1 ITBS_NEURONAV
## li-b-dlpfc, 2024_ITBS_NEURONAV_GC_MCCB_1 ITBS_NEURONAV
## lindenmayer, 2019_TDCS_10-20EEG_AHRS_1 SHAM
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-T_1 SHAM
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-P_1 SHAM
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-N_1 SHAM
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-G_1 SHAM
## lindenmayer, 2019_TDCS_10-20EEG_GC_MCCB_1 SHAM
## lindenmayer, 2019_TDCS_10-20EEG_PS_MCCB_1 SHAM
## lindenmayer, 2019_TDCS_10-20EEG_AV_MCCB_1 SHAM
## lindenmayer, 2019_TDCS_10-20EEG_WM_MCCB_1 SHAM
## lindenmayer, 2019_TDCS_10-20EEG_VerL_MCCB_1 SHAM
## lindenmayer, 2019_TDCS_10-20EEG_VisL_MCCB_1 SHAM
## lindenmayer, 2019_TDCS_10-20EEG_RPN_MCCB_1 SHAM
## lindenmayer, 2019_TDCS_10-20EEG_SC_MCCB_1 SHAM
## lisoni, 2022_TDCS_10-20 EEG_PANSS-P_1 SHAM
## lisoni, 2022_TDCS_10-20 EEG_PANSS-N_1 SHAM
## lisoni, 2022_TDCS_10-20 EEG_PANSS-T_1 SHAM
## lisoni, 2022_TDCS_10-20 EEG_PANSS-G_1 SHAM
## lisoni, 2022_TDCS_10-20 EEG_GC_BACS (Composite z-scores)_1 SHAM
## lisoni, 2022_TDCS_10-20 EEG_VerL_BACS z-scores (Verbal memory)_1 SHAM
## lisoni, 2022_TDCS_10-20 EEG_WM_BACS z-scores (Digit sequencing)_1 SHAM
## lisoni, 2022_TDCS_10-20 EEG_PS_BACS z-scores (Verbal fluency)_1 SHAM
## lisoni, 2022_TDCS_10-20 EEG_PS_BACS z-scores (Symbol coding)_1 SHAM
## lisoni, 2022_TDCS_10-20 EEG_RPS_BACS z-scores (Tower of London)_1 SHAM
## liu, 2024_HF-RTMS_NA_T_PANSS_1 HF-RTMS_NA
## liu, 2024_HF-RTMS_NA_P_PANSS_1 HF-RTMS_NA
## liu, 2024_HF-RTMS_NA_N_PANSS_1 HF-RTMS_NA
## liu, 2024_HF-RTMS_NA_G_PANSS_1 HF-RTMS_NA
## liu, 2024_HF-RTMS_NA_VerL_RBANS (Immediate memory)_1 HF-RTMS_NA
## liu, 2024_HF-RTMS_NA_VisL_RBANS (Visual spatial structure)_1 HF-RTMS_NA
## liu, 2024_HF-RTMS_NA_PS_RBANS (Speech function)_1 HF-RTMS_NA
## liu, 2024_HF-RTMS_NA_WM_RBANS (Attention)_1 HF-RTMS_NA
## liu, 2024_HF-RTMS_NA_Visl_RBANS (Delayed memory)_1 HF-RTMS_NA
## lyu, 2024_TDCS_10-20EEG_T_PANSS_1 SHAM
## lyu, 2024_TDCS_10-20EEG_P_PANSS_1 SHAM
## lyu, 2024_TDCS_10-20EEG_N_PANSS_1 SHAM
## lyu, 2024_TDCS_10-20EEG_G_PANSS_1 SHAM
## lyu, 2024_TDCS_10-20EEG_N_SANS_1 SHAM
## mao, 2023_HF-RTMS_CM_GC_RBANS_1 HF-RTMS_CM
## mao, 2023_HF-RTMS_CM_VerL_RBANS-Immediate Memory_1 HF-RTMS_CM
## mao, 2023_HF-RTMS_CM_RBANS-Visuospatial_1 HF-RTMS_CM
## mao, 2023_HF-RTMS_CM_VerL_RBANS-Language_1 HF-RTMS_CM
## mao, 2023_HF-RTMS_CM_WM_RBANS-Attention_1 HF-RTMS_CM
## mao, 2023_HF-RTMS_CM_VerL_RBANS-Delayed memory_1 HF-RTMS_CM
## mao, 2023_HF-RTMS_CM_P_AHRS_1 HF-RTMS_CM
## mao, 2023_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## marquardt, 2022_TDCS_10-20EEG_P_PANSS_1 SHAM
## marquardt, 2022_TDCS_10-20EEG_N_PANSS_1 SHAM
## marquardt, 2022_TDCS_10-20EEG_P_AHRS_1 SHAM
## marquardt, 2022_TDCS_10-20EEG_RPS_Stroop 3 (s/RT)_1 SHAM
## marquardt, 2022_TDCS_10-20EEG_RPS_Stroop 4 (s/RT)_1 SHAM
## marquardt, 2022_TDCS_10-20EEG_PS_TMT-A_1 SHAM
## marquardt, 2022_TDCS_10-20EEG_RPS_TMT-B_1 SHAM
## mcintosh, 2004_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## mcintosh, 2004_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## mcintosh, 2004_LF-RTMS_10-20EEG_VerL_AVLT_1 LF-RTMS_10-20EEG
## meiron, 2021_TDCS_10-20EEG_T_PANSS_1 SHAM
## meiron, 2021_TDCS_10-20EEG_WM_(verbal) WM - Accuracy_1 SHAM
## meiron, 2021_TDCS_10-20EEG_WM_(verbal) WM - RT_1 SHAM
## meiron, 2024_TDCS_10-20EEG_T_PANSS_1 SHAM
## meiron, 2024_TDCS_10-20EEG_WM_2-BACK Acc_1 SHAM
## meiron, 2024_TDCS_10-20EEG_WM_2-BACK RT_1 SHAM
## mellin-tacs, 2018_TACS_10-20EEG_P_AHRS_1 SHAM
## mellin-tacs, 2018_TACS_10-20EEG_T_PANSS-T_1 SHAM
## mellin-tacs, 2018_TACS_10-20EEG_P_PANSS-P_1 SHAM
## mellin-tacs, 2018_TACS_10-20EEG_N_PANSS-N_1 SHAM
## mellin-tacs, 2018_TACS_10-20EEG_G_PANSS-G_1 SHAM
## mellin-tacs, 2018_TACS_10-20EEG_GC_BACS_1 SHAM
## mellin-tdcs, 2018_TDCS_10-20EEG_P_AHRS_1 SHAM
## mellin-tdcs, 2018_TDCS_10-20EEG_T_PANSS_1 SHAM
## mellin-tdcs, 2018_TDCS_10-20EEG_P_PANSS_1 SHAM
## mellin-tdcs, 2018_TDCS_10-20EEG_N_PANSS_1 SHAM
## mellin-tdcs, 2018_TDCS_10-20EEG_G_PANSS_1 SHAM
## mellin-tdcs, 2018_TDCS_10-20EEG_GC_BACS_1 SHAM
## moeller, 2022_DTMS_CM_T_PANSS_1 DTMS_CM
## moeller, 2022_DTMS_CM_P_PANSS_1 DTMS_CM
## moeller, 2022_DTMS_CM_N_PANSS_1 DTMS_CM
## mogg, 2007_HF-RTMS_CM_VerL_HVLT immediate recall_1 HF-RTMS_CM
## mogg, 2007_HF-RTMS_CM_VerL_HVLT delayed recall_1 HF-RTMS_CM
## mogg, 2007_HF-RTMS_CM_PS_COWAT (number)_1 HF-RTMS_CM
## mogg, 2007_HF-RTMS_CM_RPS_Stroop RT (seconds)_1 HF-RTMS_CM
## mondino, 2015_TDCS_10-20EG_P_PANSS_1 SHAM
## mondino, 2015_TDCS_10-20EG_N_PANSS_1 SHAM
## mondino, 2015_TDCS_10-20EG_G_PANSS_1 SHAM
## mondino, 2015_TDCS_10-20EG_P_AHRS_1 SHAM
## novak, 2006_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## novak, 2006_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## novak, 2006_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## novak, 2006_HF-RTMS_CM_G_PANSS_1 HF-RTMS_CM
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_SAPS_1 LF-RTMS_NEURONAV
## paillere-martinot, 2017_LF-RTMS_NEURONAV_N_SANS_1 LF-RTMS_NEURONAV
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_AHRS_1 LF-RTMS_NEURONAV
## palm, 2016_TDCS_10-20EEG_T_PANSS_1 SHAM
## palm, 2016_TDCS_10-20EEG_P_PANSS_1 SHAM
## palm, 2016_TDCS_10-20EEG_N_PANSS_1 SHAM
## palm, 2016_TDCS_10-20EEG_N_SANS_1 SHAM
## palm, 2016_TDCS_10-20EEG_WM_SOPT_1 SHAM
## palm, 2016_TDCS_10-20EEG_PS_TMT-A_1 SHAM
## palm, 2016_TDCS_10-20EEG_RPS_TMT-B_1 SHAM
## prikryl, 2007_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## prikryl, 2007_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## prikryl, 2007_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## prikryl, 2007_HF-RTMS_CM_N_SANS_1 HF-RTMS_CM
## prikryl, 2007_HF-RTMS_CM_P_SAPS_1 HF-RTMS_CM
## prikryl, 2012_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## prikryl, 2012_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## prikryl, 2012_HF-RTMS_CM_G_PANSS_1 HF-RTMS_CM
## prikryl, 2012_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## prikryl, 2012_HF-RTMS_CM_PS_VFT_1 HF-RTMS_CM
## prikryl, 2014_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## prikryl, 2014_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## prikryl, 2014_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## prikryl, 2014_HF-RTMS_CM_G_PANSS_1 HF-RTMS_CM
## prikryl, 2013_HF-RTMS_CM_N_SANS_1 HF-RTMS_CM
## prikryl, 2013_HF-RTMS_CM_P_SAPS_1 HF-RTMS_CM
## quan, 2015_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## quan, 2015_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## quan, 2015_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## quan, 2015_HF-RTMS_CM_G_PANSS_1 HF-RTMS_CM
## quan, 2015_HF-RTMS_CM_N_SANS_1 HF-RTMS_CM
## rabany, 2014_DTMS_CM_T_PANSS_1 DTMS_CM
## rabany, 2014_DTMS_CM_N_PANSS_1 DTMS_CM
## rabany, 2014_DTMS_CM_N_SANS_1 DTMS_CM
## rabany, 2014_DTMS_CM_AV_RVP-A_1 DTMS_CM
## rabany, 2014_DTMS_CM_AV_RVP-B_1 DTMS_CM
## rabany, 2014_DTMS_CM_WM_SWM (Total between search errors)_1 DTMS_CM
## rabany, 2014_DTMS_CM_WM_SWM (Strategy score)_1 DTMS_CM
## rabany, 2014_DTMS_CM_RPS_SOC (Minimum move solutions for test trials)_1 DTMS_CM
## rabany, 2014_DTMS_CM_RPS_SOC (Initial times for 5 move problems)_1 DTMS_CM
## rabany, 2014_DTMS_CM_RPS_SOC (Subsequent times for 5 move problems)_1 DTMS_CM
## rabany, 2014_DTMS_CM_PS_RTI (Mean reaction time, stages 4 and 5)_1 DTMS_CM
## rabany, 2014_DTMS_CM_PS_RTI (Mean movement time, stages 4 and 5)_1 DTMS_CM
## rollnik, 2000_HF-RTMS_CM_T_BPRS_1 HF-RTMS_CM
## rollnik, 2000_HF-RTMS_CM_PS_NCT (seconds)_1 HF-RTMS_CM
## rosa, 2007_LF-RTMS_10-20EEG_T_PANSS_1 LF-RTMS_10-20EEG
## rosa, 2007_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## rosa, 2007_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## rosa, 2007_LF-RTMS_10-20EEG_G_PANSS_1 LF-RTMS_10-20EEG
## rosenberg, 2012_LF-RTMS_CM_P_AHRS_1 LF-RTMS_CM
## saba, 2006_LF-RTMS_CM_T_PANSS_1 LF-RTMS_CM
## saba, 2006_LF-RTMS_CM_P_PANSS_1 LF-RTMS_CM
## saba, 2006_LF-RTMS_CM_N_PANSS_1 LF-RTMS_CM
## saba, 2006_LF-RTMS_CM_G_PANSS_1 LF-RTMS_CM
## schilling, 2021_TDCS_10-20EEG_WM_Verbal Working Memory Reaction Time (t-score)_1 SHAM
## schilling, 2021_TDCS_10-20EEG_WM_Verbal Working Memory d-prime (z-score)_1 SHAM
## schilling, 2021_TDCS_10-20EEG_RPS_Response Inhibition Reaction Time (t-score)_1 SHAM
## schilling, 2021_TDCS_10-20EEG_RPS_Response Inhibition Errors (t-scores)_1 SHAM
## schilling, 2021_TDCS_10-20EEG_RPS_Problem solving t-score_1 SHAM
## schilling, 2021_TDCS_10-20EEG_RPS_Mental Flexibility Speed (t-score)_1 SHAM
## schilling, 2021_TDCS_10-20EEG_RPS_Mental Flexibility Accuracy (t-score)_1 SHAM
## singh, 2020_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## singh, 2020_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## singh, 2020_HF-RTMS_CM_N_SANS_1 HF-RTMS_CM
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_AHRS_1 LF-RTMS_NEURONAV
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_PANSS_1 LF-RTMS_NEURONAV
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_AHRS_1 LF-RTMS_10-20EEG
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## smith, 2015_TDCS_10-20EEG_GC_MCCB_1 SHAM
## smith, 2015_TDCS_10-20EEG_WM_MCCB_1 SHAM
## smith, 2015_TDCS_10-20EEG_AV_MCCB_1 SHAM
## smith, 2015_TDCS_10-20EEG_RPS_MCCB_1 SHAM
## smith, 2015_TDCS_10-20EEG_VerL_MCCB_1 SHAM
## smith, 2015_TDCS_10-20EEG_VisL_MCCB_1 SHAM
## smith, 2015_TDCS_10-20EEG_PS_MCCB_1 SHAM
## smith, 2015_TDCS_10-20EEG_SC_MCCB_1 SHAM
## smith, 2015_TDCS_10-20EEG_T_PANSS_1 SHAM
## smith, 2015_TDCS_10-20EEG_P_PANSS_1 SHAM
## smith, 2015_TDCS_10-20EEG_N_PANSS_1 SHAM
## smith, 2015_TDCS_10-20EEG_G_PANSS_1 SHAM
## smith, 2020_TDCS_10-20EEG_GC_MCCB_1 SHAM
## smith, 2020_TDCS_10-20EEG_PS_MCCB_1 SHAM
## smith, 2020_TDCS_10-20EEG_AV_MCCB_1 SHAM
## smith, 2020_TDCS_10-20EEG_WM_MCCB_1 SHAM
## smith, 2020_TDCS_10-20EEG_VerL_MCCB_1 SHAM
## smith, 2020_TDCS_10-20EEG_VisL_MCCB_1 SHAM
## smith, 2020_TDCS_10-20EEG_RPS_MCCB_1 SHAM
## smith, 2020_TDCS_10-20EEG_SC_MCCB_1 SHAM
## smith, 2020_TDCS_10-20EEG_AV_PASAT (Number Correct)_1 SHAM
## smith, 2020_TDCS_10-20EEG_T_PANSS_1 SHAM
## smith, 2020_TDCS_10-20EEG_P_PANSS_1 SHAM
## smith, 2020_TDCS_10-20EEG_N_PANSS_1 SHAM
## su, 2023b_HF-RTMS_NEURONAV_T_PANSS_1 HF-RTMS_NEURONAV
## su, 2023b_HF-RTMS_NEURONAV_P_PANSS_1 HF-RTMS_NEURONAV
## su, 2023b_HF-RTMS_NEURONAV_N_PANSS_1 HF-RTMS_NEURONAV
## su, 2023b_HF-RTMS_NEURONAV_G_PANSS_1 HF-RTMS_NEURONAV
## su, 2022_HF-RTMS_NEURONAV_T_PANSS_1 HF-RTMS_NEURONAV
## su, 2022_HF-RTMS_NEURONAV_P_PANSS_1 HF-RTMS_NEURONAV
## su, 2022_HF-RTMS_NEURONAV_N_PANSS_1 HF-RTMS_NEURONAV
## su, 2022_HF-RTMS_NEURONAV_G_PANSS_1 HF-RTMS_NEURONAV
## tikka, 2017_CTBS_NEURONAV_P_PANSS_1 CTBS_NEURONAV
## tikka, 2017_CTBS_NEURONAV_N_PANSS_1 CTBS_NEURONAV
## tikka, 2017_CTBS_NEURONAV_G_PANSS_1 CTBS_NEURONAV
## tikka, 2017_CTBS_NEURONAV_T_PANSS_1 CTBS_NEURONAV
## tikka, 2017_CTBS_NEURONAV_RPS_Self-Monitoring Task_1 CTBS_NEURONAV
## tikka, 2017_CTBS_NEURONAV_WM_Visual Memory Task_1 CTBS_NEURONAV
## tyagi, 2022_CTBS_10-20EEG_P_PANSS_1 CTBS_10-20EEG
## tyagi, 2022_CTBS_10-20EEG_N_PANSS_1 CTBS_10-20EEG
## tyagi, 2022_CTBS_10-20EEG_T_PANSS_1 CTBS_10-20EEG
## tyagi, 2022_CTBS_10-20EEG_G_PANSS_1 CTBS_10-20EEG
## tyagi, 2022_CTBS_10-20EEG_P_AVHRS_1 CTBS_10-20EEG
## tyagi, 2022_CTBS_10-20EEG_P_PSYRAT-AH_1 CTBS_10-20EEG
## valiengo, 2020_TDCS_10-20EEG_N_PANSS_1 SHAM
## valiengo, 2020_TDCS_10-20EEG_P_PANSS_1 SHAM
## valiengo, 2020_TDCS_10-20EEG_T_PANSS_1 SHAM
## valiengo, 2020_TDCS_10-20EEG_G_PANSS_1 SHAM
## valiengo, 2020_TDCS_10-20EEG_P_AVHRS_1 SHAM
## vercammen, 2011_TDCS_10-20EEG_RPS_Weather Prediction Test_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_T_PANSS_1 ITBS_10-20EEG
## vergallito, 2024_ITBS_10-20EEG_P_PANSS_1 ITBS_10-20EEG
## vergallito, 2024_ITBS_10-20EEG_N_PANSS_1 ITBS_10-20EEG
## vergallito, 2024_ITBS_10-20EEG_N_BNSS_1 ITBS_10-20EEG
## vergallito, 2024_ITBS_10-20EEG_GC_MCCB_1 ITBS_10-20EEG
## vergallito, 2024_ITBS_10-20EEG_PS_MCCB_1 ITBS_10-20EEG
## vergallito, 2024_ITBS_10-20EEG_AV_MCCB_1 ITBS_10-20EEG
## vergallito, 2024_ITBS_10-20EEG_WM_MCCB_1 ITBS_10-20EEG
## vergallito, 2024_ITBS_10-20EEG_VerL_MCCB_1 ITBS_10-20EEG
## vergallito, 2024_ITBS_10-20EEG_VisL_MCCB_1 ITBS_10-20EEG
## vergallito, 2024_ITBS_10-20EEG_RPS_MCCB_1 ITBS_10-20EEG
## vergallito, 2024_ITBS_10-20EEG_SC_MCCB_1 ITBS_10-20EEG
## walther-lft, 2024_UNKNOWN_STANDARD_T_PANSS_1 SHAM
## walther-lft, 2024_UNKNOWN_STANDARD_P_PANSS_1 SHAM
## walther-lft, 2024_UNKNOWN_STANDARD_N_PANSS_1 SHAM
## walther-lft, 2024_UNKNOWN_STANDARD_G_PANSS_1 SHAM
## walther-lft, 2024_UNKNOWN_STANDARD_N_BNSS_1 SHAM
## walther-itbs, 2024_ITBS_CM_T_PANSS_1 ITBS_CM
## walther-itbs, 2024_ITBS_CM_P_PANSS_1 ITBS_CM
## walther-itbs, 2024_ITBS_CM_N_PANSS_1 ITBS_CM
## walther-itbs, 2024_ITBS_CM_G_PANSS_1 ITBS_CM
## walther-itbs, 2024_ITBS_CM_N_BNSS_1 ITBS_CM
## wang, 2020_ITBS_NEURONAV_T_PANSS_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_P_PANSS_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_N_PANSS_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_G_PANSS_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_P_SAPS_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_N_SANS_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_GC_MoCA_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_PS_VFT_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_WM_Digit span (forward)_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_WM_Digit span (backward)_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_RPS_Stroop Color Test_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_RPS_Stroop Word Test_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_RPS_Stroop Interference Test_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_PS_TMT-A_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_RPS_TMT-B_1 ITBS_NEURONAV
## wang, 2022_ITBS_NEURONAV_P_PANSS_1 ITBS_NEURONAV
## wang, 2022_ITBS_NEURONAV_N_PANSS_1 ITBS_NEURONAV
## wang, 2022_ITBS_NEURONAV_G_PANSS_1 ITBS_NEURONAV
## wang, 2022_ITBS_NEURONAV_T_PANSS_1 ITBS_NEURONAV
## wang, 2022_ITBS_NEURONAV_P_SAPS_1 ITBS_NEURONAV
## wang, 2022_ITBS_NEURONAV_N_SANS_1 ITBS_NEURONAV
## wang, 2022_ITBS_NEURONAV_GC_MoCA_1 ITBS_NEURONAV
## wang, 2022_ITBS_NEURONAV_WM_3-back RT_1 ITBS_NEURONAV
## weickert, 2019_TDCS_10-20EEG_T_PANSS_1 SHAM
## weickert, 2019_TDCS_10-20EEG_P_PANSS_1 SHAM
## weickert, 2019_TDCS_10-20EEG_N_PANSS_1 SHAM
## weickert, 2019_TDCS_10-20EEG_G_PANSS_1 SHAM
## weickert, 2019_TDCS_10-20EEG_P_AHRS_1 SHAM
## weickert, 2019_TDCS_10-20EEG_PS_BACS sc_1 SHAM
## weickert, 2019_TDCS_10-20EEG_PS_TMT-A_1 SHAM
## weickert, 2019_TDCS_10-20EEG_WM_LNS_1 SHAM
## weickert, 2019_TDCS_10-20EEG_VerL_HVLTr_1 SHAM
## weickert, 2019_TDCS_10-20EEG_VisL_BVMT_1 SHAM
## weickert, 2019_TDCS_10-20EEG_RPS_NAB maze_1 SHAM
## weickert, 2019_TDCS_10-20EEG_PS_fluency_1 SHAM
## wen, 2021_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## wen, 2021_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## wen, 2021_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## wen, 2021_HF-RTMS_CM_G_PANSS_1 HF-RTMS_CM
## wen, 2021_HF-RTMS_CM_GC_RBANS-T_1 HF-RTMS_CM
## wen, 2021_HF-RTMS_CM_VerL_RBANS\r\nImmediate memory_1 HF-RTMS_CM
## wen, 2021_HF-RTMS_CM_WM_RBANS\r\nAttention_1 HF-RTMS_CM
## wen, 2021_HF-RTMS_CM_VisL_RBANS\r\nVisuospatial_1 HF-RTMS_CM
## wen, 2021_HF-RTMS_CM_VisL_RBANS\r\nDelayed memory_1 HF-RTMS_CM
## wen, 2021_HF-RTMS_CM_VerL_RBANS\r\nLanguage_1 HF-RTMS_CM
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n1 word (s)_1 HF-RTMS_CM
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n2 word (s)_1 HF-RTMS_CM
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n3 word (s)_1 HF-RTMS_CM
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n3 color (s)_1 HF-RTMS_CM
## wobrock, 2015_HF-RTMS_10-20EEG_T_PANSS_1 HF-RTMS_10-20EEG
## wobrock, 2015_HF-RTMS_10-20EEG_P_PANSS_1 HF-RTMS_10-20EEG
## wobrock, 2015_HF-RTMS_10-20EEG_N_PANSS_1 HF-RTMS_10-20EEG
## xie, 2023-a_LF-RTMS_10-20EEG_T_PANSS_1 LF-RTMS_10-20EEG
## xie, 2023-a_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## xie, 2023-a_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## xie, 2023-a_LF-RTMS_10-20EEG_G_PANSS_1 LF-RTMS_10-20EEG
## xie, 2023-a_LF-RTMS_10-20EEG_P_AHRS_1 LF-RTMS_10-20EEG
## xiu-10hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 HF-RTMS_NEURONAV
## xiu-10hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 HF-RTMS_NEURONAV
## xiu-10hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 HF-RTMS_NEURONAV
## xiu-10hz, 2020_HF-RTMS_NEURONAV_G_PANSS_1 HF-RTMS_NEURONAV
## xiu-10hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 HF-RTMS_NEURONAV
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nImmediate memory_1 HF-RTMS_NEURONAV
## xiu-10hz, 2020_HF-RTMS_NEURONAV_WM_RBANS\r\nAttention_1 HF-RTMS_NEURONAV
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nVisuospatial_1 HF-RTMS_NEURONAV
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nDelayed memory_1 HF-RTMS_NEURONAV
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nLanguage_1 HF-RTMS_NEURONAV
## xiu-20hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 HF-RTMS_NEURONAV
## xiu-20hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 HF-RTMS_NEURONAV
## xiu-20hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 HF-RTMS_NEURONAV
## xiu-20hz, 2020_HF-RTMS_NEURONAV_G_PANSS_1 HF-RTMS_NEURONAV
## xiu-20hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 HF-RTMS_NEURONAV
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nImmediate memory_1 HF-RTMS_NEURONAV
## xiu-20hz, 2020_HF-RTMS_NEURONAV_WM_RBANS\r\nAttention_1 HF-RTMS_NEURONAV
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nVisuospatial_1 HF-RTMS_NEURONAV
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nDelayed memory_1 HF-RTMS_NEURONAV
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nLanguage_1 HF-RTMS_NEURONAV
## xu, 2023_HD-TDCS_10-20EEG_T_PANSS_1 HD-TDCS_10-20EEG
## xu, 2023_HD-TDCS_10-20EEG_P_PANSS_1 HD-TDCS_10-20EEG
## xu, 2023_HD-TDCS_10-20EEG_N_PANSS_1 HD-TDCS_10-20EEG
## xu, 2023_HD-TDCS_10-20EEG_G_PANSS_1 HD-TDCS_10-20EEG
## xu, 2023_HD-TDCS_10-20EEG_GC_RBANS_1 HD-TDCS_10-20EEG
## ye-20hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 HF-RTMS_NEURONAV
## ye-20hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Immediate memory_1 HF-RTMS_NEURONAV
## ye-20hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Visuospatial_1 HF-RTMS_NEURONAV
## ye-20hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Language_1 HF-RTMS_NEURONAV
## ye-20hz, 2024_HF-RTMS_NEURONAV_WM_RBANS - Attention_1 HF-RTMS_NEURONAV
## ye-20hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Delayed memory_1 HF-RTMS_NEURONAV
## ye-10hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 HF-RTMS_NEURONAV
## ye-10hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Immediate memory_1 HF-RTMS_NEURONAV
## ye-10hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Visuospatial_1 HF-RTMS_NEURONAV
## ye-10hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Language_1 HF-RTMS_NEURONAV
## ye-10hz, 2024_HF-RTMS_NEURONAV_WM_RBANS - Attention_1 HF-RTMS_NEURONAV
## ye-10hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Delayed memory_1 HF-RTMS_NEURONAV
## yuanjun, 2024_LF-RTMS_10-20EEG_T_PANSS_1 LF-RTMS_10-20EEG
## yuanjun, 2024_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## yuanjun, 2024_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## yuanjun, 2024_LF-RTMS_10-20EEG_G_PANSS_1 LF-RTMS_10-20EEG
## yuanjun, 2024_LF-RTMS_10-20EEG_P_AHRS_1 LF-RTMS_10-20EEG
## zhai-a, 2023_HF-RTMS_NA_T_PANSS_1 HF-RTMS_NA
## zhang, 2022_TACS_10-20EEG_T_PANSS_1 SHAM
## zhang, 2022_TACS_10-20EEG_P_PANSS_1 SHAM
## zhang, 2022_TACS_10-20EEG_N_PANSS_1 SHAM
## zhang, 2022_TACS_10-20EEG_P_AHRS_1 SHAM
## zhao-tbs, 2014_ITBS_10-20EEG_T_PANSS_1 ITBS_10-20EEG
## zhao-tbs, 2014_ITBS_10-20EEG_P_PANSS_1 ITBS_10-20EEG
## zhao-tbs, 2014_ITBS_10-20EEG_N_PANSS_1 ITBS_10-20EEG
## zhao-tbs, 2014_ITBS_10-20EEG_G_PANSS_1 ITBS_10-20EEG
## zhao-tbs, 2014_ITBS_10-20EEG_N_SANS_1 ITBS_10-20EEG
## zhao-20hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 HF-RTMS_10-20EEG
## zhao-20hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 HF-RTMS_10-20EEG
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 HF-RTMS_10-20EEG
## zhao-20hz, 2014_HF-RTMS_10-20EEG_G_PANSS_1 HF-RTMS_10-20EEG
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 HF-RTMS_10-20EEG
## zhao-10hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 HF-RTMS_10-20EEG
## zhao-10hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 HF-RTMS_10-20EEG
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 HF-RTMS_10-20EEG
## zhao-10hz, 2014_HF-RTMS_10-20EEG_G_PANSS_1 HF-RTMS_10-20EEG
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 HF-RTMS_10-20EEG
## zhou, 2024_HF-RTMS_10-20EEG_P_PANSS_1 HF-RTMS_10-20EEG
## zhou, 2024_HF-RTMS_10-20EEG_N_PANSS_1 HF-RTMS_10-20EEG
## zhou, 2024_HF-RTMS_10-20EEG_T_PANSS_1 HF-RTMS_10-20EEG
## zhou, 2024_HF-RTMS_10-20EEG_G_PANSS_1 HF-RTMS_10-20EEG
## zhou, 2024_HF-RTMS_10-20EEG_GC_RBANS-T_1 HF-RTMS_10-20EEG
## zhou, 2024_HF-RTMS_10-20EEG_VerL_RBANS\r\nImmediate memory_1 HF-RTMS_10-20EEG
## zhou, 2024_HF-RTMS_10-20EEG_VisL_RBANS\r\nVisuospatial_1 HF-RTMS_10-20EEG
## zhou, 2024_HF-RTMS_10-20EEG_VerL_RBANS\r\nLanguage_1 HF-RTMS_10-20EEG
## zhou, 2024_HF-RTMS_10-20EEG_WM_RBANS\r\nAttention_1 HF-RTMS_10-20EEG
## zhou, 2024_HF-RTMS_10-20EEG_VisL_RBANS\r\nDelayed memory_1 HF-RTMS_10-20EEG
## zhou, 2024_HF-RTMS_10-20EEG_RPS_SCWT \r\nInference scores_1 HF-RTMS_10-20EEG
## zhou, 2023_TDCS_10-20EEG_T_PANSS_1 SHAM
## zhou, 2023_TDCS_10-20EEG_N_SANS_1 SHAM
## zhou, 2023_TDCS_10-20EEG_RPS_IED total errors_1 SHAM
## zhu, 2021_ITBS_CM_N_PANSS_1 ITBS_CM
## zhuo, 2019_HF-RTMS_10-20EEG_T_PANSS_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_P_PANSS_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_N_PANSS_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_G_PANSS_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_N_SANS_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_PS_MCCB TMT-A_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_PS_MCCB BACS_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_PS_MCCB Fluency_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_WM_MCCB Working memory (WMS-SS)_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_VerL_MCCB Verbal learning (HVLT-R)_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_VisL_MCCB Visual learning (BVMT-R)_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_RPS_MCCB Reasoning/problem solving (NAB)_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_SC_MCCB Social cognition (MSCEIT)_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_GC_MCCB Composite score_1 HF-RTMS_10-20EEG
## treat2
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANSS_1 SHAM
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANSS_1 SHAM
## bais, 2014 - l_LF-RTMS_10-20EEG_G_PANSS_1 SHAM
## bais, 2014 - l_LF-RTMS_10-20EEG_P_AHRS_1 SHAM
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANAS_1 SHAM
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANAS_1 SHAM
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANSS_1 SHAM
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANSS_1 SHAM
## bais, 2014 - bi_LF-RTMS_10-20EEG_G_PANSS_1 SHAM
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_AHRS_1 SHAM
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANAS_1 SHAM
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANAS_1 SHAM
## barr, 2011_HF-RTMS_NEURONAV_WM_1-back RT ms_1 SHAM
## barr, 2011_HF-RTMS_NEURONAV_WM_2-back RT ms_1 SHAM
## barr, 2011_HF-RTMS_NEURONAV_WM_3-back RT ms_1 SHAM
## barr, 2013_HF-RTMS_NEURONAV_WM_1-back RT ms Target Correct_1 SHAM
## barr, 2013_HF-RTMS_NEURONAV_WM_1-back RT ms Non Target Correct_1 SHAM
## barr, 2013_HF-RTMS_NEURONAV_WM_3-back RT ms Target Correct_1 SHAM
## barr, 2013_HF-RTMS_NEURONAV_WM_3-back RT ms Non Target Correct_1 SHAM
## barr, 2012_HF-RTMS_NEURONAV_P_PANSS_1 SHAM
## barr, 2012_HF-RTMS_NEURONAV_N_PANSS_1 SHAM
## barr, 2012_HF-RTMS_NEURONAV_N_SANS_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_N_SANS_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_P_SAPS_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_VerL_AVLT Hits_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_VisL_CFT copying_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_VisL_CFT Immediate Recall_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_VisL_CFT Delayed Recall_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_PS_DSST time (sec)_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_PS_DSST errors_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_AV_DVT time (sec)_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-A time (sec)_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-A errors_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-B time (sec)_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-B errors_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_WM_1back verbal Hits_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_WM_1back verbal Errors_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_WM_2back verbal Hits_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_WM_2back verbal Errors_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_WM_Spatial Span total_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_RPS_FAS_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_RPS_Stroop Effect score_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_SC_FOT index_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_SC_SOT index_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_SC_Faux Pax CI_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_SC_Personalizing Bias Index_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_SC_Social Perception Index_1 SHAM
## basavaraju, 2021_ITBS_NEURONAV_SC_Emotion Recognition Index_1 SHAM
## battion, 2021_ITBS_CM_T_PANSS_1 SHAM
## battion, 2021_ITBS_CM_N_SANS_1 SHAM
## blumberger, 2012_LF-RTMS_NEURONAV_P_PSYRATS_1 SHAM
## blumberger, 2012_LF-RTMS_NEURONAV_T_PANSS_1 SHAM
## blumberger, 2012_LF-RTMS_NEURONAV_P_PANSS_1 SHAM
## blumberger, 2012_LF-RTMS_NEURONAV_P_AHRS_1 SHAM
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PSYRATS_1 SHAM
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_T_PANSS_1 SHAM
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PANSS_1 SHAM
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_AHRS_1 SHAM
## bodén, 2021_ITBS_CM_N_CAIN_1 SHAM
## bose, 2018_TDCS_10-20EEG_P_SAPS_1 TDCS_10-20EEG
## bose, 2018_TDCS_10-20EEG_N_SANS_1 TDCS_10-20EEG
## bose, 2018_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG
## brunelin, 2012_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG
## brunelin, 2012_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## brunelin, 2006_LF-RTMS_10-20EEG_P_AHRS_1 SHAM
## brunelin, 2006_LF-RTMS_10-20EEG_P_SAPS_1 SHAM
## brunelin, 2006_LF-RTMS_10-20EEG_WM_MonitorSourceTask_1 SHAM
## bulubas, 2021_TDCS_10-20EEG_VisL_PFMT Total Correct Responses_1 TDCS_10-20EEG
## bulubas, 2021_TDCS_10-20EEG_VerL_PWMT Total Correct Responses_1 TDCS_10-20EEG
## bulubas, 2021_TDCS_10-20EEG_SC_EMI Correct Responses_1 TDCS_10-20EEG
## bulubas, 2021_TDCS_10-20EEG_WM_PLNB 0-back True Positive Responses_1 TDCS_10-20EEG
## bulubas, 2021_TDCS_10-20EEG_WM_PLNB 1-back True Positive Responses_1 TDCS_10-20EEG
## bulubas, 2021_TDCS_10-20EEG_WM_PLNB 2-back True Positive Responses_1 TDCS_10-20EEG
## bulubas, 2021_TDCS_10-20EEG_RPS_PCET Number Correct Responses_1 TDCS_10-20EEG
## bulubas, 2021_TDCS_10-20EEG_VisL_Short VOLT Total Correct_1 TDCS_10-20EEG
## chang-a, 2021_TACS_10-20EEG_T_PANSS_1 TACS_10-20EEG
## chang-a, 2021_TACS_10-20EEG_N_PANSS_1 TACS_10-20EEG
## chang-a, 2021_TACS_10-20EEG_N_SANS_1 TACS_10-20EEG
## chauhan, 2021_ITBS_10-20EEG_P_PANSS_1 SHAM
## chauhan, 2021_ITBS_10-20EEG_N_PANSS_1 SHAM
## chauhan, 2021_ITBS_10-20EEG_G_PANSS_1 SHAM
## chauhan, 2021_ITBS_10-20EEG_T_PANSS_1 SHAM
## chauhan, 2021_ITBS_10-20EEG_T_BPRS_1 SHAM
## de jesus, 2011_LF-RTMS_10-20EEG_T_BPRS_1 SHAM
## de jesus, 2011_LF-RTMS_10-20EEG_P_BPRS_1 SHAM
## de jesus, 2011_LF-RTMS_10-20EEG_N_BPRS_1 SHAM
## de jesus, 2011_LF-RTMS_10-20EEG_P_AHRS_1 SHAM
## dharani, 2021_HD-TDCS_10-10EEG_P_PANSS_1 SHAM
## dharani, 2021_HD-TDCS_10-10EEG_N_PANSS_1 SHAM
## dharani, 2021_HD-TDCS_10-10EEG_G_PANSS_1 SHAM
## dharani, 2021_HD-TDCS_10-10EEG_N_SANS_1 SHAM
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_SANS_1 SHAM
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_P_PANSS_1 SHAM
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_PANSS_1 SHAM
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_G_PANSS_1 SHAM
## dolfus, 2018_HF-RTMS_NEURONAV_P_AHRS_1 SHAM
## du, 2024_HF-RTMS_NEURONAV_T_BPRS_1 SHAM
## du, 2024_HF-RTMS_NEURONAV_P_BPRS_1 SHAM
## du, 2024_HF-RTMS_NEURONAV_N_BPRS_1 SHAM
## du, 2022_HF-RTMS_10-20EEG_VisL_PRM number correct_1 SHAM
## du, 2022_HF-RTMS_10-20EEG_N_SANS_1 SHAM
## du, 2022_HF-RTMS_10-20EEG_T_PANSS_1 SHAM
## du, 2022_HF-RTMS_10-20EEG_P_PANSS_1 SHAM
## du, 2022_HF-RTMS_10-20EEG_N_PANSS_1 SHAM
## du, 2022_HF-RTMS_10-20EEG_G_PANSS_1 SHAM
## farhang, 2024_TDCS_10-20EEG_WM_ letter-number sequencing_1 TDCS_10-20EEG
## fitzerald, 2008_LF-RTMS_CM_N_SANS_1 SHAM
## fitzerald, 2008_LF-RTMS_CM_P_PANSS_1 SHAM
## fitzerald, 2008_LF-RTMS_CM_N_PANSS_1 SHAM
## fitzerald, 2008_LF-RTMS_CM_T_PANSS_1 SHAM
## fitzerald-l, 2014_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG
## fitzerald-l, 2014_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG
## fitzerald-l, 2014_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## fitzerald-l, 2014_TDCS_10-20EEG_N_SANS_1 TDCS_10-20EEG
## fitzerald-bi, 2014_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG
## fitzerald-bi, 2014_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG
## fitzerald-bi, 2014_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## fitzerald-bi, 2014_TDCS_10-20EEG_N_SANS_1 TDCS_10-20EEG
## francis, 2019_HF-RTMS_CM_VerL_BACS Verbal Memory_1 SHAM
## francis, 2019_HF-RTMS_CM_WM_BACS Digit Sequencing_1 SHAM
## francis, 2019_HF-RTMS_CM_PS_BACS Semantic and Letter Fluency_1 SHAM
## francis, 2019_HF-RTMS_CM_PS_BACS Symbol Coding_1 SHAM
## francis, 2019_HF-RTMS_CM_RPS_BACS Tower of London_1 SHAM
## francis, 2019_HF-RTMS_CM_GC_BACS Composite Score_1 SHAM
## frohlich, 2016_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG
## frohlich, 2016_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## frohlich, 2016_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG
## frohlich, 2016_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG
## frohlich, 2016_TDCS_10-20EEG_G_PANSS_1 TDCS_10-20EEG
## gao, 2024_ITBS_10-20EEG_P_PANSS_1 SHAM
## gao, 2024_ITBS_10-20EEG_N_PANSS_1 SHAM
## gao, 2024_ITBS_10-20EEG_G_PANSS_1 SHAM
## gao, 2024_ITBS_10-20EEG_T_PANSS_1 SHAM
## gao, 2024_ITBS_10-20EEG_N_SANS_1 SHAM
## garcía-fernández, 2024_TDCS_10-20EEG_PS_MCCB_1 TDCS_10-20EEG
## garcía-fernández, 2024_TDCS_10-20EEG_AV_MCCB_1 TDCS_10-20EEG
## garcía-fernández, 2024_TDCS_10-20EEG_WM_MCCB_1 TDCS_10-20EEG
## garcía-fernández, 2024_TDCS_10-20EEG_VerL_MCCB_1 TDCS_10-20EEG
## garcía-fernández, 2024_TDCS_10-20EEG_VisL_MCCB_1 TDCS_10-20EEG
## garcía-fernández, 2024_TDCS_10-20EEG_RPS_MCCB_1 TDCS_10-20EEG
## garcía-fernández, 2024_TDCS_10-20EEG_SC_MCCB_1 TDCS_10-20EEG
## garg, 2016_DTMS_CM_P_PANSS_1 SHAM
## garg, 2016_DTMS_CM_N_PANSS_1 SHAM
## garg, 2016_DTMS_CM_G_PANSS_1 SHAM
## garg, 2016_DTMS_CM_T_PANSS_1 SHAM
## gogler, 2017_TDCS_10-20EEG_PS_C_1 TDCS_10-20EEG
## gogler, 2017_TDCS_10-20EEG_WM_K_1 TDCS_10-20EEG
## gogler, 2017_TDCS_10-20EEG_AV_α_1 TDCS_10-20EEG
## gomes, 2018_TDCS_10-20EEG_WM_MCCB_1 TDCS_10-20EEG
## gomes, 2018_TDCS_10-20EEG_PS_MCCB_1 TDCS_10-20EEG
## gomes, 2018_TDCS_10-20EEG_AV_MCCB_1 TDCS_10-20EEG
## gomes, 2018_TDCS_10-20EEG_VerL_MCCB_1 TDCS_10-20EEG
## gomes, 2018_TDCS_10-20EEG_VisL_MCCB_1 TDCS_10-20EEG
## gomes, 2018_TDCS_10-20EEG_RPS_MCCB_1 TDCS_10-20EEG
## gomes, 2018_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG
## gomes, 2018_TDCS_10-20EEG_N_PANSS-N_1 TDCS_10-20EEG
## gomes, 2018_TDCS_10-20EEG_G_PANSS_1 TDCS_10-20EEG
## gomes, 2018_TDCS_10-20EEG_T_PANSS-T_1 TDCS_10-20EEG
## guan, 2020_HF-RTMS_NEURONAV_T_PANSS-T_1 SHAM
## guan, 2020_HF-RTMS_NEURONAV_P_PANSS_1 SHAM
## guan, 2020_HF-RTMS_NEURONAV_N_PANSS-N_1 SHAM
## guan, 2020_HF-RTMS_NEURONAV_G_PANSS_1 SHAM
## guan, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nImmediate memory_1 SHAM
## guan, 2020_HF-RTMS_NEURONAV_WM_RBANS\r\nAttention_1 SHAM
## guan, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nVisuospatial/constructional_1 SHAM
## guan, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nDelayed memory_1 SHAM
## guan, 2020_HF-RTMS_NEURONAV_PS_RBANS\r\nLanguage_1 SHAM
## guan, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 SHAM
## guleken, 2020_HF-RTMS_CM_P_PANSS_1 SHAM
## guleken, 2020_HF-RTMS_CM_N_SANS_1 SHAM
## guleken, 2020_HF-RTMS_CM_RPS_WSCT total correct responses_1 SHAM
## guleken, 2020_HF-RTMS_CM_RPS_WSCT perseverative errors_1 SHAM
## guleken, 2020_HF-RTMS_CM_WM_DST forward_1 SHAM
## guleken, 2020_HF-RTMS_CM_WM_DST backwards_1 SHAM
## guleken, 2020_HF-RTMS_CM_RPS_Total time_1 SHAM
## guleken, 2020_HF-RTMS_CM_RPS_Total errors_1 SHAM
## guleken, 2020_HF-RTMS_CM_RPS_Stroop Interference_1 SHAM
## guse, 2013_HF-RTMS_10-20EEG_PS_TMT-A_1 SHAM
## guse, 2013_HF-RTMS_10-20EEG_RPS_TMT-B_1 SHAM
## guse, 2013_HF-RTMS_10-20EEG_RPS_WCST Accuracy_1 SHAM
## guse, 2013_HF-RTMS_10-20EEG_RPS_WCST RT_1 SHAM
## guse, 2013_HF-RTMS_10-20EEG_AV_Sel. Attention Accuracy_1 SHAM
## guse, 2013_HF-RTMS_10-20EEG_AV_Sel. Attention RT_1 SHAM
## guse, 2013_HF-RTMS_10-20EEG_AV_Div. Attention Accuracy_1 SHAM
## guse, 2013_HF-RTMS_10-20EEG_AV_Div. Attention RT_1 SHAM
## guse, 2013_HF-RTMS_10-20EEG_WM_0-back Accuracy_1 SHAM
## guse, 2013_HF-RTMS_10-20EEG_WM_0-back RT_1 SHAM
## guse, 2013_HF-RTMS_10-20EEG_WM_1-back Accuracy_1 SHAM
## guse, 2013_HF-RTMS_10-20EEG_WM_1-back RT_1 SHAM
## guse, 2013_HF-RTMS_10-20EEG_WM_2-back Accuracy_1 SHAM
## guse, 2013_HF-RTMS_10-20EEG_WM_2-back RT_1 SHAM
## hasan, 2016_HF-RTMS_10-20EEG_WM_DST z score_1 SHAM
## hasan, 2016_HF-RTMS_10-20EEG_WM_DST Forward_1 SHAM
## hasan, 2016_HF-RTMS_10-20EEG_WM_DST Backward_1 SHAM
## hasan, 2016_HF-RTMS_10-20EEG_PS_TMT-A time (s)_1 SHAM
## hasan, 2016_HF-RTMS_10-20EEG_RPS_TMT-B time (s)_1 SHAM
## hasan, 2016_HF-RTMS_10-20EEG_VerL_VLMT z score_1 SHAM
## hasan, 2016_HF-RTMS_10-20EEG_RPS_WCST z score_1 SHAM
## hasan, 2016_HF-RTMS_10-20EEG_RPS_WCST total correct score_1 SHAM
## hasan, 2016_HF-RTMS_10-20EEG_RPS_WCST total errors_1 SHAM
## hasan, 2016_HF-RTMS_10-20EEG_PS_RWT z score_1 SHAM
## holi, 2004_HF-RTMS_10-20EEG_T_PANSS_1 SHAM
## holi, 2004_HF-RTMS_10-20EEG_P_PANSS_1 SHAM
## holi, 2004_HF-RTMS_10-20EEG_N_PANSS_1 SHAM
## holi, 2004_HF-RTMS_10-20EEG_G_PANSS_1 SHAM
## hu, 2024_LF-RTMS_10-20EEG_T_PANSS_1 SHAM
## hu, 2024_LF-RTMS_10-20EEG_P_PANSS_1 SHAM
## hu, 2024_LF-RTMS_10-20EEG_N_PANSS_1 SHAM
## hu, 2024_LF-RTMS_10-20EEG_G_PANSS_1 SHAM
## hu, 2024_LF-RTMS_10-20EEG_PS_TMT-A_1 SHAM
## hu, 2024_LF-RTMS_10-20EEG_PS_BACS Symbol Coding_1 SHAM
## hu, 2024_LF-RTMS_10-20EEG_PS_Category Fluency_1 SHAM
## hu, 2024_LF-RTMS_10-20EEG_AV_CPT-IP_1 SHAM
## hu, 2024_LF-RTMS_10-20EEG_WM_WMS-3 spatial span_1 SHAM
## hu, 2024_LF-RTMS_10-20EEG_VerL_HVLT-R_1 SHAM
## hu, 2024_LF-RTMS_10-20EEG_VisL_BVMT-R_1 SHAM
## hu, 2024_LF-RTMS_10-20EEG_RPS_NAB_1 SHAM
## hu, 2023_LF-RTMS_10-10EEG_T_PANSS_1 SHAM
## hu, 2023_LF-RTMS_10-10EEG_P_PANSS_1 SHAM
## hu, 2023_LF-RTMS_10-10EEG_N_PANSS_1 SHAM
## hu, 2023_LF-RTMS_10-10EEG_G_PANSS_1 SHAM
## hu, 2023_LF-RTMS_10-10EEG_GC_MCCB-T_1 SHAM
## hu, 2023_LF-RTMS_10-10EEG_PS_MCCB_1 SHAM
## hu, 2023_LF-RTMS_10-10EEG_AV_MCCB_1 SHAM
## hu, 2023_LF-RTMS_10-10EEG_WM_MCCB_1 SHAM
## hu, 2023_LF-RTMS_10-10EEG_VerL_MCCB_1 SHAM
## hu, 2023_LF-RTMS_10-10EEG_VisL_MCCB_1 SHAM
## hu, 2023_LF-RTMS_10-10EEG_RPS_MCCB_1 SHAM
## hu, 2023_LF-RTMS_10-10EEG_SC_MCCB_1 SHAM
## huang, 2016_HF-RTMS_CM_P_PANSS_1 SHAM
## huang, 2016_HF-RTMS_CM_N_PANSS_1 SHAM
## huang, 2016_HF-RTMS_CM_G_PANSS_1 SHAM
## huang, 2016_HF-RTMS_CM_T_PANSS_1 SHAM
## huang, 2016_HF-RTMS_CM_RPS_WSCT total errors_1 SHAM
## jeon, 2018_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG
## jeon, 2018_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG
## jeon, 2018_TDCS_10-20EEG_G_PANSS_1 TDCS_10-20EEG
## jeon, 2018_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## jeon, 2018_TDCS_10-20EEG_PS_MCCB_1 TDCS_10-20EEG
## jeon, 2018_TDCS_10-20EEG_AV_MCCB_1 TDCS_10-20EEG
## jeon, 2018_TDCS_10-20EEG_WM_MCCB_1 TDCS_10-20EEG
## jeon, 2018_TDCS_10-20EEG_VerL_MCCB_1 TDCS_10-20EEG
## jeon, 2018_TDCS_10-20EEG_VisL_MCCB_1 TDCS_10-20EEG
## jeon, 2018_TDCS_10-20EEG_RPS_MCCB_1 TDCS_10-20EEG
## jeon, 2018_TDCS_10-20EEG_SC_MCCB_1 TDCS_10-20EEG
## jeon, 2018_TDCS_10-20EEG_GC_MCCB Composite Score_1 TDCS_10-20EEG
## jeon, 2018_TDCS_10-20EEG_RPS_WCST Perservative Responses_1 TDCS_10-20EEG
## jeon, 2018_TDCS_10-20EEG_RPS_WCST Perservative Errors_1 TDCS_10-20EEG
## jeon, 2018_TDCS_10-20EEG_RPS_WCST Categoris number_1 TDCS_10-20EEG
## jin, 2023_ITBS_NA_SC_FERT_1 SHAM
## jin, 2023_ITBS_NA_SC_HT_1 SHAM
## jin, 2023_ITBS_NA_T_PANSS_1 SHAM
## jin, 2023_ITBS_NA_P_PANSS_1 SHAM
## jin, 2023_ITBS_NA_N_PANSS_1 SHAM
## jin, 2023_ITBS_NA_G_PANSS_1 SHAM
## kang, 2024_CTBS_CM_T_PANSS_1 SHAM
## kang, 2024_CTBS_CM_P_PANSS_1 SHAM
## kang, 2024_CTBS_CM_N_PANSS_1 SHAM
## kang, 2024_CTBS_CM_G_PANSS_1 SHAM
## kang, 2024_CTBS_CM_P_AHRS_1 SHAM
## kantrowitz, 2019_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG
## kimura, 2016_HF-RTMS_10-20EEG_P_AHRS_1 SHAM
## klein, 1999_LF-RTMS_CM_P_PANSS_1 SHAM
## klein, 1999_LF-RTMS_CM_N_PANSS_1 SHAM
## klein, 1999_LF-RTMS_CM_G_PANSS_1 SHAM
## klein, 1999_LF-RTMS_CM_T_BPRS_1 SHAM
## koops, 2018_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG
## koops, 2018_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## koops, 2018_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG
## koops, 2018_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG
## koops, 2018_TDCS_10-20EEG_RPS_Stroop Interference_1 TDCS_10-20EEG
## koops, 2018_TDCS_10-20EEG_PS_TMT-A_1 TDCS_10-20EEG
## koops, 2018_TDCS_10-20EEG_RPS_TMT-B_1 TDCS_10-20EEG
## koops, 2016_CTBS_10-20EEG_P_PANSS_1 SHAM
## koops, 2016_CTBS_10-20EEG_P_AHRS_1 SHAM
## koops, 2016_CTBS_10-20EEG_P_PSYRATS_1 SHAM
## kos, 2024_TDCS_10-20EEG_N_SANS_1 TDCS_10-20EEG
## kos, 2024_TDCS_10-20EEG_N_AES_1 TDCS_10-20EEG
## kumar, 2020_HF-RTMS_CM_PANSS-N_1 SHAM
## kumar, 2020_HF-RTMS_CM_PANSS-G_1 SHAM
## li, 2024 - a_ITBS_10-20EEG_GC_MCCB_1 SHAM
## li, 2024 - a_ITBS_10-20EEG_WM_MCCB_1 SHAM
## li, 2024 - a_ITBS_10-20EEG_PANSS-P_1 SHAM
## li, 2024 - a_ITBS_10-20EEG_PANSS-N_1 SHAM
## li, 2024 - a_ITBS_10-20EEG_PANSS-G_1 SHAM
## li-b-lpc, 2024_ITBS_NEURONAV_PS_MCCB_1 SHAM
## li-b-lpc, 2024_ITBS_NEURONAV_AV_MCCB_1 SHAM
## li-b-lpc, 2024_ITBS_NEURONAV_WM_MCCB_1 SHAM
## li-b-lpc, 2024_ITBS_NEURONAV_VerL_MCCB_1 SHAM
## li-b-lpc, 2024_ITBS_NEURONAV_VisL_MCCB_1 SHAM
## li-b-lpc, 2024_ITBS_NEURONAV_RPS_MCCB_1 SHAM
## li-b-lpc, 2024_ITBS_NEURONAV_SC_MCCB_1 SHAM
## li-b-lpc, 2024_ITBS_NEURONAV_GC_MCCB_1 SHAM
## li-b-dlpfc, 2024_ITBS_NEURONAV_PS_MCCB_1 SHAM
## li-b-dlpfc, 2024_ITBS_NEURONAV_AV_MCCB_1 SHAM
## li-b-dlpfc, 2024_ITBS_NEURONAV_WM_MCCB_1 SHAM
## li-b-dlpfc, 2024_ITBS_NEURONAV_VerL_MCCB_1 SHAM
## li-b-dlpfc, 2024_ITBS_NEURONAV_VisL_MCCB_1 SHAM
## li-b-dlpfc, 2024_ITBS_NEURONAV_RPS_MCCB_1 SHAM
## li-b-dlpfc, 2024_ITBS_NEURONAV_SC_MCCB_1 SHAM
## li-b-dlpfc, 2024_ITBS_NEURONAV_GC_MCCB_1 SHAM
## lindenmayer, 2019_TDCS_10-20EEG_AHRS_1 TDCS_10-20EEG
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-T_1 TDCS_10-20EEG
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-P_1 TDCS_10-20EEG
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-N_1 TDCS_10-20EEG
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-G_1 TDCS_10-20EEG
## lindenmayer, 2019_TDCS_10-20EEG_GC_MCCB_1 TDCS_10-20EEG
## lindenmayer, 2019_TDCS_10-20EEG_PS_MCCB_1 TDCS_10-20EEG
## lindenmayer, 2019_TDCS_10-20EEG_AV_MCCB_1 TDCS_10-20EEG
## lindenmayer, 2019_TDCS_10-20EEG_WM_MCCB_1 TDCS_10-20EEG
## lindenmayer, 2019_TDCS_10-20EEG_VerL_MCCB_1 TDCS_10-20EEG
## lindenmayer, 2019_TDCS_10-20EEG_VisL_MCCB_1 TDCS_10-20EEG
## lindenmayer, 2019_TDCS_10-20EEG_RPN_MCCB_1 TDCS_10-20EEG
## lindenmayer, 2019_TDCS_10-20EEG_SC_MCCB_1 TDCS_10-20EEG
## lisoni, 2022_TDCS_10-20 EEG_PANSS-P_1 TDCS_10-20 EEG
## lisoni, 2022_TDCS_10-20 EEG_PANSS-N_1 TDCS_10-20 EEG
## lisoni, 2022_TDCS_10-20 EEG_PANSS-T_1 TDCS_10-20 EEG
## lisoni, 2022_TDCS_10-20 EEG_PANSS-G_1 TDCS_10-20 EEG
## lisoni, 2022_TDCS_10-20 EEG_GC_BACS (Composite z-scores)_1 TDCS_10-20 EEG
## lisoni, 2022_TDCS_10-20 EEG_VerL_BACS z-scores (Verbal memory)_1 TDCS_10-20 EEG
## lisoni, 2022_TDCS_10-20 EEG_WM_BACS z-scores (Digit sequencing)_1 TDCS_10-20 EEG
## lisoni, 2022_TDCS_10-20 EEG_PS_BACS z-scores (Verbal fluency)_1 TDCS_10-20 EEG
## lisoni, 2022_TDCS_10-20 EEG_PS_BACS z-scores (Symbol coding)_1 TDCS_10-20 EEG
## lisoni, 2022_TDCS_10-20 EEG_RPS_BACS z-scores (Tower of London)_1 TDCS_10-20 EEG
## liu, 2024_HF-RTMS_NA_T_PANSS_1 SHAM
## liu, 2024_HF-RTMS_NA_P_PANSS_1 SHAM
## liu, 2024_HF-RTMS_NA_N_PANSS_1 SHAM
## liu, 2024_HF-RTMS_NA_G_PANSS_1 SHAM
## liu, 2024_HF-RTMS_NA_VerL_RBANS (Immediate memory)_1 SHAM
## liu, 2024_HF-RTMS_NA_VisL_RBANS (Visual spatial structure)_1 SHAM
## liu, 2024_HF-RTMS_NA_PS_RBANS (Speech function)_1 SHAM
## liu, 2024_HF-RTMS_NA_WM_RBANS (Attention)_1 SHAM
## liu, 2024_HF-RTMS_NA_Visl_RBANS (Delayed memory)_1 SHAM
## lyu, 2024_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## lyu, 2024_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG
## lyu, 2024_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG
## lyu, 2024_TDCS_10-20EEG_G_PANSS_1 TDCS_10-20EEG
## lyu, 2024_TDCS_10-20EEG_N_SANS_1 TDCS_10-20EEG
## mao, 2023_HF-RTMS_CM_GC_RBANS_1 SHAM
## mao, 2023_HF-RTMS_CM_VerL_RBANS-Immediate Memory_1 SHAM
## mao, 2023_HF-RTMS_CM_RBANS-Visuospatial_1 SHAM
## mao, 2023_HF-RTMS_CM_VerL_RBANS-Language_1 SHAM
## mao, 2023_HF-RTMS_CM_WM_RBANS-Attention_1 SHAM
## mao, 2023_HF-RTMS_CM_VerL_RBANS-Delayed memory_1 SHAM
## mao, 2023_HF-RTMS_CM_P_AHRS_1 SHAM
## mao, 2023_HF-RTMS_CM_T_PANSS_1 SHAM
## marquardt, 2022_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG
## marquardt, 2022_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG
## marquardt, 2022_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG
## marquardt, 2022_TDCS_10-20EEG_RPS_Stroop 3 (s/RT)_1 TDCS_10-20EEG
## marquardt, 2022_TDCS_10-20EEG_RPS_Stroop 4 (s/RT)_1 TDCS_10-20EEG
## marquardt, 2022_TDCS_10-20EEG_PS_TMT-A_1 TDCS_10-20EEG
## marquardt, 2022_TDCS_10-20EEG_RPS_TMT-B_1 TDCS_10-20EEG
## mcintosh, 2004_LF-RTMS_10-20EEG_P_PANSS_1 SHAM
## mcintosh, 2004_LF-RTMS_10-20EEG_N_PANSS_1 SHAM
## mcintosh, 2004_LF-RTMS_10-20EEG_VerL_AVLT_1 SHAM
## meiron, 2021_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## meiron, 2021_TDCS_10-20EEG_WM_(verbal) WM - Accuracy_1 TDCS_10-20EEG
## meiron, 2021_TDCS_10-20EEG_WM_(verbal) WM - RT_1 TDCS_10-20EEG
## meiron, 2024_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## meiron, 2024_TDCS_10-20EEG_WM_2-BACK Acc_1 TDCS_10-20EEG
## meiron, 2024_TDCS_10-20EEG_WM_2-BACK RT_1 TDCS_10-20EEG
## mellin-tacs, 2018_TACS_10-20EEG_P_AHRS_1 TACS_10-20EEG
## mellin-tacs, 2018_TACS_10-20EEG_T_PANSS-T_1 TACS_10-20EEG
## mellin-tacs, 2018_TACS_10-20EEG_P_PANSS-P_1 TACS_10-20EEG
## mellin-tacs, 2018_TACS_10-20EEG_N_PANSS-N_1 TACS_10-20EEG
## mellin-tacs, 2018_TACS_10-20EEG_G_PANSS-G_1 TACS_10-20EEG
## mellin-tacs, 2018_TACS_10-20EEG_GC_BACS_1 TACS_10-20EEG
## mellin-tdcs, 2018_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG
## mellin-tdcs, 2018_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## mellin-tdcs, 2018_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG
## mellin-tdcs, 2018_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG
## mellin-tdcs, 2018_TDCS_10-20EEG_G_PANSS_1 TDCS_10-20EEG
## mellin-tdcs, 2018_TDCS_10-20EEG_GC_BACS_1 TDCS_10-20EEG
## moeller, 2022_DTMS_CM_T_PANSS_1 SHAM
## moeller, 2022_DTMS_CM_P_PANSS_1 SHAM
## moeller, 2022_DTMS_CM_N_PANSS_1 SHAM
## mogg, 2007_HF-RTMS_CM_VerL_HVLT immediate recall_1 SHAM
## mogg, 2007_HF-RTMS_CM_VerL_HVLT delayed recall_1 SHAM
## mogg, 2007_HF-RTMS_CM_PS_COWAT (number)_1 SHAM
## mogg, 2007_HF-RTMS_CM_RPS_Stroop RT (seconds)_1 SHAM
## mondino, 2015_TDCS_10-20EG_P_PANSS_1 TDCS_10-20EG
## mondino, 2015_TDCS_10-20EG_N_PANSS_1 TDCS_10-20EG
## mondino, 2015_TDCS_10-20EG_G_PANSS_1 TDCS_10-20EG
## mondino, 2015_TDCS_10-20EG_P_AHRS_1 TDCS_10-20EG
## novak, 2006_HF-RTMS_CM_T_PANSS_1 SHAM
## novak, 2006_HF-RTMS_CM_P_PANSS_1 SHAM
## novak, 2006_HF-RTMS_CM_N_PANSS_1 SHAM
## novak, 2006_HF-RTMS_CM_G_PANSS_1 SHAM
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_SAPS_1 SHAM
## paillere-martinot, 2017_LF-RTMS_NEURONAV_N_SANS_1 SHAM
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_AHRS_1 SHAM
## palm, 2016_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## palm, 2016_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG
## palm, 2016_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG
## palm, 2016_TDCS_10-20EEG_N_SANS_1 TDCS_10-20EEG
## palm, 2016_TDCS_10-20EEG_WM_SOPT_1 TDCS_10-20EEG
## palm, 2016_TDCS_10-20EEG_PS_TMT-A_1 TDCS_10-20EEG
## palm, 2016_TDCS_10-20EEG_RPS_TMT-B_1 TDCS_10-20EEG
## prikryl, 2007_HF-RTMS_CM_T_PANSS_1 SHAM
## prikryl, 2007_HF-RTMS_CM_P_PANSS_1 SHAM
## prikryl, 2007_HF-RTMS_CM_N_PANSS_1 SHAM
## prikryl, 2007_HF-RTMS_CM_N_SANS_1 SHAM
## prikryl, 2007_HF-RTMS_CM_P_SAPS_1 SHAM
## prikryl, 2012_HF-RTMS_CM_P_PANSS_1 SHAM
## prikryl, 2012_HF-RTMS_CM_N_PANSS_1 SHAM
## prikryl, 2012_HF-RTMS_CM_G_PANSS_1 SHAM
## prikryl, 2012_HF-RTMS_CM_T_PANSS_1 SHAM
## prikryl, 2012_HF-RTMS_CM_PS_VFT_1 SHAM
## prikryl, 2014_HF-RTMS_CM_T_PANSS_1 SHAM
## prikryl, 2014_HF-RTMS_CM_P_PANSS_1 SHAM
## prikryl, 2014_HF-RTMS_CM_N_PANSS_1 SHAM
## prikryl, 2014_HF-RTMS_CM_G_PANSS_1 SHAM
## prikryl, 2013_HF-RTMS_CM_N_SANS_1 SHAM
## prikryl, 2013_HF-RTMS_CM_P_SAPS_1 SHAM
## quan, 2015_HF-RTMS_CM_T_PANSS_1 SHAM
## quan, 2015_HF-RTMS_CM_P_PANSS_1 SHAM
## quan, 2015_HF-RTMS_CM_N_PANSS_1 SHAM
## quan, 2015_HF-RTMS_CM_G_PANSS_1 SHAM
## quan, 2015_HF-RTMS_CM_N_SANS_1 SHAM
## rabany, 2014_DTMS_CM_T_PANSS_1 SHAM
## rabany, 2014_DTMS_CM_N_PANSS_1 SHAM
## rabany, 2014_DTMS_CM_N_SANS_1 SHAM
## rabany, 2014_DTMS_CM_AV_RVP-A_1 SHAM
## rabany, 2014_DTMS_CM_AV_RVP-B_1 SHAM
## rabany, 2014_DTMS_CM_WM_SWM (Total between search errors)_1 SHAM
## rabany, 2014_DTMS_CM_WM_SWM (Strategy score)_1 SHAM
## rabany, 2014_DTMS_CM_RPS_SOC (Minimum move solutions for test trials)_1 SHAM
## rabany, 2014_DTMS_CM_RPS_SOC (Initial times for 5 move problems)_1 SHAM
## rabany, 2014_DTMS_CM_RPS_SOC (Subsequent times for 5 move problems)_1 SHAM
## rabany, 2014_DTMS_CM_PS_RTI (Mean reaction time, stages 4 and 5)_1 SHAM
## rabany, 2014_DTMS_CM_PS_RTI (Mean movement time, stages 4 and 5)_1 SHAM
## rollnik, 2000_HF-RTMS_CM_T_BPRS_1 SHAM
## rollnik, 2000_HF-RTMS_CM_PS_NCT (seconds)_1 SHAM
## rosa, 2007_LF-RTMS_10-20EEG_T_PANSS_1 SHAM
## rosa, 2007_LF-RTMS_10-20EEG_P_PANSS_1 SHAM
## rosa, 2007_LF-RTMS_10-20EEG_N_PANSS_1 SHAM
## rosa, 2007_LF-RTMS_10-20EEG_G_PANSS_1 SHAM
## rosenberg, 2012_LF-RTMS_CM_P_AHRS_1 SHAM
## saba, 2006_LF-RTMS_CM_T_PANSS_1 SHAM
## saba, 2006_LF-RTMS_CM_P_PANSS_1 SHAM
## saba, 2006_LF-RTMS_CM_N_PANSS_1 SHAM
## saba, 2006_LF-RTMS_CM_G_PANSS_1 SHAM
## schilling, 2021_TDCS_10-20EEG_WM_Verbal Working Memory Reaction Time (t-score)_1 TDCS_10-20EEG
## schilling, 2021_TDCS_10-20EEG_WM_Verbal Working Memory d-prime (z-score)_1 TDCS_10-20EEG
## schilling, 2021_TDCS_10-20EEG_RPS_Response Inhibition Reaction Time (t-score)_1 TDCS_10-20EEG
## schilling, 2021_TDCS_10-20EEG_RPS_Response Inhibition Errors (t-scores)_1 TDCS_10-20EEG
## schilling, 2021_TDCS_10-20EEG_RPS_Problem solving t-score_1 TDCS_10-20EEG
## schilling, 2021_TDCS_10-20EEG_RPS_Mental Flexibility Speed (t-score)_1 TDCS_10-20EEG
## schilling, 2021_TDCS_10-20EEG_RPS_Mental Flexibility Accuracy (t-score)_1 TDCS_10-20EEG
## singh, 2020_HF-RTMS_CM_P_PANSS_1 SHAM
## singh, 2020_HF-RTMS_CM_N_PANSS_1 SHAM
## singh, 2020_HF-RTMS_CM_N_SANS_1 SHAM
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_AHRS_1 SHAM
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_PANSS_1 SHAM
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_AHRS_1 SHAM
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_PANSS_1 SHAM
## smith, 2015_TDCS_10-20EEG_GC_MCCB_1 TDCS_10-20EEG
## smith, 2015_TDCS_10-20EEG_WM_MCCB_1 TDCS_10-20EEG
## smith, 2015_TDCS_10-20EEG_AV_MCCB_1 TDCS_10-20EEG
## smith, 2015_TDCS_10-20EEG_RPS_MCCB_1 TDCS_10-20EEG
## smith, 2015_TDCS_10-20EEG_VerL_MCCB_1 TDCS_10-20EEG
## smith, 2015_TDCS_10-20EEG_VisL_MCCB_1 TDCS_10-20EEG
## smith, 2015_TDCS_10-20EEG_PS_MCCB_1 TDCS_10-20EEG
## smith, 2015_TDCS_10-20EEG_SC_MCCB_1 TDCS_10-20EEG
## smith, 2015_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## smith, 2015_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG
## smith, 2015_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG
## smith, 2015_TDCS_10-20EEG_G_PANSS_1 TDCS_10-20EEG
## smith, 2020_TDCS_10-20EEG_GC_MCCB_1 TDCS_10-20EEG
## smith, 2020_TDCS_10-20EEG_PS_MCCB_1 TDCS_10-20EEG
## smith, 2020_TDCS_10-20EEG_AV_MCCB_1 TDCS_10-20EEG
## smith, 2020_TDCS_10-20EEG_WM_MCCB_1 TDCS_10-20EEG
## smith, 2020_TDCS_10-20EEG_VerL_MCCB_1 TDCS_10-20EEG
## smith, 2020_TDCS_10-20EEG_VisL_MCCB_1 TDCS_10-20EEG
## smith, 2020_TDCS_10-20EEG_RPS_MCCB_1 TDCS_10-20EEG
## smith, 2020_TDCS_10-20EEG_SC_MCCB_1 TDCS_10-20EEG
## smith, 2020_TDCS_10-20EEG_AV_PASAT (Number Correct)_1 TDCS_10-20EEG
## smith, 2020_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## smith, 2020_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG
## smith, 2020_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG
## su, 2023b_HF-RTMS_NEURONAV_T_PANSS_1 SHAM
## su, 2023b_HF-RTMS_NEURONAV_P_PANSS_1 SHAM
## su, 2023b_HF-RTMS_NEURONAV_N_PANSS_1 SHAM
## su, 2023b_HF-RTMS_NEURONAV_G_PANSS_1 SHAM
## su, 2022_HF-RTMS_NEURONAV_T_PANSS_1 SHAM
## su, 2022_HF-RTMS_NEURONAV_P_PANSS_1 SHAM
## su, 2022_HF-RTMS_NEURONAV_N_PANSS_1 SHAM
## su, 2022_HF-RTMS_NEURONAV_G_PANSS_1 SHAM
## tikka, 2017_CTBS_NEURONAV_P_PANSS_1 SHAM
## tikka, 2017_CTBS_NEURONAV_N_PANSS_1 SHAM
## tikka, 2017_CTBS_NEURONAV_G_PANSS_1 SHAM
## tikka, 2017_CTBS_NEURONAV_T_PANSS_1 SHAM
## tikka, 2017_CTBS_NEURONAV_RPS_Self-Monitoring Task_1 SHAM
## tikka, 2017_CTBS_NEURONAV_WM_Visual Memory Task_1 SHAM
## tyagi, 2022_CTBS_10-20EEG_P_PANSS_1 SHAM
## tyagi, 2022_CTBS_10-20EEG_N_PANSS_1 SHAM
## tyagi, 2022_CTBS_10-20EEG_T_PANSS_1 SHAM
## tyagi, 2022_CTBS_10-20EEG_G_PANSS_1 SHAM
## tyagi, 2022_CTBS_10-20EEG_P_AVHRS_1 SHAM
## tyagi, 2022_CTBS_10-20EEG_P_PSYRAT-AH_1 SHAM
## valiengo, 2020_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG
## valiengo, 2020_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG
## valiengo, 2020_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## valiengo, 2020_TDCS_10-20EEG_G_PANSS_1 TDCS_10-20EEG
## valiengo, 2020_TDCS_10-20EEG_P_AVHRS_1 TDCS_10-20EEG
## vercammen, 2011_TDCS_10-20EEG_RPS_Weather Prediction Test_1 TDCS_10-20EEG
## vergallito, 2024_ITBS_10-20EEG_T_PANSS_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_P_PANSS_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_N_PANSS_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_N_BNSS_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_GC_MCCB_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_PS_MCCB_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_AV_MCCB_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_WM_MCCB_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_VerL_MCCB_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_VisL_MCCB_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_RPS_MCCB_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_SC_MCCB_1 SHAM
## walther-lft, 2024_UNKNOWN_STANDARD_T_PANSS_1 UNKNOWN_STANDARD
## walther-lft, 2024_UNKNOWN_STANDARD_P_PANSS_1 UNKNOWN_STANDARD
## walther-lft, 2024_UNKNOWN_STANDARD_N_PANSS_1 UNKNOWN_STANDARD
## walther-lft, 2024_UNKNOWN_STANDARD_G_PANSS_1 UNKNOWN_STANDARD
## walther-lft, 2024_UNKNOWN_STANDARD_N_BNSS_1 UNKNOWN_STANDARD
## walther-itbs, 2024_ITBS_CM_T_PANSS_1 SHAM
## walther-itbs, 2024_ITBS_CM_P_PANSS_1 SHAM
## walther-itbs, 2024_ITBS_CM_N_PANSS_1 SHAM
## walther-itbs, 2024_ITBS_CM_G_PANSS_1 SHAM
## walther-itbs, 2024_ITBS_CM_N_BNSS_1 SHAM
## wang, 2020_ITBS_NEURONAV_T_PANSS_1 SHAM
## wang, 2020_ITBS_NEURONAV_P_PANSS_1 SHAM
## wang, 2020_ITBS_NEURONAV_N_PANSS_1 SHAM
## wang, 2020_ITBS_NEURONAV_G_PANSS_1 SHAM
## wang, 2020_ITBS_NEURONAV_P_SAPS_1 SHAM
## wang, 2020_ITBS_NEURONAV_N_SANS_1 SHAM
## wang, 2020_ITBS_NEURONAV_GC_MoCA_1 SHAM
## wang, 2020_ITBS_NEURONAV_PS_VFT_1 SHAM
## wang, 2020_ITBS_NEURONAV_WM_Digit span (forward)_1 SHAM
## wang, 2020_ITBS_NEURONAV_WM_Digit span (backward)_1 SHAM
## wang, 2020_ITBS_NEURONAV_RPS_Stroop Color Test_1 SHAM
## wang, 2020_ITBS_NEURONAV_RPS_Stroop Word Test_1 SHAM
## wang, 2020_ITBS_NEURONAV_RPS_Stroop Interference Test_1 SHAM
## wang, 2020_ITBS_NEURONAV_PS_TMT-A_1 SHAM
## wang, 2020_ITBS_NEURONAV_RPS_TMT-B_1 SHAM
## wang, 2022_ITBS_NEURONAV_P_PANSS_1 SHAM
## wang, 2022_ITBS_NEURONAV_N_PANSS_1 SHAM
## wang, 2022_ITBS_NEURONAV_G_PANSS_1 SHAM
## wang, 2022_ITBS_NEURONAV_T_PANSS_1 SHAM
## wang, 2022_ITBS_NEURONAV_P_SAPS_1 SHAM
## wang, 2022_ITBS_NEURONAV_N_SANS_1 SHAM
## wang, 2022_ITBS_NEURONAV_GC_MoCA_1 SHAM
## wang, 2022_ITBS_NEURONAV_WM_3-back RT_1 SHAM
## weickert, 2019_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## weickert, 2019_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG
## weickert, 2019_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG
## weickert, 2019_TDCS_10-20EEG_G_PANSS_1 TDCS_10-20EEG
## weickert, 2019_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG
## weickert, 2019_TDCS_10-20EEG_PS_BACS sc_1 TDCS_10-20EEG
## weickert, 2019_TDCS_10-20EEG_PS_TMT-A_1 TDCS_10-20EEG
## weickert, 2019_TDCS_10-20EEG_WM_LNS_1 TDCS_10-20EEG
## weickert, 2019_TDCS_10-20EEG_VerL_HVLTr_1 TDCS_10-20EEG
## weickert, 2019_TDCS_10-20EEG_VisL_BVMT_1 TDCS_10-20EEG
## weickert, 2019_TDCS_10-20EEG_RPS_NAB maze_1 TDCS_10-20EEG
## weickert, 2019_TDCS_10-20EEG_PS_fluency_1 TDCS_10-20EEG
## wen, 2021_HF-RTMS_CM_T_PANSS_1 SHAM
## wen, 2021_HF-RTMS_CM_P_PANSS_1 SHAM
## wen, 2021_HF-RTMS_CM_N_PANSS_1 SHAM
## wen, 2021_HF-RTMS_CM_G_PANSS_1 SHAM
## wen, 2021_HF-RTMS_CM_GC_RBANS-T_1 SHAM
## wen, 2021_HF-RTMS_CM_VerL_RBANS\r\nImmediate memory_1 SHAM
## wen, 2021_HF-RTMS_CM_WM_RBANS\r\nAttention_1 SHAM
## wen, 2021_HF-RTMS_CM_VisL_RBANS\r\nVisuospatial_1 SHAM
## wen, 2021_HF-RTMS_CM_VisL_RBANS\r\nDelayed memory_1 SHAM
## wen, 2021_HF-RTMS_CM_VerL_RBANS\r\nLanguage_1 SHAM
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n1 word (s)_1 SHAM
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n2 word (s)_1 SHAM
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n3 word (s)_1 SHAM
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n3 color (s)_1 SHAM
## wobrock, 2015_HF-RTMS_10-20EEG_T_PANSS_1 SHAM
## wobrock, 2015_HF-RTMS_10-20EEG_P_PANSS_1 SHAM
## wobrock, 2015_HF-RTMS_10-20EEG_N_PANSS_1 SHAM
## xie, 2023-a_LF-RTMS_10-20EEG_T_PANSS_1 SHAM
## xie, 2023-a_LF-RTMS_10-20EEG_P_PANSS_1 SHAM
## xie, 2023-a_LF-RTMS_10-20EEG_N_PANSS_1 SHAM
## xie, 2023-a_LF-RTMS_10-20EEG_G_PANSS_1 SHAM
## xie, 2023-a_LF-RTMS_10-20EEG_P_AHRS_1 SHAM
## xiu-10hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 SHAM
## xiu-10hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 SHAM
## xiu-10hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 SHAM
## xiu-10hz, 2020_HF-RTMS_NEURONAV_G_PANSS_1 SHAM
## xiu-10hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 SHAM
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nImmediate memory_1 SHAM
## xiu-10hz, 2020_HF-RTMS_NEURONAV_WM_RBANS\r\nAttention_1 SHAM
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nVisuospatial_1 SHAM
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nDelayed memory_1 SHAM
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nLanguage_1 SHAM
## xiu-20hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 SHAM
## xiu-20hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 SHAM
## xiu-20hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 SHAM
## xiu-20hz, 2020_HF-RTMS_NEURONAV_G_PANSS_1 SHAM
## xiu-20hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 SHAM
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nImmediate memory_1 SHAM
## xiu-20hz, 2020_HF-RTMS_NEURONAV_WM_RBANS\r\nAttention_1 SHAM
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nVisuospatial_1 SHAM
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nDelayed memory_1 SHAM
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nLanguage_1 SHAM
## xu, 2023_HD-TDCS_10-20EEG_T_PANSS_1 SHAM
## xu, 2023_HD-TDCS_10-20EEG_P_PANSS_1 SHAM
## xu, 2023_HD-TDCS_10-20EEG_N_PANSS_1 SHAM
## xu, 2023_HD-TDCS_10-20EEG_G_PANSS_1 SHAM
## xu, 2023_HD-TDCS_10-20EEG_GC_RBANS_1 SHAM
## ye-20hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 SHAM
## ye-20hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Immediate memory_1 SHAM
## ye-20hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Visuospatial_1 SHAM
## ye-20hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Language_1 SHAM
## ye-20hz, 2024_HF-RTMS_NEURONAV_WM_RBANS - Attention_1 SHAM
## ye-20hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Delayed memory_1 SHAM
## ye-10hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 SHAM
## ye-10hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Immediate memory_1 SHAM
## ye-10hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Visuospatial_1 SHAM
## ye-10hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Language_1 SHAM
## ye-10hz, 2024_HF-RTMS_NEURONAV_WM_RBANS - Attention_1 SHAM
## ye-10hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Delayed memory_1 SHAM
## yuanjun, 2024_LF-RTMS_10-20EEG_T_PANSS_1 SHAM
## yuanjun, 2024_LF-RTMS_10-20EEG_P_PANSS_1 SHAM
## yuanjun, 2024_LF-RTMS_10-20EEG_N_PANSS_1 SHAM
## yuanjun, 2024_LF-RTMS_10-20EEG_G_PANSS_1 SHAM
## yuanjun, 2024_LF-RTMS_10-20EEG_P_AHRS_1 SHAM
## zhai-a, 2023_HF-RTMS_NA_T_PANSS_1 SHAM
## zhang, 2022_TACS_10-20EEG_T_PANSS_1 TACS_10-20EEG
## zhang, 2022_TACS_10-20EEG_P_PANSS_1 TACS_10-20EEG
## zhang, 2022_TACS_10-20EEG_N_PANSS_1 TACS_10-20EEG
## zhang, 2022_TACS_10-20EEG_P_AHRS_1 TACS_10-20EEG
## zhao-tbs, 2014_ITBS_10-20EEG_T_PANSS_1 SHAM
## zhao-tbs, 2014_ITBS_10-20EEG_P_PANSS_1 SHAM
## zhao-tbs, 2014_ITBS_10-20EEG_N_PANSS_1 SHAM
## zhao-tbs, 2014_ITBS_10-20EEG_G_PANSS_1 SHAM
## zhao-tbs, 2014_ITBS_10-20EEG_N_SANS_1 SHAM
## zhao-20hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 SHAM
## zhao-20hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 SHAM
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 SHAM
## zhao-20hz, 2014_HF-RTMS_10-20EEG_G_PANSS_1 SHAM
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 SHAM
## zhao-10hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 SHAM
## zhao-10hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 SHAM
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 SHAM
## zhao-10hz, 2014_HF-RTMS_10-20EEG_G_PANSS_1 SHAM
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 SHAM
## zhou, 2024_HF-RTMS_10-20EEG_P_PANSS_1 SHAM
## zhou, 2024_HF-RTMS_10-20EEG_N_PANSS_1 SHAM
## zhou, 2024_HF-RTMS_10-20EEG_T_PANSS_1 SHAM
## zhou, 2024_HF-RTMS_10-20EEG_G_PANSS_1 SHAM
## zhou, 2024_HF-RTMS_10-20EEG_GC_RBANS-T_1 SHAM
## zhou, 2024_HF-RTMS_10-20EEG_VerL_RBANS\r\nImmediate memory_1 SHAM
## zhou, 2024_HF-RTMS_10-20EEG_VisL_RBANS\r\nVisuospatial_1 SHAM
## zhou, 2024_HF-RTMS_10-20EEG_VerL_RBANS\r\nLanguage_1 SHAM
## zhou, 2024_HF-RTMS_10-20EEG_WM_RBANS\r\nAttention_1 SHAM
## zhou, 2024_HF-RTMS_10-20EEG_VisL_RBANS\r\nDelayed memory_1 SHAM
## zhou, 2024_HF-RTMS_10-20EEG_RPS_SCWT \r\nInference scores_1 SHAM
## zhou, 2023_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG
## zhou, 2023_TDCS_10-20EEG_N_SANS_1 TDCS_10-20EEG
## zhou, 2023_TDCS_10-20EEG_RPS_IED total errors_1 TDCS_10-20EEG
## zhu, 2021_ITBS_CM_N_PANSS_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_T_PANSS_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_P_PANSS_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_N_PANSS_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_G_PANSS_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_N_SANS_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_PS_MCCB TMT-A_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_PS_MCCB BACS_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_PS_MCCB Fluency_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_WM_MCCB Working memory (WMS-SS)_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_VerL_MCCB Verbal learning (HVLT-R)_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_VisL_MCCB Visual learning (BVMT-R)_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_RPS_MCCB Reasoning/problem solving (NAB)_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_SC_MCCB Social cognition (MSCEIT)_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_GC_MCCB Composite score_1 SHAM
## MD
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANSS_1 2.2509
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANSS_1 2.2509
## bais, 2014 - l_LF-RTMS_10-20EEG_G_PANSS_1 2.2509
## bais, 2014 - l_LF-RTMS_10-20EEG_P_AHRS_1 2.2509
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANAS_1 2.2509
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANAS_1 2.2509
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANSS_1 2.2509
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANSS_1 2.2509
## bais, 2014 - bi_LF-RTMS_10-20EEG_G_PANSS_1 2.2509
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_AHRS_1 2.2509
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANAS_1 2.2509
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANAS_1 2.2509
## barr, 2011_HF-RTMS_NEURONAV_WM_1-back RT ms_1 0.6213
## barr, 2011_HF-RTMS_NEURONAV_WM_2-back RT ms_1 0.6213
## barr, 2011_HF-RTMS_NEURONAV_WM_3-back RT ms_1 0.6213
## barr, 2013_HF-RTMS_NEURONAV_WM_1-back RT ms Target Correct_1 0.6213
## barr, 2013_HF-RTMS_NEURONAV_WM_1-back RT ms Non Target Correct_1 0.6213
## barr, 2013_HF-RTMS_NEURONAV_WM_3-back RT ms Target Correct_1 0.6213
## barr, 2013_HF-RTMS_NEURONAV_WM_3-back RT ms Non Target Correct_1 0.6213
## barr, 2012_HF-RTMS_NEURONAV_P_PANSS_1 0.6213
## barr, 2012_HF-RTMS_NEURONAV_N_PANSS_1 0.6213
## barr, 2012_HF-RTMS_NEURONAV_N_SANS_1 0.6213
## basavaraju, 2021_ITBS_NEURONAV_N_SANS_1 0.2601
## basavaraju, 2021_ITBS_NEURONAV_P_SAPS_1 0.2601
## basavaraju, 2021_ITBS_NEURONAV_VerL_AVLT Hits_1 0.2601
## basavaraju, 2021_ITBS_NEURONAV_VisL_CFT copying_1 0.2601
## basavaraju, 2021_ITBS_NEURONAV_VisL_CFT Immediate Recall_1 0.2601
## basavaraju, 2021_ITBS_NEURONAV_VisL_CFT Delayed Recall_1 0.2601
## basavaraju, 2021_ITBS_NEURONAV_PS_DSST time (sec)_1 0.2601
## basavaraju, 2021_ITBS_NEURONAV_PS_DSST errors_1 0.2601
## basavaraju, 2021_ITBS_NEURONAV_AV_DVT time (sec)_1 0.2601
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-A time (sec)_1 0.2601
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-A errors_1 0.2601
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-B time (sec)_1 0.2601
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-B errors_1 0.2601
## basavaraju, 2021_ITBS_NEURONAV_WM_1back verbal Hits_1 0.2601
## basavaraju, 2021_ITBS_NEURONAV_WM_1back verbal Errors_1 0.2601
## basavaraju, 2021_ITBS_NEURONAV_WM_2back verbal Hits_1 0.2601
## basavaraju, 2021_ITBS_NEURONAV_WM_2back verbal Errors_1 0.2601
## basavaraju, 2021_ITBS_NEURONAV_WM_Spatial Span total_1 0.2601
## basavaraju, 2021_ITBS_NEURONAV_RPS_FAS_1 0.2601
## basavaraju, 2021_ITBS_NEURONAV_RPS_Stroop Effect score_1 0.2601
## basavaraju, 2021_ITBS_NEURONAV_SC_FOT index_1 0.2601
## basavaraju, 2021_ITBS_NEURONAV_SC_SOT index_1 0.2601
## basavaraju, 2021_ITBS_NEURONAV_SC_Faux Pax CI_1 0.2601
## basavaraju, 2021_ITBS_NEURONAV_SC_Personalizing Bias Index_1 0.2601
## basavaraju, 2021_ITBS_NEURONAV_SC_Social Perception Index_1 0.2601
## basavaraju, 2021_ITBS_NEURONAV_SC_Emotion Recognition Index_1 0.2601
## battion, 2021_ITBS_CM_T_PANSS_1 1.6035
## battion, 2021_ITBS_CM_N_SANS_1 1.6035
## blumberger, 2012_LF-RTMS_NEURONAV_P_PSYRATS_1 0.1658
## blumberger, 2012_LF-RTMS_NEURONAV_T_PANSS_1 0.1658
## blumberger, 2012_LF-RTMS_NEURONAV_P_PANSS_1 0.1658
## blumberger, 2012_LF-RTMS_NEURONAV_P_AHRS_1 0.1658
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PSYRATS_1 0.9325
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_T_PANSS_1 0.9325
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PANSS_1 0.9325
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_AHRS_1 0.9325
## bodén, 2021_ITBS_CM_N_CAIN_1 1.6035
## bose, 2018_TDCS_10-20EEG_P_SAPS_1 -0.3642
## bose, 2018_TDCS_10-20EEG_N_SANS_1 -0.3642
## bose, 2018_TDCS_10-20EEG_P_AHRS_1 -0.3642
## brunelin, 2012_TDCS_10-20EEG_P_AHRS_1 -0.3642
## brunelin, 2012_TDCS_10-20EEG_T_PANSS_1 -0.3642
## brunelin, 2006_LF-RTMS_10-20EEG_P_AHRS_1 2.2509
## brunelin, 2006_LF-RTMS_10-20EEG_P_SAPS_1 2.2509
## brunelin, 2006_LF-RTMS_10-20EEG_WM_MonitorSourceTask_1 2.2509
## bulubas, 2021_TDCS_10-20EEG_VisL_PFMT Total Correct Responses_1 -0.3642
## bulubas, 2021_TDCS_10-20EEG_VerL_PWMT Total Correct Responses_1 -0.3642
## bulubas, 2021_TDCS_10-20EEG_SC_EMI Correct Responses_1 -0.3642
## bulubas, 2021_TDCS_10-20EEG_WM_PLNB 0-back True Positive Responses_1 -0.3642
## bulubas, 2021_TDCS_10-20EEG_WM_PLNB 1-back True Positive Responses_1 -0.3642
## bulubas, 2021_TDCS_10-20EEG_WM_PLNB 2-back True Positive Responses_1 -0.3642
## bulubas, 2021_TDCS_10-20EEG_RPS_PCET Number Correct Responses_1 -0.3642
## bulubas, 2021_TDCS_10-20EEG_VisL_Short VOLT Total Correct_1 -0.3642
## chang-a, 2021_TACS_10-20EEG_T_PANSS_1 -0.9420
## chang-a, 2021_TACS_10-20EEG_N_PANSS_1 -0.9420
## chang-a, 2021_TACS_10-20EEG_N_SANS_1 -0.9420
## chauhan, 2021_ITBS_10-20EEG_P_PANSS_1 1.7055
## chauhan, 2021_ITBS_10-20EEG_N_PANSS_1 1.7055
## chauhan, 2021_ITBS_10-20EEG_G_PANSS_1 1.7055
## chauhan, 2021_ITBS_10-20EEG_T_PANSS_1 1.7055
## chauhan, 2021_ITBS_10-20EEG_T_BPRS_1 1.7055
## de jesus, 2011_LF-RTMS_10-20EEG_T_BPRS_1 2.2509
## de jesus, 2011_LF-RTMS_10-20EEG_P_BPRS_1 2.2509
## de jesus, 2011_LF-RTMS_10-20EEG_N_BPRS_1 2.2509
## de jesus, 2011_LF-RTMS_10-20EEG_P_AHRS_1 2.2509
## dharani, 2021_HD-TDCS_10-10EEG_P_PANSS_1 1.2666
## dharani, 2021_HD-TDCS_10-10EEG_N_PANSS_1 1.2666
## dharani, 2021_HD-TDCS_10-10EEG_G_PANSS_1 1.2666
## dharani, 2021_HD-TDCS_10-10EEG_N_SANS_1 1.2666
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_SANS_1 2.2509
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_P_PANSS_1 2.2509
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_PANSS_1 2.2509
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_G_PANSS_1 2.2509
## dolfus, 2018_HF-RTMS_NEURONAV_P_AHRS_1 0.6213
## du, 2024_HF-RTMS_NEURONAV_T_BPRS_1 0.6213
## du, 2024_HF-RTMS_NEURONAV_P_BPRS_1 0.6213
## du, 2024_HF-RTMS_NEURONAV_N_BPRS_1 0.6213
## du, 2022_HF-RTMS_10-20EEG_VisL_PRM number correct_1 1.1715
## du, 2022_HF-RTMS_10-20EEG_N_SANS_1 1.1715
## du, 2022_HF-RTMS_10-20EEG_T_PANSS_1 1.1715
## du, 2022_HF-RTMS_10-20EEG_P_PANSS_1 1.1715
## du, 2022_HF-RTMS_10-20EEG_N_PANSS_1 1.1715
## du, 2022_HF-RTMS_10-20EEG_G_PANSS_1 1.1715
## farhang, 2024_TDCS_10-20EEG_WM_ letter-number sequencing_1 -0.3642
## fitzerald, 2008_LF-RTMS_CM_N_SANS_1 -0.6373
## fitzerald, 2008_LF-RTMS_CM_P_PANSS_1 -0.6373
## fitzerald, 2008_LF-RTMS_CM_N_PANSS_1 -0.6373
## fitzerald, 2008_LF-RTMS_CM_T_PANSS_1 -0.6373
## fitzerald-l, 2014_TDCS_10-20EEG_P_PANSS_1 -0.3642
## fitzerald-l, 2014_TDCS_10-20EEG_N_PANSS_1 -0.3642
## fitzerald-l, 2014_TDCS_10-20EEG_T_PANSS_1 -0.3642
## fitzerald-l, 2014_TDCS_10-20EEG_N_SANS_1 -0.3642
## fitzerald-bi, 2014_TDCS_10-20EEG_P_PANSS_1 -0.3642
## fitzerald-bi, 2014_TDCS_10-20EEG_N_PANSS_1 -0.3642
## fitzerald-bi, 2014_TDCS_10-20EEG_T_PANSS_1 -0.3642
## fitzerald-bi, 2014_TDCS_10-20EEG_N_SANS_1 -0.3642
## francis, 2019_HF-RTMS_CM_VerL_BACS Verbal Memory_1 1.1276
## francis, 2019_HF-RTMS_CM_WM_BACS Digit Sequencing_1 1.1276
## francis, 2019_HF-RTMS_CM_PS_BACS Semantic and Letter Fluency_1 1.1276
## francis, 2019_HF-RTMS_CM_PS_BACS Symbol Coding_1 1.1276
## francis, 2019_HF-RTMS_CM_RPS_BACS Tower of London_1 1.1276
## francis, 2019_HF-RTMS_CM_GC_BACS Composite Score_1 1.1276
## frohlich, 2016_TDCS_10-20EEG_P_AHRS_1 -0.3642
## frohlich, 2016_TDCS_10-20EEG_T_PANSS_1 -0.3642
## frohlich, 2016_TDCS_10-20EEG_P_PANSS_1 -0.3642
## frohlich, 2016_TDCS_10-20EEG_N_PANSS_1 -0.3642
## frohlich, 2016_TDCS_10-20EEG_G_PANSS_1 -0.3642
## gao, 2024_ITBS_10-20EEG_P_PANSS_1 1.7055
## gao, 2024_ITBS_10-20EEG_N_PANSS_1 1.7055
## gao, 2024_ITBS_10-20EEG_G_PANSS_1 1.7055
## gao, 2024_ITBS_10-20EEG_T_PANSS_1 1.7055
## gao, 2024_ITBS_10-20EEG_N_SANS_1 1.7055
## garcía-fernández, 2024_TDCS_10-20EEG_PS_MCCB_1 -0.3642
## garcía-fernández, 2024_TDCS_10-20EEG_AV_MCCB_1 -0.3642
## garcía-fernández, 2024_TDCS_10-20EEG_WM_MCCB_1 -0.3642
## garcía-fernández, 2024_TDCS_10-20EEG_VerL_MCCB_1 -0.3642
## garcía-fernández, 2024_TDCS_10-20EEG_VisL_MCCB_1 -0.3642
## garcía-fernández, 2024_TDCS_10-20EEG_RPS_MCCB_1 -0.3642
## garcía-fernández, 2024_TDCS_10-20EEG_SC_MCCB_1 -0.3642
## garg, 2016_DTMS_CM_P_PANSS_1 0.1833
## garg, 2016_DTMS_CM_N_PANSS_1 0.1833
## garg, 2016_DTMS_CM_G_PANSS_1 0.1833
## garg, 2016_DTMS_CM_T_PANSS_1 0.1833
## gogler, 2017_TDCS_10-20EEG_PS_C_1 -0.3642
## gogler, 2017_TDCS_10-20EEG_WM_K_1 -0.3642
## gogler, 2017_TDCS_10-20EEG_AV_α_1 -0.3642
## gomes, 2018_TDCS_10-20EEG_WM_MCCB_1 -0.3642
## gomes, 2018_TDCS_10-20EEG_PS_MCCB_1 -0.3642
## gomes, 2018_TDCS_10-20EEG_AV_MCCB_1 -0.3642
## gomes, 2018_TDCS_10-20EEG_VerL_MCCB_1 -0.3642
## gomes, 2018_TDCS_10-20EEG_VisL_MCCB_1 -0.3642
## gomes, 2018_TDCS_10-20EEG_RPS_MCCB_1 -0.3642
## gomes, 2018_TDCS_10-20EEG_P_PANSS_1 -0.3642
## gomes, 2018_TDCS_10-20EEG_N_PANSS-N_1 -0.3642
## gomes, 2018_TDCS_10-20EEG_G_PANSS_1 -0.3642
## gomes, 2018_TDCS_10-20EEG_T_PANSS-T_1 -0.3642
## guan, 2020_HF-RTMS_NEURONAV_T_PANSS-T_1 0.6213
## guan, 2020_HF-RTMS_NEURONAV_P_PANSS_1 0.6213
## guan, 2020_HF-RTMS_NEURONAV_N_PANSS-N_1 0.6213
## guan, 2020_HF-RTMS_NEURONAV_G_PANSS_1 0.6213
## guan, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nImmediate memory_1 0.6213
## guan, 2020_HF-RTMS_NEURONAV_WM_RBANS\r\nAttention_1 0.6213
## guan, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nVisuospatial/constructional_1 0.6213
## guan, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nDelayed memory_1 0.6213
## guan, 2020_HF-RTMS_NEURONAV_PS_RBANS\r\nLanguage_1 0.6213
## guan, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 0.6213
## guleken, 2020_HF-RTMS_CM_P_PANSS_1 1.1276
## guleken, 2020_HF-RTMS_CM_N_SANS_1 1.1276
## guleken, 2020_HF-RTMS_CM_RPS_WSCT total correct responses_1 1.1276
## guleken, 2020_HF-RTMS_CM_RPS_WSCT perseverative errors_1 1.1276
## guleken, 2020_HF-RTMS_CM_WM_DST forward_1 1.1276
## guleken, 2020_HF-RTMS_CM_WM_DST backwards_1 1.1276
## guleken, 2020_HF-RTMS_CM_RPS_Total time_1 1.1276
## guleken, 2020_HF-RTMS_CM_RPS_Total errors_1 1.1276
## guleken, 2020_HF-RTMS_CM_RPS_Stroop Interference_1 1.1276
## guse, 2013_HF-RTMS_10-20EEG_PS_TMT-A_1 1.1715
## guse, 2013_HF-RTMS_10-20EEG_RPS_TMT-B_1 1.1715
## guse, 2013_HF-RTMS_10-20EEG_RPS_WCST Accuracy_1 1.1715
## guse, 2013_HF-RTMS_10-20EEG_RPS_WCST RT_1 1.1715
## guse, 2013_HF-RTMS_10-20EEG_AV_Sel. Attention Accuracy_1 1.1715
## guse, 2013_HF-RTMS_10-20EEG_AV_Sel. Attention RT_1 1.1715
## guse, 2013_HF-RTMS_10-20EEG_AV_Div. Attention Accuracy_1 1.1715
## guse, 2013_HF-RTMS_10-20EEG_AV_Div. Attention RT_1 1.1715
## guse, 2013_HF-RTMS_10-20EEG_WM_0-back Accuracy_1 1.1715
## guse, 2013_HF-RTMS_10-20EEG_WM_0-back RT_1 1.1715
## guse, 2013_HF-RTMS_10-20EEG_WM_1-back Accuracy_1 1.1715
## guse, 2013_HF-RTMS_10-20EEG_WM_1-back RT_1 1.1715
## guse, 2013_HF-RTMS_10-20EEG_WM_2-back Accuracy_1 1.1715
## guse, 2013_HF-RTMS_10-20EEG_WM_2-back RT_1 1.1715
## hasan, 2016_HF-RTMS_10-20EEG_WM_DST z score_1 1.1715
## hasan, 2016_HF-RTMS_10-20EEG_WM_DST Forward_1 1.1715
## hasan, 2016_HF-RTMS_10-20EEG_WM_DST Backward_1 1.1715
## hasan, 2016_HF-RTMS_10-20EEG_PS_TMT-A time (s)_1 1.1715
## hasan, 2016_HF-RTMS_10-20EEG_RPS_TMT-B time (s)_1 1.1715
## hasan, 2016_HF-RTMS_10-20EEG_VerL_VLMT z score_1 1.1715
## hasan, 2016_HF-RTMS_10-20EEG_RPS_WCST z score_1 1.1715
## hasan, 2016_HF-RTMS_10-20EEG_RPS_WCST total correct score_1 1.1715
## hasan, 2016_HF-RTMS_10-20EEG_RPS_WCST total errors_1 1.1715
## hasan, 2016_HF-RTMS_10-20EEG_PS_RWT z score_1 1.1715
## holi, 2004_HF-RTMS_10-20EEG_T_PANSS_1 1.1715
## holi, 2004_HF-RTMS_10-20EEG_P_PANSS_1 1.1715
## holi, 2004_HF-RTMS_10-20EEG_N_PANSS_1 1.1715
## holi, 2004_HF-RTMS_10-20EEG_G_PANSS_1 1.1715
## hu, 2024_LF-RTMS_10-20EEG_T_PANSS_1 2.2509
## hu, 2024_LF-RTMS_10-20EEG_P_PANSS_1 2.2509
## hu, 2024_LF-RTMS_10-20EEG_N_PANSS_1 2.2509
## hu, 2024_LF-RTMS_10-20EEG_G_PANSS_1 2.2509
## hu, 2024_LF-RTMS_10-20EEG_PS_TMT-A_1 2.2509
## hu, 2024_LF-RTMS_10-20EEG_PS_BACS Symbol Coding_1 2.2509
## hu, 2024_LF-RTMS_10-20EEG_PS_Category Fluency_1 2.2509
## hu, 2024_LF-RTMS_10-20EEG_AV_CPT-IP_1 2.2509
## hu, 2024_LF-RTMS_10-20EEG_WM_WMS-3 spatial span_1 2.2509
## hu, 2024_LF-RTMS_10-20EEG_VerL_HVLT-R_1 2.2509
## hu, 2024_LF-RTMS_10-20EEG_VisL_BVMT-R_1 2.2509
## hu, 2024_LF-RTMS_10-20EEG_RPS_NAB_1 2.2509
## hu, 2023_LF-RTMS_10-10EEG_T_PANSS_1 2.7018
## hu, 2023_LF-RTMS_10-10EEG_P_PANSS_1 2.7018
## hu, 2023_LF-RTMS_10-10EEG_N_PANSS_1 2.7018
## hu, 2023_LF-RTMS_10-10EEG_G_PANSS_1 2.7018
## hu, 2023_LF-RTMS_10-10EEG_GC_MCCB-T_1 2.7018
## hu, 2023_LF-RTMS_10-10EEG_PS_MCCB_1 2.7018
## hu, 2023_LF-RTMS_10-10EEG_AV_MCCB_1 2.7018
## hu, 2023_LF-RTMS_10-10EEG_WM_MCCB_1 2.7018
## hu, 2023_LF-RTMS_10-10EEG_VerL_MCCB_1 2.7018
## hu, 2023_LF-RTMS_10-10EEG_VisL_MCCB_1 2.7018
## hu, 2023_LF-RTMS_10-10EEG_RPS_MCCB_1 2.7018
## hu, 2023_LF-RTMS_10-10EEG_SC_MCCB_1 2.7018
## huang, 2016_HF-RTMS_CM_P_PANSS_1 1.1276
## huang, 2016_HF-RTMS_CM_N_PANSS_1 1.1276
## huang, 2016_HF-RTMS_CM_G_PANSS_1 1.1276
## huang, 2016_HF-RTMS_CM_T_PANSS_1 1.1276
## huang, 2016_HF-RTMS_CM_RPS_WSCT total errors_1 1.1276
## jeon, 2018_TDCS_10-20EEG_P_PANSS_1 -0.3642
## jeon, 2018_TDCS_10-20EEG_N_PANSS_1 -0.3642
## jeon, 2018_TDCS_10-20EEG_G_PANSS_1 -0.3642
## jeon, 2018_TDCS_10-20EEG_T_PANSS_1 -0.3642
## jeon, 2018_TDCS_10-20EEG_PS_MCCB_1 -0.3642
## jeon, 2018_TDCS_10-20EEG_AV_MCCB_1 -0.3642
## jeon, 2018_TDCS_10-20EEG_WM_MCCB_1 -0.3642
## jeon, 2018_TDCS_10-20EEG_VerL_MCCB_1 -0.3642
## jeon, 2018_TDCS_10-20EEG_VisL_MCCB_1 -0.3642
## jeon, 2018_TDCS_10-20EEG_RPS_MCCB_1 -0.3642
## jeon, 2018_TDCS_10-20EEG_SC_MCCB_1 -0.3642
## jeon, 2018_TDCS_10-20EEG_GC_MCCB Composite Score_1 -0.3642
## jeon, 2018_TDCS_10-20EEG_RPS_WCST Perservative Responses_1 -0.3642
## jeon, 2018_TDCS_10-20EEG_RPS_WCST Perservative Errors_1 -0.3642
## jeon, 2018_TDCS_10-20EEG_RPS_WCST Categoris number_1 -0.3642
## jin, 2023_ITBS_NA_SC_FERT_1 0.8017
## jin, 2023_ITBS_NA_SC_HT_1 0.8017
## jin, 2023_ITBS_NA_T_PANSS_1 0.8017
## jin, 2023_ITBS_NA_P_PANSS_1 0.8017
## jin, 2023_ITBS_NA_N_PANSS_1 0.8017
## jin, 2023_ITBS_NA_G_PANSS_1 0.8017
## kang, 2024_CTBS_CM_T_PANSS_1 1.9362
## kang, 2024_CTBS_CM_P_PANSS_1 1.9362
## kang, 2024_CTBS_CM_N_PANSS_1 1.9362
## kang, 2024_CTBS_CM_G_PANSS_1 1.9362
## kang, 2024_CTBS_CM_P_AHRS_1 1.9362
## kantrowitz, 2019_TDCS_10-20EEG_P_AHRS_1 -0.3642
## kimura, 2016_HF-RTMS_10-20EEG_P_AHRS_1 1.1715
## klein, 1999_LF-RTMS_CM_P_PANSS_1 -0.6373
## klein, 1999_LF-RTMS_CM_N_PANSS_1 -0.6373
## klein, 1999_LF-RTMS_CM_G_PANSS_1 -0.6373
## klein, 1999_LF-RTMS_CM_T_BPRS_1 -0.6373
## koops, 2018_TDCS_10-20EEG_P_AHRS_1 -0.3642
## koops, 2018_TDCS_10-20EEG_T_PANSS_1 -0.3642
## koops, 2018_TDCS_10-20EEG_P_PANSS_1 -0.3642
## koops, 2018_TDCS_10-20EEG_N_PANSS_1 -0.3642
## koops, 2018_TDCS_10-20EEG_RPS_Stroop Interference_1 -0.3642
## koops, 2018_TDCS_10-20EEG_PS_TMT-A_1 -0.3642
## koops, 2018_TDCS_10-20EEG_RPS_TMT-B_1 -0.3642
## koops, 2016_CTBS_10-20EEG_P_PANSS_1 -2.2587
## koops, 2016_CTBS_10-20EEG_P_AHRS_1 -2.2587
## koops, 2016_CTBS_10-20EEG_P_PSYRATS_1 -2.2587
## kos, 2024_TDCS_10-20EEG_N_SANS_1 -0.3642
## kos, 2024_TDCS_10-20EEG_N_AES_1 -0.3642
## kumar, 2020_HF-RTMS_CM_PANSS-N_1 1.1276
## kumar, 2020_HF-RTMS_CM_PANSS-G_1 1.1276
## li, 2024 - a_ITBS_10-20EEG_GC_MCCB_1 1.7055
## li, 2024 - a_ITBS_10-20EEG_WM_MCCB_1 1.7055
## li, 2024 - a_ITBS_10-20EEG_PANSS-P_1 1.7055
## li, 2024 - a_ITBS_10-20EEG_PANSS-N_1 1.7055
## li, 2024 - a_ITBS_10-20EEG_PANSS-G_1 1.7055
## li-b-lpc, 2024_ITBS_NEURONAV_PS_MCCB_1 0.2601
## li-b-lpc, 2024_ITBS_NEURONAV_AV_MCCB_1 0.2601
## li-b-lpc, 2024_ITBS_NEURONAV_WM_MCCB_1 0.2601
## li-b-lpc, 2024_ITBS_NEURONAV_VerL_MCCB_1 0.2601
## li-b-lpc, 2024_ITBS_NEURONAV_VisL_MCCB_1 0.2601
## li-b-lpc, 2024_ITBS_NEURONAV_RPS_MCCB_1 0.2601
## li-b-lpc, 2024_ITBS_NEURONAV_SC_MCCB_1 0.2601
## li-b-lpc, 2024_ITBS_NEURONAV_GC_MCCB_1 0.2601
## li-b-dlpfc, 2024_ITBS_NEURONAV_PS_MCCB_1 0.2601
## li-b-dlpfc, 2024_ITBS_NEURONAV_AV_MCCB_1 0.2601
## li-b-dlpfc, 2024_ITBS_NEURONAV_WM_MCCB_1 0.2601
## li-b-dlpfc, 2024_ITBS_NEURONAV_VerL_MCCB_1 0.2601
## li-b-dlpfc, 2024_ITBS_NEURONAV_VisL_MCCB_1 0.2601
## li-b-dlpfc, 2024_ITBS_NEURONAV_RPS_MCCB_1 0.2601
## li-b-dlpfc, 2024_ITBS_NEURONAV_SC_MCCB_1 0.2601
## li-b-dlpfc, 2024_ITBS_NEURONAV_GC_MCCB_1 0.2601
## lindenmayer, 2019_TDCS_10-20EEG_AHRS_1 -0.3642
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-T_1 -0.3642
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-P_1 -0.3642
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-N_1 -0.3642
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-G_1 -0.3642
## lindenmayer, 2019_TDCS_10-20EEG_GC_MCCB_1 -0.3642
## lindenmayer, 2019_TDCS_10-20EEG_PS_MCCB_1 -0.3642
## lindenmayer, 2019_TDCS_10-20EEG_AV_MCCB_1 -0.3642
## lindenmayer, 2019_TDCS_10-20EEG_WM_MCCB_1 -0.3642
## lindenmayer, 2019_TDCS_10-20EEG_VerL_MCCB_1 -0.3642
## lindenmayer, 2019_TDCS_10-20EEG_VisL_MCCB_1 -0.3642
## lindenmayer, 2019_TDCS_10-20EEG_RPN_MCCB_1 -0.3642
## lindenmayer, 2019_TDCS_10-20EEG_SC_MCCB_1 -0.3642
## lisoni, 2022_TDCS_10-20 EEG_PANSS-P_1 -1.3936
## lisoni, 2022_TDCS_10-20 EEG_PANSS-N_1 -1.3936
## lisoni, 2022_TDCS_10-20 EEG_PANSS-T_1 -1.3936
## lisoni, 2022_TDCS_10-20 EEG_PANSS-G_1 -1.3936
## lisoni, 2022_TDCS_10-20 EEG_GC_BACS (Composite z-scores)_1 -1.3936
## lisoni, 2022_TDCS_10-20 EEG_VerL_BACS z-scores (Verbal memory)_1 -1.3936
## lisoni, 2022_TDCS_10-20 EEG_WM_BACS z-scores (Digit sequencing)_1 -1.3936
## lisoni, 2022_TDCS_10-20 EEG_PS_BACS z-scores (Verbal fluency)_1 -1.3936
## lisoni, 2022_TDCS_10-20 EEG_PS_BACS z-scores (Symbol coding)_1 -1.3936
## lisoni, 2022_TDCS_10-20 EEG_RPS_BACS z-scores (Tower of London)_1 -1.3936
## liu, 2024_HF-RTMS_NA_T_PANSS_1 0.3003
## liu, 2024_HF-RTMS_NA_P_PANSS_1 0.3003
## liu, 2024_HF-RTMS_NA_N_PANSS_1 0.3003
## liu, 2024_HF-RTMS_NA_G_PANSS_1 0.3003
## liu, 2024_HF-RTMS_NA_VerL_RBANS (Immediate memory)_1 0.3003
## liu, 2024_HF-RTMS_NA_VisL_RBANS (Visual spatial structure)_1 0.3003
## liu, 2024_HF-RTMS_NA_PS_RBANS (Speech function)_1 0.3003
## liu, 2024_HF-RTMS_NA_WM_RBANS (Attention)_1 0.3003
## liu, 2024_HF-RTMS_NA_Visl_RBANS (Delayed memory)_1 0.3003
## lyu, 2024_TDCS_10-20EEG_T_PANSS_1 -0.3642
## lyu, 2024_TDCS_10-20EEG_P_PANSS_1 -0.3642
## lyu, 2024_TDCS_10-20EEG_N_PANSS_1 -0.3642
## lyu, 2024_TDCS_10-20EEG_G_PANSS_1 -0.3642
## lyu, 2024_TDCS_10-20EEG_N_SANS_1 -0.3642
## mao, 2023_HF-RTMS_CM_GC_RBANS_1 1.1276
## mao, 2023_HF-RTMS_CM_VerL_RBANS-Immediate Memory_1 1.1276
## mao, 2023_HF-RTMS_CM_RBANS-Visuospatial_1 1.1276
## mao, 2023_HF-RTMS_CM_VerL_RBANS-Language_1 1.1276
## mao, 2023_HF-RTMS_CM_WM_RBANS-Attention_1 1.1276
## mao, 2023_HF-RTMS_CM_VerL_RBANS-Delayed memory_1 1.1276
## mao, 2023_HF-RTMS_CM_P_AHRS_1 1.1276
## mao, 2023_HF-RTMS_CM_T_PANSS_1 1.1276
## marquardt, 2022_TDCS_10-20EEG_P_PANSS_1 -0.3642
## marquardt, 2022_TDCS_10-20EEG_N_PANSS_1 -0.3642
## marquardt, 2022_TDCS_10-20EEG_P_AHRS_1 -0.3642
## marquardt, 2022_TDCS_10-20EEG_RPS_Stroop 3 (s/RT)_1 -0.3642
## marquardt, 2022_TDCS_10-20EEG_RPS_Stroop 4 (s/RT)_1 -0.3642
## marquardt, 2022_TDCS_10-20EEG_PS_TMT-A_1 -0.3642
## marquardt, 2022_TDCS_10-20EEG_RPS_TMT-B_1 -0.3642
## mcintosh, 2004_LF-RTMS_10-20EEG_P_PANSS_1 2.2509
## mcintosh, 2004_LF-RTMS_10-20EEG_N_PANSS_1 2.2509
## mcintosh, 2004_LF-RTMS_10-20EEG_VerL_AVLT_1 2.2509
## meiron, 2021_TDCS_10-20EEG_T_PANSS_1 -0.3642
## meiron, 2021_TDCS_10-20EEG_WM_(verbal) WM - Accuracy_1 -0.3642
## meiron, 2021_TDCS_10-20EEG_WM_(verbal) WM - RT_1 -0.3642
## meiron, 2024_TDCS_10-20EEG_T_PANSS_1 -0.3642
## meiron, 2024_TDCS_10-20EEG_WM_2-BACK Acc_1 -0.3642
## meiron, 2024_TDCS_10-20EEG_WM_2-BACK RT_1 -0.3642
## mellin-tacs, 2018_TACS_10-20EEG_P_AHRS_1 -0.9420
## mellin-tacs, 2018_TACS_10-20EEG_T_PANSS-T_1 -0.9420
## mellin-tacs, 2018_TACS_10-20EEG_P_PANSS-P_1 -0.9420
## mellin-tacs, 2018_TACS_10-20EEG_N_PANSS-N_1 -0.9420
## mellin-tacs, 2018_TACS_10-20EEG_G_PANSS-G_1 -0.9420
## mellin-tacs, 2018_TACS_10-20EEG_GC_BACS_1 -0.9420
## mellin-tdcs, 2018_TDCS_10-20EEG_P_AHRS_1 -0.3642
## mellin-tdcs, 2018_TDCS_10-20EEG_T_PANSS_1 -0.3642
## mellin-tdcs, 2018_TDCS_10-20EEG_P_PANSS_1 -0.3642
## mellin-tdcs, 2018_TDCS_10-20EEG_N_PANSS_1 -0.3642
## mellin-tdcs, 2018_TDCS_10-20EEG_G_PANSS_1 -0.3642
## mellin-tdcs, 2018_TDCS_10-20EEG_GC_BACS_1 -0.3642
## moeller, 2022_DTMS_CM_T_PANSS_1 0.1833
## moeller, 2022_DTMS_CM_P_PANSS_1 0.1833
## moeller, 2022_DTMS_CM_N_PANSS_1 0.1833
## mogg, 2007_HF-RTMS_CM_VerL_HVLT immediate recall_1 1.1276
## mogg, 2007_HF-RTMS_CM_VerL_HVLT delayed recall_1 1.1276
## mogg, 2007_HF-RTMS_CM_PS_COWAT (number)_1 1.1276
## mogg, 2007_HF-RTMS_CM_RPS_Stroop RT (seconds)_1 1.1276
## mondino, 2015_TDCS_10-20EG_P_PANSS_1 -1.9475
## mondino, 2015_TDCS_10-20EG_N_PANSS_1 -1.9475
## mondino, 2015_TDCS_10-20EG_G_PANSS_1 -1.9475
## mondino, 2015_TDCS_10-20EG_P_AHRS_1 -1.9475
## novak, 2006_HF-RTMS_CM_T_PANSS_1 1.1276
## novak, 2006_HF-RTMS_CM_P_PANSS_1 1.1276
## novak, 2006_HF-RTMS_CM_N_PANSS_1 1.1276
## novak, 2006_HF-RTMS_CM_G_PANSS_1 1.1276
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_SAPS_1 0.1658
## paillere-martinot, 2017_LF-RTMS_NEURONAV_N_SANS_1 0.1658
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_AHRS_1 0.1658
## palm, 2016_TDCS_10-20EEG_T_PANSS_1 -0.3642
## palm, 2016_TDCS_10-20EEG_P_PANSS_1 -0.3642
## palm, 2016_TDCS_10-20EEG_N_PANSS_1 -0.3642
## palm, 2016_TDCS_10-20EEG_N_SANS_1 -0.3642
## palm, 2016_TDCS_10-20EEG_WM_SOPT_1 -0.3642
## palm, 2016_TDCS_10-20EEG_PS_TMT-A_1 -0.3642
## palm, 2016_TDCS_10-20EEG_RPS_TMT-B_1 -0.3642
## prikryl, 2007_HF-RTMS_CM_T_PANSS_1 1.1276
## prikryl, 2007_HF-RTMS_CM_P_PANSS_1 1.1276
## prikryl, 2007_HF-RTMS_CM_N_PANSS_1 1.1276
## prikryl, 2007_HF-RTMS_CM_N_SANS_1 1.1276
## prikryl, 2007_HF-RTMS_CM_P_SAPS_1 1.1276
## prikryl, 2012_HF-RTMS_CM_P_PANSS_1 1.1276
## prikryl, 2012_HF-RTMS_CM_N_PANSS_1 1.1276
## prikryl, 2012_HF-RTMS_CM_G_PANSS_1 1.1276
## prikryl, 2012_HF-RTMS_CM_T_PANSS_1 1.1276
## prikryl, 2012_HF-RTMS_CM_PS_VFT_1 1.1276
## prikryl, 2014_HF-RTMS_CM_T_PANSS_1 1.1276
## prikryl, 2014_HF-RTMS_CM_P_PANSS_1 1.1276
## prikryl, 2014_HF-RTMS_CM_N_PANSS_1 1.1276
## prikryl, 2014_HF-RTMS_CM_G_PANSS_1 1.1276
## prikryl, 2013_HF-RTMS_CM_N_SANS_1 1.1276
## prikryl, 2013_HF-RTMS_CM_P_SAPS_1 1.1276
## quan, 2015_HF-RTMS_CM_T_PANSS_1 1.1276
## quan, 2015_HF-RTMS_CM_P_PANSS_1 1.1276
## quan, 2015_HF-RTMS_CM_N_PANSS_1 1.1276
## quan, 2015_HF-RTMS_CM_G_PANSS_1 1.1276
## quan, 2015_HF-RTMS_CM_N_SANS_1 1.1276
## rabany, 2014_DTMS_CM_T_PANSS_1 0.1833
## rabany, 2014_DTMS_CM_N_PANSS_1 0.1833
## rabany, 2014_DTMS_CM_N_SANS_1 0.1833
## rabany, 2014_DTMS_CM_AV_RVP-A_1 0.1833
## rabany, 2014_DTMS_CM_AV_RVP-B_1 0.1833
## rabany, 2014_DTMS_CM_WM_SWM (Total between search errors)_1 0.1833
## rabany, 2014_DTMS_CM_WM_SWM (Strategy score)_1 0.1833
## rabany, 2014_DTMS_CM_RPS_SOC (Minimum move solutions for test trials)_1 0.1833
## rabany, 2014_DTMS_CM_RPS_SOC (Initial times for 5 move problems)_1 0.1833
## rabany, 2014_DTMS_CM_RPS_SOC (Subsequent times for 5 move problems)_1 0.1833
## rabany, 2014_DTMS_CM_PS_RTI (Mean reaction time, stages 4 and 5)_1 0.1833
## rabany, 2014_DTMS_CM_PS_RTI (Mean movement time, stages 4 and 5)_1 0.1833
## rollnik, 2000_HF-RTMS_CM_T_BPRS_1 1.1276
## rollnik, 2000_HF-RTMS_CM_PS_NCT (seconds)_1 1.1276
## rosa, 2007_LF-RTMS_10-20EEG_T_PANSS_1 2.2509
## rosa, 2007_LF-RTMS_10-20EEG_P_PANSS_1 2.2509
## rosa, 2007_LF-RTMS_10-20EEG_N_PANSS_1 2.2509
## rosa, 2007_LF-RTMS_10-20EEG_G_PANSS_1 2.2509
## rosenberg, 2012_LF-RTMS_CM_P_AHRS_1 -0.6373
## saba, 2006_LF-RTMS_CM_T_PANSS_1 -0.6373
## saba, 2006_LF-RTMS_CM_P_PANSS_1 -0.6373
## saba, 2006_LF-RTMS_CM_N_PANSS_1 -0.6373
## saba, 2006_LF-RTMS_CM_G_PANSS_1 -0.6373
## schilling, 2021_TDCS_10-20EEG_WM_Verbal Working Memory Reaction Time (t-score)_1 -0.3642
## schilling, 2021_TDCS_10-20EEG_WM_Verbal Working Memory d-prime (z-score)_1 -0.3642
## schilling, 2021_TDCS_10-20EEG_RPS_Response Inhibition Reaction Time (t-score)_1 -0.3642
## schilling, 2021_TDCS_10-20EEG_RPS_Response Inhibition Errors (t-scores)_1 -0.3642
## schilling, 2021_TDCS_10-20EEG_RPS_Problem solving t-score_1 -0.3642
## schilling, 2021_TDCS_10-20EEG_RPS_Mental Flexibility Speed (t-score)_1 -0.3642
## schilling, 2021_TDCS_10-20EEG_RPS_Mental Flexibility Accuracy (t-score)_1 -0.3642
## singh, 2020_HF-RTMS_CM_P_PANSS_1 1.1276
## singh, 2020_HF-RTMS_CM_N_PANSS_1 1.1276
## singh, 2020_HF-RTMS_CM_N_SANS_1 1.1276
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_AHRS_1 0.1658
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_PANSS_1 0.1658
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_AHRS_1 2.2509
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_PANSS_1 2.2509
## smith, 2015_TDCS_10-20EEG_GC_MCCB_1 -0.3642
## smith, 2015_TDCS_10-20EEG_WM_MCCB_1 -0.3642
## smith, 2015_TDCS_10-20EEG_AV_MCCB_1 -0.3642
## smith, 2015_TDCS_10-20EEG_RPS_MCCB_1 -0.3642
## smith, 2015_TDCS_10-20EEG_VerL_MCCB_1 -0.3642
## smith, 2015_TDCS_10-20EEG_VisL_MCCB_1 -0.3642
## smith, 2015_TDCS_10-20EEG_PS_MCCB_1 -0.3642
## smith, 2015_TDCS_10-20EEG_SC_MCCB_1 -0.3642
## smith, 2015_TDCS_10-20EEG_T_PANSS_1 -0.3642
## smith, 2015_TDCS_10-20EEG_P_PANSS_1 -0.3642
## smith, 2015_TDCS_10-20EEG_N_PANSS_1 -0.3642
## smith, 2015_TDCS_10-20EEG_G_PANSS_1 -0.3642
## smith, 2020_TDCS_10-20EEG_GC_MCCB_1 -0.3642
## smith, 2020_TDCS_10-20EEG_PS_MCCB_1 -0.3642
## smith, 2020_TDCS_10-20EEG_AV_MCCB_1 -0.3642
## smith, 2020_TDCS_10-20EEG_WM_MCCB_1 -0.3642
## smith, 2020_TDCS_10-20EEG_VerL_MCCB_1 -0.3642
## smith, 2020_TDCS_10-20EEG_VisL_MCCB_1 -0.3642
## smith, 2020_TDCS_10-20EEG_RPS_MCCB_1 -0.3642
## smith, 2020_TDCS_10-20EEG_SC_MCCB_1 -0.3642
## smith, 2020_TDCS_10-20EEG_AV_PASAT (Number Correct)_1 -0.3642
## smith, 2020_TDCS_10-20EEG_T_PANSS_1 -0.3642
## smith, 2020_TDCS_10-20EEG_P_PANSS_1 -0.3642
## smith, 2020_TDCS_10-20EEG_N_PANSS_1 -0.3642
## su, 2023b_HF-RTMS_NEURONAV_T_PANSS_1 0.6213
## su, 2023b_HF-RTMS_NEURONAV_P_PANSS_1 0.6213
## su, 2023b_HF-RTMS_NEURONAV_N_PANSS_1 0.6213
## su, 2023b_HF-RTMS_NEURONAV_G_PANSS_1 0.6213
## su, 2022_HF-RTMS_NEURONAV_T_PANSS_1 0.6213
## su, 2022_HF-RTMS_NEURONAV_P_PANSS_1 0.6213
## su, 2022_HF-RTMS_NEURONAV_N_PANSS_1 0.6213
## su, 2022_HF-RTMS_NEURONAV_G_PANSS_1 0.6213
## tikka, 2017_CTBS_NEURONAV_P_PANSS_1 -0.1797
## tikka, 2017_CTBS_NEURONAV_N_PANSS_1 -0.1797
## tikka, 2017_CTBS_NEURONAV_G_PANSS_1 -0.1797
## tikka, 2017_CTBS_NEURONAV_T_PANSS_1 -0.1797
## tikka, 2017_CTBS_NEURONAV_RPS_Self-Monitoring Task_1 -0.1797
## tikka, 2017_CTBS_NEURONAV_WM_Visual Memory Task_1 -0.1797
## tyagi, 2022_CTBS_10-20EEG_P_PANSS_1 -2.2587
## tyagi, 2022_CTBS_10-20EEG_N_PANSS_1 -2.2587
## tyagi, 2022_CTBS_10-20EEG_T_PANSS_1 -2.2587
## tyagi, 2022_CTBS_10-20EEG_G_PANSS_1 -2.2587
## tyagi, 2022_CTBS_10-20EEG_P_AVHRS_1 -2.2587
## tyagi, 2022_CTBS_10-20EEG_P_PSYRAT-AH_1 -2.2587
## valiengo, 2020_TDCS_10-20EEG_N_PANSS_1 -0.3642
## valiengo, 2020_TDCS_10-20EEG_P_PANSS_1 -0.3642
## valiengo, 2020_TDCS_10-20EEG_T_PANSS_1 -0.3642
## valiengo, 2020_TDCS_10-20EEG_G_PANSS_1 -0.3642
## valiengo, 2020_TDCS_10-20EEG_P_AVHRS_1 -0.3642
## vercammen, 2011_TDCS_10-20EEG_RPS_Weather Prediction Test_1 -0.3642
## vergallito, 2024_ITBS_10-20EEG_T_PANSS_1 1.7055
## vergallito, 2024_ITBS_10-20EEG_P_PANSS_1 1.7055
## vergallito, 2024_ITBS_10-20EEG_N_PANSS_1 1.7055
## vergallito, 2024_ITBS_10-20EEG_N_BNSS_1 1.7055
## vergallito, 2024_ITBS_10-20EEG_GC_MCCB_1 1.7055
## vergallito, 2024_ITBS_10-20EEG_PS_MCCB_1 1.7055
## vergallito, 2024_ITBS_10-20EEG_AV_MCCB_1 1.7055
## vergallito, 2024_ITBS_10-20EEG_WM_MCCB_1 1.7055
## vergallito, 2024_ITBS_10-20EEG_VerL_MCCB_1 1.7055
## vergallito, 2024_ITBS_10-20EEG_VisL_MCCB_1 1.7055
## vergallito, 2024_ITBS_10-20EEG_RPS_MCCB_1 1.7055
## vergallito, 2024_ITBS_10-20EEG_SC_MCCB_1 1.7055
## walther-lft, 2024_UNKNOWN_STANDARD_T_PANSS_1 -1.0712
## walther-lft, 2024_UNKNOWN_STANDARD_P_PANSS_1 -1.0712
## walther-lft, 2024_UNKNOWN_STANDARD_N_PANSS_1 -1.0712
## walther-lft, 2024_UNKNOWN_STANDARD_G_PANSS_1 -1.0712
## walther-lft, 2024_UNKNOWN_STANDARD_N_BNSS_1 -1.0712
## walther-itbs, 2024_ITBS_CM_T_PANSS_1 1.6035
## walther-itbs, 2024_ITBS_CM_P_PANSS_1 1.6035
## walther-itbs, 2024_ITBS_CM_N_PANSS_1 1.6035
## walther-itbs, 2024_ITBS_CM_G_PANSS_1 1.6035
## walther-itbs, 2024_ITBS_CM_N_BNSS_1 1.6035
## wang, 2020_ITBS_NEURONAV_T_PANSS_1 0.2601
## wang, 2020_ITBS_NEURONAV_P_PANSS_1 0.2601
## wang, 2020_ITBS_NEURONAV_N_PANSS_1 0.2601
## wang, 2020_ITBS_NEURONAV_G_PANSS_1 0.2601
## wang, 2020_ITBS_NEURONAV_P_SAPS_1 0.2601
## wang, 2020_ITBS_NEURONAV_N_SANS_1 0.2601
## wang, 2020_ITBS_NEURONAV_GC_MoCA_1 0.2601
## wang, 2020_ITBS_NEURONAV_PS_VFT_1 0.2601
## wang, 2020_ITBS_NEURONAV_WM_Digit span (forward)_1 0.2601
## wang, 2020_ITBS_NEURONAV_WM_Digit span (backward)_1 0.2601
## wang, 2020_ITBS_NEURONAV_RPS_Stroop Color Test_1 0.2601
## wang, 2020_ITBS_NEURONAV_RPS_Stroop Word Test_1 0.2601
## wang, 2020_ITBS_NEURONAV_RPS_Stroop Interference Test_1 0.2601
## wang, 2020_ITBS_NEURONAV_PS_TMT-A_1 0.2601
## wang, 2020_ITBS_NEURONAV_RPS_TMT-B_1 0.2601
## wang, 2022_ITBS_NEURONAV_P_PANSS_1 0.2601
## wang, 2022_ITBS_NEURONAV_N_PANSS_1 0.2601
## wang, 2022_ITBS_NEURONAV_G_PANSS_1 0.2601
## wang, 2022_ITBS_NEURONAV_T_PANSS_1 0.2601
## wang, 2022_ITBS_NEURONAV_P_SAPS_1 0.2601
## wang, 2022_ITBS_NEURONAV_N_SANS_1 0.2601
## wang, 2022_ITBS_NEURONAV_GC_MoCA_1 0.2601
## wang, 2022_ITBS_NEURONAV_WM_3-back RT_1 0.2601
## weickert, 2019_TDCS_10-20EEG_T_PANSS_1 -0.3642
## weickert, 2019_TDCS_10-20EEG_P_PANSS_1 -0.3642
## weickert, 2019_TDCS_10-20EEG_N_PANSS_1 -0.3642
## weickert, 2019_TDCS_10-20EEG_G_PANSS_1 -0.3642
## weickert, 2019_TDCS_10-20EEG_P_AHRS_1 -0.3642
## weickert, 2019_TDCS_10-20EEG_PS_BACS sc_1 -0.3642
## weickert, 2019_TDCS_10-20EEG_PS_TMT-A_1 -0.3642
## weickert, 2019_TDCS_10-20EEG_WM_LNS_1 -0.3642
## weickert, 2019_TDCS_10-20EEG_VerL_HVLTr_1 -0.3642
## weickert, 2019_TDCS_10-20EEG_VisL_BVMT_1 -0.3642
## weickert, 2019_TDCS_10-20EEG_RPS_NAB maze_1 -0.3642
## weickert, 2019_TDCS_10-20EEG_PS_fluency_1 -0.3642
## wen, 2021_HF-RTMS_CM_T_PANSS_1 1.1276
## wen, 2021_HF-RTMS_CM_P_PANSS_1 1.1276
## wen, 2021_HF-RTMS_CM_N_PANSS_1 1.1276
## wen, 2021_HF-RTMS_CM_G_PANSS_1 1.1276
## wen, 2021_HF-RTMS_CM_GC_RBANS-T_1 1.1276
## wen, 2021_HF-RTMS_CM_VerL_RBANS\r\nImmediate memory_1 1.1276
## wen, 2021_HF-RTMS_CM_WM_RBANS\r\nAttention_1 1.1276
## wen, 2021_HF-RTMS_CM_VisL_RBANS\r\nVisuospatial_1 1.1276
## wen, 2021_HF-RTMS_CM_VisL_RBANS\r\nDelayed memory_1 1.1276
## wen, 2021_HF-RTMS_CM_VerL_RBANS\r\nLanguage_1 1.1276
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n1 word (s)_1 1.1276
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n2 word (s)_1 1.1276
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n3 word (s)_1 1.1276
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n3 color (s)_1 1.1276
## wobrock, 2015_HF-RTMS_10-20EEG_T_PANSS_1 1.1715
## wobrock, 2015_HF-RTMS_10-20EEG_P_PANSS_1 1.1715
## wobrock, 2015_HF-RTMS_10-20EEG_N_PANSS_1 1.1715
## xie, 2023-a_LF-RTMS_10-20EEG_T_PANSS_1 2.2509
## xie, 2023-a_LF-RTMS_10-20EEG_P_PANSS_1 2.2509
## xie, 2023-a_LF-RTMS_10-20EEG_N_PANSS_1 2.2509
## xie, 2023-a_LF-RTMS_10-20EEG_G_PANSS_1 2.2509
## xie, 2023-a_LF-RTMS_10-20EEG_P_AHRS_1 2.2509
## xiu-10hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 0.6213
## xiu-10hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 0.6213
## xiu-10hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 0.6213
## xiu-10hz, 2020_HF-RTMS_NEURONAV_G_PANSS_1 0.6213
## xiu-10hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 0.6213
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nImmediate memory_1 0.6213
## xiu-10hz, 2020_HF-RTMS_NEURONAV_WM_RBANS\r\nAttention_1 0.6213
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nVisuospatial_1 0.6213
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nDelayed memory_1 0.6213
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nLanguage_1 0.6213
## xiu-20hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 0.6213
## xiu-20hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 0.6213
## xiu-20hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 0.6213
## xiu-20hz, 2020_HF-RTMS_NEURONAV_G_PANSS_1 0.6213
## xiu-20hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 0.6213
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nImmediate memory_1 0.6213
## xiu-20hz, 2020_HF-RTMS_NEURONAV_WM_RBANS\r\nAttention_1 0.6213
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nVisuospatial_1 0.6213
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nDelayed memory_1 0.6213
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nLanguage_1 0.6213
## xu, 2023_HD-TDCS_10-20EEG_T_PANSS_1 1.1766
## xu, 2023_HD-TDCS_10-20EEG_P_PANSS_1 1.1766
## xu, 2023_HD-TDCS_10-20EEG_N_PANSS_1 1.1766
## xu, 2023_HD-TDCS_10-20EEG_G_PANSS_1 1.1766
## xu, 2023_HD-TDCS_10-20EEG_GC_RBANS_1 1.1766
## ye-20hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 0.6213
## ye-20hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Immediate memory_1 0.6213
## ye-20hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Visuospatial_1 0.6213
## ye-20hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Language_1 0.6213
## ye-20hz, 2024_HF-RTMS_NEURONAV_WM_RBANS - Attention_1 0.6213
## ye-20hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Delayed memory_1 0.6213
## ye-10hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 0.6213
## ye-10hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Immediate memory_1 0.6213
## ye-10hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Visuospatial_1 0.6213
## ye-10hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Language_1 0.6213
## ye-10hz, 2024_HF-RTMS_NEURONAV_WM_RBANS - Attention_1 0.6213
## ye-10hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Delayed memory_1 0.6213
## yuanjun, 2024_LF-RTMS_10-20EEG_T_PANSS_1 2.2509
## yuanjun, 2024_LF-RTMS_10-20EEG_P_PANSS_1 2.2509
## yuanjun, 2024_LF-RTMS_10-20EEG_N_PANSS_1 2.2509
## yuanjun, 2024_LF-RTMS_10-20EEG_G_PANSS_1 2.2509
## yuanjun, 2024_LF-RTMS_10-20EEG_P_AHRS_1 2.2509
## zhai-a, 2023_HF-RTMS_NA_T_PANSS_1 0.3003
## zhang, 2022_TACS_10-20EEG_T_PANSS_1 -0.9420
## zhang, 2022_TACS_10-20EEG_P_PANSS_1 -0.9420
## zhang, 2022_TACS_10-20EEG_N_PANSS_1 -0.9420
## zhang, 2022_TACS_10-20EEG_P_AHRS_1 -0.9420
## zhao-tbs, 2014_ITBS_10-20EEG_T_PANSS_1 1.7055
## zhao-tbs, 2014_ITBS_10-20EEG_P_PANSS_1 1.7055
## zhao-tbs, 2014_ITBS_10-20EEG_N_PANSS_1 1.7055
## zhao-tbs, 2014_ITBS_10-20EEG_G_PANSS_1 1.7055
## zhao-tbs, 2014_ITBS_10-20EEG_N_SANS_1 1.7055
## zhao-20hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 1.1715
## zhao-20hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 1.1715
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 1.1715
## zhao-20hz, 2014_HF-RTMS_10-20EEG_G_PANSS_1 1.1715
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 1.1715
## zhao-10hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 1.1715
## zhao-10hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 1.1715
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 1.1715
## zhao-10hz, 2014_HF-RTMS_10-20EEG_G_PANSS_1 1.1715
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 1.1715
## zhou, 2024_HF-RTMS_10-20EEG_P_PANSS_1 1.1715
## zhou, 2024_HF-RTMS_10-20EEG_N_PANSS_1 1.1715
## zhou, 2024_HF-RTMS_10-20EEG_T_PANSS_1 1.1715
## zhou, 2024_HF-RTMS_10-20EEG_G_PANSS_1 1.1715
## zhou, 2024_HF-RTMS_10-20EEG_GC_RBANS-T_1 1.1715
## zhou, 2024_HF-RTMS_10-20EEG_VerL_RBANS\r\nImmediate memory_1 1.1715
## zhou, 2024_HF-RTMS_10-20EEG_VisL_RBANS\r\nVisuospatial_1 1.1715
## zhou, 2024_HF-RTMS_10-20EEG_VerL_RBANS\r\nLanguage_1 1.1715
## zhou, 2024_HF-RTMS_10-20EEG_WM_RBANS\r\nAttention_1 1.1715
## zhou, 2024_HF-RTMS_10-20EEG_VisL_RBANS\r\nDelayed memory_1 1.1715
## zhou, 2024_HF-RTMS_10-20EEG_RPS_SCWT \r\nInference scores_1 1.1715
## zhou, 2023_TDCS_10-20EEG_T_PANSS_1 -0.3642
## zhou, 2023_TDCS_10-20EEG_N_SANS_1 -0.3642
## zhou, 2023_TDCS_10-20EEG_RPS_IED total errors_1 -0.3642
## zhu, 2021_ITBS_CM_N_PANSS_1 1.6035
## zhuo, 2019_HF-RTMS_10-20EEG_T_PANSS_1 1.1715
## zhuo, 2019_HF-RTMS_10-20EEG_P_PANSS_1 1.1715
## zhuo, 2019_HF-RTMS_10-20EEG_N_PANSS_1 1.1715
## zhuo, 2019_HF-RTMS_10-20EEG_G_PANSS_1 1.1715
## zhuo, 2019_HF-RTMS_10-20EEG_N_SANS_1 1.1715
## zhuo, 2019_HF-RTMS_10-20EEG_PS_MCCB TMT-A_1 1.1715
## zhuo, 2019_HF-RTMS_10-20EEG_PS_MCCB BACS_1 1.1715
## zhuo, 2019_HF-RTMS_10-20EEG_PS_MCCB Fluency_1 1.1715
## zhuo, 2019_HF-RTMS_10-20EEG_WM_MCCB Working memory (WMS-SS)_1 1.1715
## zhuo, 2019_HF-RTMS_10-20EEG_VerL_MCCB Verbal learning (HVLT-R)_1 1.1715
## zhuo, 2019_HF-RTMS_10-20EEG_VisL_MCCB Visual learning (BVMT-R)_1 1.1715
## zhuo, 2019_HF-RTMS_10-20EEG_RPS_MCCB Reasoning/problem solving (NAB)_1 1.1715
## zhuo, 2019_HF-RTMS_10-20EEG_SC_MCCB Social cognition (MSCEIT)_1 1.1715
## zhuo, 2019_HF-RTMS_10-20EEG_GC_MCCB Composite score_1 1.1715
## 95%-CI
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANSS_1 [ 1.8489; 2.6528]
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANSS_1 [ 1.8489; 2.6528]
## bais, 2014 - l_LF-RTMS_10-20EEG_G_PANSS_1 [ 1.8489; 2.6528]
## bais, 2014 - l_LF-RTMS_10-20EEG_P_AHRS_1 [ 1.8489; 2.6528]
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANAS_1 [ 1.8489; 2.6528]
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANAS_1 [ 1.8489; 2.6528]
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANSS_1 [ 1.8489; 2.6528]
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANSS_1 [ 1.8489; 2.6528]
## bais, 2014 - bi_LF-RTMS_10-20EEG_G_PANSS_1 [ 1.8489; 2.6528]
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_AHRS_1 [ 1.8489; 2.6528]
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANAS_1 [ 1.8489; 2.6528]
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANAS_1 [ 1.8489; 2.6528]
## barr, 2011_HF-RTMS_NEURONAV_WM_1-back RT ms_1 [ 0.0140; 1.2286]
## barr, 2011_HF-RTMS_NEURONAV_WM_2-back RT ms_1 [ 0.0140; 1.2286]
## barr, 2011_HF-RTMS_NEURONAV_WM_3-back RT ms_1 [ 0.0140; 1.2286]
## barr, 2013_HF-RTMS_NEURONAV_WM_1-back RT ms Target Correct_1 [ 0.0140; 1.2286]
## barr, 2013_HF-RTMS_NEURONAV_WM_1-back RT ms Non Target Correct_1 [ 0.0140; 1.2286]
## barr, 2013_HF-RTMS_NEURONAV_WM_3-back RT ms Target Correct_1 [ 0.0140; 1.2286]
## barr, 2013_HF-RTMS_NEURONAV_WM_3-back RT ms Non Target Correct_1 [ 0.0140; 1.2286]
## barr, 2012_HF-RTMS_NEURONAV_P_PANSS_1 [ 0.0140; 1.2286]
## barr, 2012_HF-RTMS_NEURONAV_N_PANSS_1 [ 0.0140; 1.2286]
## barr, 2012_HF-RTMS_NEURONAV_N_SANS_1 [ 0.0140; 1.2286]
## basavaraju, 2021_ITBS_NEURONAV_N_SANS_1 [-0.0443; 0.5644]
## basavaraju, 2021_ITBS_NEURONAV_P_SAPS_1 [-0.0443; 0.5644]
## basavaraju, 2021_ITBS_NEURONAV_VerL_AVLT Hits_1 [-0.0443; 0.5644]
## basavaraju, 2021_ITBS_NEURONAV_VisL_CFT copying_1 [-0.0443; 0.5644]
## basavaraju, 2021_ITBS_NEURONAV_VisL_CFT Immediate Recall_1 [-0.0443; 0.5644]
## basavaraju, 2021_ITBS_NEURONAV_VisL_CFT Delayed Recall_1 [-0.0443; 0.5644]
## basavaraju, 2021_ITBS_NEURONAV_PS_DSST time (sec)_1 [-0.0443; 0.5644]
## basavaraju, 2021_ITBS_NEURONAV_PS_DSST errors_1 [-0.0443; 0.5644]
## basavaraju, 2021_ITBS_NEURONAV_AV_DVT time (sec)_1 [-0.0443; 0.5644]
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-A time (sec)_1 [-0.0443; 0.5644]
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-A errors_1 [-0.0443; 0.5644]
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-B time (sec)_1 [-0.0443; 0.5644]
## basavaraju, 2021_ITBS_NEURONAV_RPS_CT-B errors_1 [-0.0443; 0.5644]
## basavaraju, 2021_ITBS_NEURONAV_WM_1back verbal Hits_1 [-0.0443; 0.5644]
## basavaraju, 2021_ITBS_NEURONAV_WM_1back verbal Errors_1 [-0.0443; 0.5644]
## basavaraju, 2021_ITBS_NEURONAV_WM_2back verbal Hits_1 [-0.0443; 0.5644]
## basavaraju, 2021_ITBS_NEURONAV_WM_2back verbal Errors_1 [-0.0443; 0.5644]
## basavaraju, 2021_ITBS_NEURONAV_WM_Spatial Span total_1 [-0.0443; 0.5644]
## basavaraju, 2021_ITBS_NEURONAV_RPS_FAS_1 [-0.0443; 0.5644]
## basavaraju, 2021_ITBS_NEURONAV_RPS_Stroop Effect score_1 [-0.0443; 0.5644]
## basavaraju, 2021_ITBS_NEURONAV_SC_FOT index_1 [-0.0443; 0.5644]
## basavaraju, 2021_ITBS_NEURONAV_SC_SOT index_1 [-0.0443; 0.5644]
## basavaraju, 2021_ITBS_NEURONAV_SC_Faux Pax CI_1 [-0.0443; 0.5644]
## basavaraju, 2021_ITBS_NEURONAV_SC_Personalizing Bias Index_1 [-0.0443; 0.5644]
## basavaraju, 2021_ITBS_NEURONAV_SC_Social Perception Index_1 [-0.0443; 0.5644]
## basavaraju, 2021_ITBS_NEURONAV_SC_Emotion Recognition Index_1 [-0.0443; 0.5644]
## battion, 2021_ITBS_CM_T_PANSS_1 [ 0.8792; 2.3279]
## battion, 2021_ITBS_CM_N_SANS_1 [ 0.8792; 2.3279]
## blumberger, 2012_LF-RTMS_NEURONAV_P_PSYRATS_1 [-1.2116; 1.5433]
## blumberger, 2012_LF-RTMS_NEURONAV_T_PANSS_1 [-1.2116; 1.5433]
## blumberger, 2012_LF-RTMS_NEURONAV_P_PANSS_1 [-1.2116; 1.5433]
## blumberger, 2012_LF-RTMS_NEURONAV_P_AHRS_1 [-1.2116; 1.5433]
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PSYRATS_1 [-0.9417; 2.8067]
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_T_PANSS_1 [-0.9417; 2.8067]
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PANSS_1 [-0.9417; 2.8067]
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_AHRS_1 [-0.9417; 2.8067]
## bodén, 2021_ITBS_CM_N_CAIN_1 [ 0.8792; 2.3279]
## bose, 2018_TDCS_10-20EEG_P_SAPS_1 [-0.6463; -0.0821]
## bose, 2018_TDCS_10-20EEG_N_SANS_1 [-0.6463; -0.0821]
## bose, 2018_TDCS_10-20EEG_P_AHRS_1 [-0.6463; -0.0821]
## brunelin, 2012_TDCS_10-20EEG_P_AHRS_1 [-0.6463; -0.0821]
## brunelin, 2012_TDCS_10-20EEG_T_PANSS_1 [-0.6463; -0.0821]
## brunelin, 2006_LF-RTMS_10-20EEG_P_AHRS_1 [ 1.8489; 2.6528]
## brunelin, 2006_LF-RTMS_10-20EEG_P_SAPS_1 [ 1.8489; 2.6528]
## brunelin, 2006_LF-RTMS_10-20EEG_WM_MonitorSourceTask_1 [ 1.8489; 2.6528]
## bulubas, 2021_TDCS_10-20EEG_VisL_PFMT Total Correct Responses_1 [-0.6463; -0.0821]
## bulubas, 2021_TDCS_10-20EEG_VerL_PWMT Total Correct Responses_1 [-0.6463; -0.0821]
## bulubas, 2021_TDCS_10-20EEG_SC_EMI Correct Responses_1 [-0.6463; -0.0821]
## bulubas, 2021_TDCS_10-20EEG_WM_PLNB 0-back True Positive Responses_1 [-0.6463; -0.0821]
## bulubas, 2021_TDCS_10-20EEG_WM_PLNB 1-back True Positive Responses_1 [-0.6463; -0.0821]
## bulubas, 2021_TDCS_10-20EEG_WM_PLNB 2-back True Positive Responses_1 [-0.6463; -0.0821]
## bulubas, 2021_TDCS_10-20EEG_RPS_PCET Number Correct Responses_1 [-0.6463; -0.0821]
## bulubas, 2021_TDCS_10-20EEG_VisL_Short VOLT Total Correct_1 [-0.6463; -0.0821]
## chang-a, 2021_TACS_10-20EEG_T_PANSS_1 [-2.0805; 0.1966]
## chang-a, 2021_TACS_10-20EEG_N_PANSS_1 [-2.0805; 0.1966]
## chang-a, 2021_TACS_10-20EEG_N_SANS_1 [-2.0805; 0.1966]
## chauhan, 2021_ITBS_10-20EEG_P_PANSS_1 [ 1.2009; 2.2101]
## chauhan, 2021_ITBS_10-20EEG_N_PANSS_1 [ 1.2009; 2.2101]
## chauhan, 2021_ITBS_10-20EEG_G_PANSS_1 [ 1.2009; 2.2101]
## chauhan, 2021_ITBS_10-20EEG_T_PANSS_1 [ 1.2009; 2.2101]
## chauhan, 2021_ITBS_10-20EEG_T_BPRS_1 [ 1.2009; 2.2101]
## de jesus, 2011_LF-RTMS_10-20EEG_T_BPRS_1 [ 1.8489; 2.6528]
## de jesus, 2011_LF-RTMS_10-20EEG_P_BPRS_1 [ 1.8489; 2.6528]
## de jesus, 2011_LF-RTMS_10-20EEG_N_BPRS_1 [ 1.8489; 2.6528]
## de jesus, 2011_LF-RTMS_10-20EEG_P_AHRS_1 [ 1.8489; 2.6528]
## dharani, 2021_HD-TDCS_10-10EEG_P_PANSS_1 [-0.3399; 2.8731]
## dharani, 2021_HD-TDCS_10-10EEG_N_PANSS_1 [-0.3399; 2.8731]
## dharani, 2021_HD-TDCS_10-10EEG_G_PANSS_1 [-0.3399; 2.8731]
## dharani, 2021_HD-TDCS_10-10EEG_N_SANS_1 [-0.3399; 2.8731]
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_SANS_1 [ 1.8489; 2.6528]
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_P_PANSS_1 [ 1.8489; 2.6528]
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_PANSS_1 [ 1.8489; 2.6528]
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_G_PANSS_1 [ 1.8489; 2.6528]
## dolfus, 2018_HF-RTMS_NEURONAV_P_AHRS_1 [ 0.0140; 1.2286]
## du, 2024_HF-RTMS_NEURONAV_T_BPRS_1 [ 0.0140; 1.2286]
## du, 2024_HF-RTMS_NEURONAV_P_BPRS_1 [ 0.0140; 1.2286]
## du, 2024_HF-RTMS_NEURONAV_N_BPRS_1 [ 0.0140; 1.2286]
## du, 2022_HF-RTMS_10-20EEG_VisL_PRM number correct_1 [ 0.8610; 1.4821]
## du, 2022_HF-RTMS_10-20EEG_N_SANS_1 [ 0.8610; 1.4821]
## du, 2022_HF-RTMS_10-20EEG_T_PANSS_1 [ 0.8610; 1.4821]
## du, 2022_HF-RTMS_10-20EEG_P_PANSS_1 [ 0.8610; 1.4821]
## du, 2022_HF-RTMS_10-20EEG_N_PANSS_1 [ 0.8610; 1.4821]
## du, 2022_HF-RTMS_10-20EEG_G_PANSS_1 [ 0.8610; 1.4821]
## farhang, 2024_TDCS_10-20EEG_WM_ letter-number sequencing_1 [-0.6463; -0.0821]
## fitzerald, 2008_LF-RTMS_CM_N_SANS_1 [-1.9085; 0.6340]
## fitzerald, 2008_LF-RTMS_CM_P_PANSS_1 [-1.9085; 0.6340]
## fitzerald, 2008_LF-RTMS_CM_N_PANSS_1 [-1.9085; 0.6340]
## fitzerald, 2008_LF-RTMS_CM_T_PANSS_1 [-1.9085; 0.6340]
## fitzerald-l, 2014_TDCS_10-20EEG_P_PANSS_1 [-0.6463; -0.0821]
## fitzerald-l, 2014_TDCS_10-20EEG_N_PANSS_1 [-0.6463; -0.0821]
## fitzerald-l, 2014_TDCS_10-20EEG_T_PANSS_1 [-0.6463; -0.0821]
## fitzerald-l, 2014_TDCS_10-20EEG_N_SANS_1 [-0.6463; -0.0821]
## fitzerald-bi, 2014_TDCS_10-20EEG_P_PANSS_1 [-0.6463; -0.0821]
## fitzerald-bi, 2014_TDCS_10-20EEG_N_PANSS_1 [-0.6463; -0.0821]
## fitzerald-bi, 2014_TDCS_10-20EEG_T_PANSS_1 [-0.6463; -0.0821]
## fitzerald-bi, 2014_TDCS_10-20EEG_N_SANS_1 [-0.6463; -0.0821]
## francis, 2019_HF-RTMS_CM_VerL_BACS Verbal Memory_1 [ 0.7627; 1.4925]
## francis, 2019_HF-RTMS_CM_WM_BACS Digit Sequencing_1 [ 0.7627; 1.4925]
## francis, 2019_HF-RTMS_CM_PS_BACS Semantic and Letter Fluency_1 [ 0.7627; 1.4925]
## francis, 2019_HF-RTMS_CM_PS_BACS Symbol Coding_1 [ 0.7627; 1.4925]
## francis, 2019_HF-RTMS_CM_RPS_BACS Tower of London_1 [ 0.7627; 1.4925]
## francis, 2019_HF-RTMS_CM_GC_BACS Composite Score_1 [ 0.7627; 1.4925]
## frohlich, 2016_TDCS_10-20EEG_P_AHRS_1 [-0.6463; -0.0821]
## frohlich, 2016_TDCS_10-20EEG_T_PANSS_1 [-0.6463; -0.0821]
## frohlich, 2016_TDCS_10-20EEG_P_PANSS_1 [-0.6463; -0.0821]
## frohlich, 2016_TDCS_10-20EEG_N_PANSS_1 [-0.6463; -0.0821]
## frohlich, 2016_TDCS_10-20EEG_G_PANSS_1 [-0.6463; -0.0821]
## gao, 2024_ITBS_10-20EEG_P_PANSS_1 [ 1.2009; 2.2101]
## gao, 2024_ITBS_10-20EEG_N_PANSS_1 [ 1.2009; 2.2101]
## gao, 2024_ITBS_10-20EEG_G_PANSS_1 [ 1.2009; 2.2101]
## gao, 2024_ITBS_10-20EEG_T_PANSS_1 [ 1.2009; 2.2101]
## gao, 2024_ITBS_10-20EEG_N_SANS_1 [ 1.2009; 2.2101]
## garcía-fernández, 2024_TDCS_10-20EEG_PS_MCCB_1 [-0.6463; -0.0821]
## garcía-fernández, 2024_TDCS_10-20EEG_AV_MCCB_1 [-0.6463; -0.0821]
## garcía-fernández, 2024_TDCS_10-20EEG_WM_MCCB_1 [-0.6463; -0.0821]
## garcía-fernández, 2024_TDCS_10-20EEG_VerL_MCCB_1 [-0.6463; -0.0821]
## garcía-fernández, 2024_TDCS_10-20EEG_VisL_MCCB_1 [-0.6463; -0.0821]
## garcía-fernández, 2024_TDCS_10-20EEG_RPS_MCCB_1 [-0.6463; -0.0821]
## garcía-fernández, 2024_TDCS_10-20EEG_SC_MCCB_1 [-0.6463; -0.0821]
## garg, 2016_DTMS_CM_P_PANSS_1 [-0.5366; 0.9031]
## garg, 2016_DTMS_CM_N_PANSS_1 [-0.5366; 0.9031]
## garg, 2016_DTMS_CM_G_PANSS_1 [-0.5366; 0.9031]
## garg, 2016_DTMS_CM_T_PANSS_1 [-0.5366; 0.9031]
## gogler, 2017_TDCS_10-20EEG_PS_C_1 [-0.6463; -0.0821]
## gogler, 2017_TDCS_10-20EEG_WM_K_1 [-0.6463; -0.0821]
## gogler, 2017_TDCS_10-20EEG_AV_α_1 [-0.6463; -0.0821]
## gomes, 2018_TDCS_10-20EEG_WM_MCCB_1 [-0.6463; -0.0821]
## gomes, 2018_TDCS_10-20EEG_PS_MCCB_1 [-0.6463; -0.0821]
## gomes, 2018_TDCS_10-20EEG_AV_MCCB_1 [-0.6463; -0.0821]
## gomes, 2018_TDCS_10-20EEG_VerL_MCCB_1 [-0.6463; -0.0821]
## gomes, 2018_TDCS_10-20EEG_VisL_MCCB_1 [-0.6463; -0.0821]
## gomes, 2018_TDCS_10-20EEG_RPS_MCCB_1 [-0.6463; -0.0821]
## gomes, 2018_TDCS_10-20EEG_P_PANSS_1 [-0.6463; -0.0821]
## gomes, 2018_TDCS_10-20EEG_N_PANSS-N_1 [-0.6463; -0.0821]
## gomes, 2018_TDCS_10-20EEG_G_PANSS_1 [-0.6463; -0.0821]
## gomes, 2018_TDCS_10-20EEG_T_PANSS-T_1 [-0.6463; -0.0821]
## guan, 2020_HF-RTMS_NEURONAV_T_PANSS-T_1 [ 0.0140; 1.2286]
## guan, 2020_HF-RTMS_NEURONAV_P_PANSS_1 [ 0.0140; 1.2286]
## guan, 2020_HF-RTMS_NEURONAV_N_PANSS-N_1 [ 0.0140; 1.2286]
## guan, 2020_HF-RTMS_NEURONAV_G_PANSS_1 [ 0.0140; 1.2286]
## guan, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nImmediate memory_1 [ 0.0140; 1.2286]
## guan, 2020_HF-RTMS_NEURONAV_WM_RBANS\r\nAttention_1 [ 0.0140; 1.2286]
## guan, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nVisuospatial/constructional_1 [ 0.0140; 1.2286]
## guan, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nDelayed memory_1 [ 0.0140; 1.2286]
## guan, 2020_HF-RTMS_NEURONAV_PS_RBANS\r\nLanguage_1 [ 0.0140; 1.2286]
## guan, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 [ 0.0140; 1.2286]
## guleken, 2020_HF-RTMS_CM_P_PANSS_1 [ 0.7627; 1.4925]
## guleken, 2020_HF-RTMS_CM_N_SANS_1 [ 0.7627; 1.4925]
## guleken, 2020_HF-RTMS_CM_RPS_WSCT total correct responses_1 [ 0.7627; 1.4925]
## guleken, 2020_HF-RTMS_CM_RPS_WSCT perseverative errors_1 [ 0.7627; 1.4925]
## guleken, 2020_HF-RTMS_CM_WM_DST forward_1 [ 0.7627; 1.4925]
## guleken, 2020_HF-RTMS_CM_WM_DST backwards_1 [ 0.7627; 1.4925]
## guleken, 2020_HF-RTMS_CM_RPS_Total time_1 [ 0.7627; 1.4925]
## guleken, 2020_HF-RTMS_CM_RPS_Total errors_1 [ 0.7627; 1.4925]
## guleken, 2020_HF-RTMS_CM_RPS_Stroop Interference_1 [ 0.7627; 1.4925]
## guse, 2013_HF-RTMS_10-20EEG_PS_TMT-A_1 [ 0.8610; 1.4821]
## guse, 2013_HF-RTMS_10-20EEG_RPS_TMT-B_1 [ 0.8610; 1.4821]
## guse, 2013_HF-RTMS_10-20EEG_RPS_WCST Accuracy_1 [ 0.8610; 1.4821]
## guse, 2013_HF-RTMS_10-20EEG_RPS_WCST RT_1 [ 0.8610; 1.4821]
## guse, 2013_HF-RTMS_10-20EEG_AV_Sel. Attention Accuracy_1 [ 0.8610; 1.4821]
## guse, 2013_HF-RTMS_10-20EEG_AV_Sel. Attention RT_1 [ 0.8610; 1.4821]
## guse, 2013_HF-RTMS_10-20EEG_AV_Div. Attention Accuracy_1 [ 0.8610; 1.4821]
## guse, 2013_HF-RTMS_10-20EEG_AV_Div. Attention RT_1 [ 0.8610; 1.4821]
## guse, 2013_HF-RTMS_10-20EEG_WM_0-back Accuracy_1 [ 0.8610; 1.4821]
## guse, 2013_HF-RTMS_10-20EEG_WM_0-back RT_1 [ 0.8610; 1.4821]
## guse, 2013_HF-RTMS_10-20EEG_WM_1-back Accuracy_1 [ 0.8610; 1.4821]
## guse, 2013_HF-RTMS_10-20EEG_WM_1-back RT_1 [ 0.8610; 1.4821]
## guse, 2013_HF-RTMS_10-20EEG_WM_2-back Accuracy_1 [ 0.8610; 1.4821]
## guse, 2013_HF-RTMS_10-20EEG_WM_2-back RT_1 [ 0.8610; 1.4821]
## hasan, 2016_HF-RTMS_10-20EEG_WM_DST z score_1 [ 0.8610; 1.4821]
## hasan, 2016_HF-RTMS_10-20EEG_WM_DST Forward_1 [ 0.8610; 1.4821]
## hasan, 2016_HF-RTMS_10-20EEG_WM_DST Backward_1 [ 0.8610; 1.4821]
## hasan, 2016_HF-RTMS_10-20EEG_PS_TMT-A time (s)_1 [ 0.8610; 1.4821]
## hasan, 2016_HF-RTMS_10-20EEG_RPS_TMT-B time (s)_1 [ 0.8610; 1.4821]
## hasan, 2016_HF-RTMS_10-20EEG_VerL_VLMT z score_1 [ 0.8610; 1.4821]
## hasan, 2016_HF-RTMS_10-20EEG_RPS_WCST z score_1 [ 0.8610; 1.4821]
## hasan, 2016_HF-RTMS_10-20EEG_RPS_WCST total correct score_1 [ 0.8610; 1.4821]
## hasan, 2016_HF-RTMS_10-20EEG_RPS_WCST total errors_1 [ 0.8610; 1.4821]
## hasan, 2016_HF-RTMS_10-20EEG_PS_RWT z score_1 [ 0.8610; 1.4821]
## holi, 2004_HF-RTMS_10-20EEG_T_PANSS_1 [ 0.8610; 1.4821]
## holi, 2004_HF-RTMS_10-20EEG_P_PANSS_1 [ 0.8610; 1.4821]
## holi, 2004_HF-RTMS_10-20EEG_N_PANSS_1 [ 0.8610; 1.4821]
## holi, 2004_HF-RTMS_10-20EEG_G_PANSS_1 [ 0.8610; 1.4821]
## hu, 2024_LF-RTMS_10-20EEG_T_PANSS_1 [ 1.8489; 2.6528]
## hu, 2024_LF-RTMS_10-20EEG_P_PANSS_1 [ 1.8489; 2.6528]
## hu, 2024_LF-RTMS_10-20EEG_N_PANSS_1 [ 1.8489; 2.6528]
## hu, 2024_LF-RTMS_10-20EEG_G_PANSS_1 [ 1.8489; 2.6528]
## hu, 2024_LF-RTMS_10-20EEG_PS_TMT-A_1 [ 1.8489; 2.6528]
## hu, 2024_LF-RTMS_10-20EEG_PS_BACS Symbol Coding_1 [ 1.8489; 2.6528]
## hu, 2024_LF-RTMS_10-20EEG_PS_Category Fluency_1 [ 1.8489; 2.6528]
## hu, 2024_LF-RTMS_10-20EEG_AV_CPT-IP_1 [ 1.8489; 2.6528]
## hu, 2024_LF-RTMS_10-20EEG_WM_WMS-3 spatial span_1 [ 1.8489; 2.6528]
## hu, 2024_LF-RTMS_10-20EEG_VerL_HVLT-R_1 [ 1.8489; 2.6528]
## hu, 2024_LF-RTMS_10-20EEG_VisL_BVMT-R_1 [ 1.8489; 2.6528]
## hu, 2024_LF-RTMS_10-20EEG_RPS_NAB_1 [ 1.8489; 2.6528]
## hu, 2023_LF-RTMS_10-10EEG_T_PANSS_1 [ 1.8523; 3.5514]
## hu, 2023_LF-RTMS_10-10EEG_P_PANSS_1 [ 1.8523; 3.5514]
## hu, 2023_LF-RTMS_10-10EEG_N_PANSS_1 [ 1.8523; 3.5514]
## hu, 2023_LF-RTMS_10-10EEG_G_PANSS_1 [ 1.8523; 3.5514]
## hu, 2023_LF-RTMS_10-10EEG_GC_MCCB-T_1 [ 1.8523; 3.5514]
## hu, 2023_LF-RTMS_10-10EEG_PS_MCCB_1 [ 1.8523; 3.5514]
## hu, 2023_LF-RTMS_10-10EEG_AV_MCCB_1 [ 1.8523; 3.5514]
## hu, 2023_LF-RTMS_10-10EEG_WM_MCCB_1 [ 1.8523; 3.5514]
## hu, 2023_LF-RTMS_10-10EEG_VerL_MCCB_1 [ 1.8523; 3.5514]
## hu, 2023_LF-RTMS_10-10EEG_VisL_MCCB_1 [ 1.8523; 3.5514]
## hu, 2023_LF-RTMS_10-10EEG_RPS_MCCB_1 [ 1.8523; 3.5514]
## hu, 2023_LF-RTMS_10-10EEG_SC_MCCB_1 [ 1.8523; 3.5514]
## huang, 2016_HF-RTMS_CM_P_PANSS_1 [ 0.7627; 1.4925]
## huang, 2016_HF-RTMS_CM_N_PANSS_1 [ 0.7627; 1.4925]
## huang, 2016_HF-RTMS_CM_G_PANSS_1 [ 0.7627; 1.4925]
## huang, 2016_HF-RTMS_CM_T_PANSS_1 [ 0.7627; 1.4925]
## huang, 2016_HF-RTMS_CM_RPS_WSCT total errors_1 [ 0.7627; 1.4925]
## jeon, 2018_TDCS_10-20EEG_P_PANSS_1 [-0.6463; -0.0821]
## jeon, 2018_TDCS_10-20EEG_N_PANSS_1 [-0.6463; -0.0821]
## jeon, 2018_TDCS_10-20EEG_G_PANSS_1 [-0.6463; -0.0821]
## jeon, 2018_TDCS_10-20EEG_T_PANSS_1 [-0.6463; -0.0821]
## jeon, 2018_TDCS_10-20EEG_PS_MCCB_1 [-0.6463; -0.0821]
## jeon, 2018_TDCS_10-20EEG_AV_MCCB_1 [-0.6463; -0.0821]
## jeon, 2018_TDCS_10-20EEG_WM_MCCB_1 [-0.6463; -0.0821]
## jeon, 2018_TDCS_10-20EEG_VerL_MCCB_1 [-0.6463; -0.0821]
## jeon, 2018_TDCS_10-20EEG_VisL_MCCB_1 [-0.6463; -0.0821]
## jeon, 2018_TDCS_10-20EEG_RPS_MCCB_1 [-0.6463; -0.0821]
## jeon, 2018_TDCS_10-20EEG_SC_MCCB_1 [-0.6463; -0.0821]
## jeon, 2018_TDCS_10-20EEG_GC_MCCB Composite Score_1 [-0.6463; -0.0821]
## jeon, 2018_TDCS_10-20EEG_RPS_WCST Perservative Responses_1 [-0.6463; -0.0821]
## jeon, 2018_TDCS_10-20EEG_RPS_WCST Perservative Errors_1 [-0.6463; -0.0821]
## jeon, 2018_TDCS_10-20EEG_RPS_WCST Categoris number_1 [-0.6463; -0.0821]
## jin, 2023_ITBS_NA_SC_FERT_1 [ 0.1130; 1.4904]
## jin, 2023_ITBS_NA_SC_HT_1 [ 0.1130; 1.4904]
## jin, 2023_ITBS_NA_T_PANSS_1 [ 0.1130; 1.4904]
## jin, 2023_ITBS_NA_P_PANSS_1 [ 0.1130; 1.4904]
## jin, 2023_ITBS_NA_N_PANSS_1 [ 0.1130; 1.4904]
## jin, 2023_ITBS_NA_G_PANSS_1 [ 0.1130; 1.4904]
## kang, 2024_CTBS_CM_T_PANSS_1 [ 0.1221; 3.7502]
## kang, 2024_CTBS_CM_P_PANSS_1 [ 0.1221; 3.7502]
## kang, 2024_CTBS_CM_N_PANSS_1 [ 0.1221; 3.7502]
## kang, 2024_CTBS_CM_G_PANSS_1 [ 0.1221; 3.7502]
## kang, 2024_CTBS_CM_P_AHRS_1 [ 0.1221; 3.7502]
## kantrowitz, 2019_TDCS_10-20EEG_P_AHRS_1 [-0.6463; -0.0821]
## kimura, 2016_HF-RTMS_10-20EEG_P_AHRS_1 [ 0.8610; 1.4821]
## klein, 1999_LF-RTMS_CM_P_PANSS_1 [-1.9085; 0.6340]
## klein, 1999_LF-RTMS_CM_N_PANSS_1 [-1.9085; 0.6340]
## klein, 1999_LF-RTMS_CM_G_PANSS_1 [-1.9085; 0.6340]
## klein, 1999_LF-RTMS_CM_T_BPRS_1 [-1.9085; 0.6340]
## koops, 2018_TDCS_10-20EEG_P_AHRS_1 [-0.6463; -0.0821]
## koops, 2018_TDCS_10-20EEG_T_PANSS_1 [-0.6463; -0.0821]
## koops, 2018_TDCS_10-20EEG_P_PANSS_1 [-0.6463; -0.0821]
## koops, 2018_TDCS_10-20EEG_N_PANSS_1 [-0.6463; -0.0821]
## koops, 2018_TDCS_10-20EEG_RPS_Stroop Interference_1 [-0.6463; -0.0821]
## koops, 2018_TDCS_10-20EEG_PS_TMT-A_1 [-0.6463; -0.0821]
## koops, 2018_TDCS_10-20EEG_RPS_TMT-B_1 [-0.6463; -0.0821]
## koops, 2016_CTBS_10-20EEG_P_PANSS_1 [-3.1344; -1.3830]
## koops, 2016_CTBS_10-20EEG_P_AHRS_1 [-3.1344; -1.3830]
## koops, 2016_CTBS_10-20EEG_P_PSYRATS_1 [-3.1344; -1.3830]
## kos, 2024_TDCS_10-20EEG_N_SANS_1 [-0.6463; -0.0821]
## kos, 2024_TDCS_10-20EEG_N_AES_1 [-0.6463; -0.0821]
## kumar, 2020_HF-RTMS_CM_PANSS-N_1 [ 0.7627; 1.4925]
## kumar, 2020_HF-RTMS_CM_PANSS-G_1 [ 0.7627; 1.4925]
## li, 2024 - a_ITBS_10-20EEG_GC_MCCB_1 [ 1.2009; 2.2101]
## li, 2024 - a_ITBS_10-20EEG_WM_MCCB_1 [ 1.2009; 2.2101]
## li, 2024 - a_ITBS_10-20EEG_PANSS-P_1 [ 1.2009; 2.2101]
## li, 2024 - a_ITBS_10-20EEG_PANSS-N_1 [ 1.2009; 2.2101]
## li, 2024 - a_ITBS_10-20EEG_PANSS-G_1 [ 1.2009; 2.2101]
## li-b-lpc, 2024_ITBS_NEURONAV_PS_MCCB_1 [-0.0443; 0.5644]
## li-b-lpc, 2024_ITBS_NEURONAV_AV_MCCB_1 [-0.0443; 0.5644]
## li-b-lpc, 2024_ITBS_NEURONAV_WM_MCCB_1 [-0.0443; 0.5644]
## li-b-lpc, 2024_ITBS_NEURONAV_VerL_MCCB_1 [-0.0443; 0.5644]
## li-b-lpc, 2024_ITBS_NEURONAV_VisL_MCCB_1 [-0.0443; 0.5644]
## li-b-lpc, 2024_ITBS_NEURONAV_RPS_MCCB_1 [-0.0443; 0.5644]
## li-b-lpc, 2024_ITBS_NEURONAV_SC_MCCB_1 [-0.0443; 0.5644]
## li-b-lpc, 2024_ITBS_NEURONAV_GC_MCCB_1 [-0.0443; 0.5644]
## li-b-dlpfc, 2024_ITBS_NEURONAV_PS_MCCB_1 [-0.0443; 0.5644]
## li-b-dlpfc, 2024_ITBS_NEURONAV_AV_MCCB_1 [-0.0443; 0.5644]
## li-b-dlpfc, 2024_ITBS_NEURONAV_WM_MCCB_1 [-0.0443; 0.5644]
## li-b-dlpfc, 2024_ITBS_NEURONAV_VerL_MCCB_1 [-0.0443; 0.5644]
## li-b-dlpfc, 2024_ITBS_NEURONAV_VisL_MCCB_1 [-0.0443; 0.5644]
## li-b-dlpfc, 2024_ITBS_NEURONAV_RPS_MCCB_1 [-0.0443; 0.5644]
## li-b-dlpfc, 2024_ITBS_NEURONAV_SC_MCCB_1 [-0.0443; 0.5644]
## li-b-dlpfc, 2024_ITBS_NEURONAV_GC_MCCB_1 [-0.0443; 0.5644]
## lindenmayer, 2019_TDCS_10-20EEG_AHRS_1 [-0.6463; -0.0821]
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-T_1 [-0.6463; -0.0821]
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-P_1 [-0.6463; -0.0821]
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-N_1 [-0.6463; -0.0821]
## lindenmayer, 2019_TDCS_10-20EEG_PANSS-G_1 [-0.6463; -0.0821]
## lindenmayer, 2019_TDCS_10-20EEG_GC_MCCB_1 [-0.6463; -0.0821]
## lindenmayer, 2019_TDCS_10-20EEG_PS_MCCB_1 [-0.6463; -0.0821]
## lindenmayer, 2019_TDCS_10-20EEG_AV_MCCB_1 [-0.6463; -0.0821]
## lindenmayer, 2019_TDCS_10-20EEG_WM_MCCB_1 [-0.6463; -0.0821]
## lindenmayer, 2019_TDCS_10-20EEG_VerL_MCCB_1 [-0.6463; -0.0821]
## lindenmayer, 2019_TDCS_10-20EEG_VisL_MCCB_1 [-0.6463; -0.0821]
## lindenmayer, 2019_TDCS_10-20EEG_RPN_MCCB_1 [-0.6463; -0.0821]
## lindenmayer, 2019_TDCS_10-20EEG_SC_MCCB_1 [-0.6463; -0.0821]
## lisoni, 2022_TDCS_10-20 EEG_PANSS-P_1 [-2.1956; -0.5916]
## lisoni, 2022_TDCS_10-20 EEG_PANSS-N_1 [-2.1956; -0.5916]
## lisoni, 2022_TDCS_10-20 EEG_PANSS-T_1 [-2.1956; -0.5916]
## lisoni, 2022_TDCS_10-20 EEG_PANSS-G_1 [-2.1956; -0.5916]
## lisoni, 2022_TDCS_10-20 EEG_GC_BACS (Composite z-scores)_1 [-2.1956; -0.5916]
## lisoni, 2022_TDCS_10-20 EEG_VerL_BACS z-scores (Verbal memory)_1 [-2.1956; -0.5916]
## lisoni, 2022_TDCS_10-20 EEG_WM_BACS z-scores (Digit sequencing)_1 [-2.1956; -0.5916]
## lisoni, 2022_TDCS_10-20 EEG_PS_BACS z-scores (Verbal fluency)_1 [-2.1956; -0.5916]
## lisoni, 2022_TDCS_10-20 EEG_PS_BACS z-scores (Symbol coding)_1 [-2.1956; -0.5916]
## lisoni, 2022_TDCS_10-20 EEG_RPS_BACS z-scores (Tower of London)_1 [-2.1956; -0.5916]
## liu, 2024_HF-RTMS_NA_T_PANSS_1 [-0.9948; 1.5954]
## liu, 2024_HF-RTMS_NA_P_PANSS_1 [-0.9948; 1.5954]
## liu, 2024_HF-RTMS_NA_N_PANSS_1 [-0.9948; 1.5954]
## liu, 2024_HF-RTMS_NA_G_PANSS_1 [-0.9948; 1.5954]
## liu, 2024_HF-RTMS_NA_VerL_RBANS (Immediate memory)_1 [-0.9948; 1.5954]
## liu, 2024_HF-RTMS_NA_VisL_RBANS (Visual spatial structure)_1 [-0.9948; 1.5954]
## liu, 2024_HF-RTMS_NA_PS_RBANS (Speech function)_1 [-0.9948; 1.5954]
## liu, 2024_HF-RTMS_NA_WM_RBANS (Attention)_1 [-0.9948; 1.5954]
## liu, 2024_HF-RTMS_NA_Visl_RBANS (Delayed memory)_1 [-0.9948; 1.5954]
## lyu, 2024_TDCS_10-20EEG_T_PANSS_1 [-0.6463; -0.0821]
## lyu, 2024_TDCS_10-20EEG_P_PANSS_1 [-0.6463; -0.0821]
## lyu, 2024_TDCS_10-20EEG_N_PANSS_1 [-0.6463; -0.0821]
## lyu, 2024_TDCS_10-20EEG_G_PANSS_1 [-0.6463; -0.0821]
## lyu, 2024_TDCS_10-20EEG_N_SANS_1 [-0.6463; -0.0821]
## mao, 2023_HF-RTMS_CM_GC_RBANS_1 [ 0.7627; 1.4925]
## mao, 2023_HF-RTMS_CM_VerL_RBANS-Immediate Memory_1 [ 0.7627; 1.4925]
## mao, 2023_HF-RTMS_CM_RBANS-Visuospatial_1 [ 0.7627; 1.4925]
## mao, 2023_HF-RTMS_CM_VerL_RBANS-Language_1 [ 0.7627; 1.4925]
## mao, 2023_HF-RTMS_CM_WM_RBANS-Attention_1 [ 0.7627; 1.4925]
## mao, 2023_HF-RTMS_CM_VerL_RBANS-Delayed memory_1 [ 0.7627; 1.4925]
## mao, 2023_HF-RTMS_CM_P_AHRS_1 [ 0.7627; 1.4925]
## mao, 2023_HF-RTMS_CM_T_PANSS_1 [ 0.7627; 1.4925]
## marquardt, 2022_TDCS_10-20EEG_P_PANSS_1 [-0.6463; -0.0821]
## marquardt, 2022_TDCS_10-20EEG_N_PANSS_1 [-0.6463; -0.0821]
## marquardt, 2022_TDCS_10-20EEG_P_AHRS_1 [-0.6463; -0.0821]
## marquardt, 2022_TDCS_10-20EEG_RPS_Stroop 3 (s/RT)_1 [-0.6463; -0.0821]
## marquardt, 2022_TDCS_10-20EEG_RPS_Stroop 4 (s/RT)_1 [-0.6463; -0.0821]
## marquardt, 2022_TDCS_10-20EEG_PS_TMT-A_1 [-0.6463; -0.0821]
## marquardt, 2022_TDCS_10-20EEG_RPS_TMT-B_1 [-0.6463; -0.0821]
## mcintosh, 2004_LF-RTMS_10-20EEG_P_PANSS_1 [ 1.8489; 2.6528]
## mcintosh, 2004_LF-RTMS_10-20EEG_N_PANSS_1 [ 1.8489; 2.6528]
## mcintosh, 2004_LF-RTMS_10-20EEG_VerL_AVLT_1 [ 1.8489; 2.6528]
## meiron, 2021_TDCS_10-20EEG_T_PANSS_1 [-0.6463; -0.0821]
## meiron, 2021_TDCS_10-20EEG_WM_(verbal) WM - Accuracy_1 [-0.6463; -0.0821]
## meiron, 2021_TDCS_10-20EEG_WM_(verbal) WM - RT_1 [-0.6463; -0.0821]
## meiron, 2024_TDCS_10-20EEG_T_PANSS_1 [-0.6463; -0.0821]
## meiron, 2024_TDCS_10-20EEG_WM_2-BACK Acc_1 [-0.6463; -0.0821]
## meiron, 2024_TDCS_10-20EEG_WM_2-BACK RT_1 [-0.6463; -0.0821]
## mellin-tacs, 2018_TACS_10-20EEG_P_AHRS_1 [-2.0805; 0.1966]
## mellin-tacs, 2018_TACS_10-20EEG_T_PANSS-T_1 [-2.0805; 0.1966]
## mellin-tacs, 2018_TACS_10-20EEG_P_PANSS-P_1 [-2.0805; 0.1966]
## mellin-tacs, 2018_TACS_10-20EEG_N_PANSS-N_1 [-2.0805; 0.1966]
## mellin-tacs, 2018_TACS_10-20EEG_G_PANSS-G_1 [-2.0805; 0.1966]
## mellin-tacs, 2018_TACS_10-20EEG_GC_BACS_1 [-2.0805; 0.1966]
## mellin-tdcs, 2018_TDCS_10-20EEG_P_AHRS_1 [-0.6463; -0.0821]
## mellin-tdcs, 2018_TDCS_10-20EEG_T_PANSS_1 [-0.6463; -0.0821]
## mellin-tdcs, 2018_TDCS_10-20EEG_P_PANSS_1 [-0.6463; -0.0821]
## mellin-tdcs, 2018_TDCS_10-20EEG_N_PANSS_1 [-0.6463; -0.0821]
## mellin-tdcs, 2018_TDCS_10-20EEG_G_PANSS_1 [-0.6463; -0.0821]
## mellin-tdcs, 2018_TDCS_10-20EEG_GC_BACS_1 [-0.6463; -0.0821]
## moeller, 2022_DTMS_CM_T_PANSS_1 [-0.5366; 0.9031]
## moeller, 2022_DTMS_CM_P_PANSS_1 [-0.5366; 0.9031]
## moeller, 2022_DTMS_CM_N_PANSS_1 [-0.5366; 0.9031]
## mogg, 2007_HF-RTMS_CM_VerL_HVLT immediate recall_1 [ 0.7627; 1.4925]
## mogg, 2007_HF-RTMS_CM_VerL_HVLT delayed recall_1 [ 0.7627; 1.4925]
## mogg, 2007_HF-RTMS_CM_PS_COWAT (number)_1 [ 0.7627; 1.4925]
## mogg, 2007_HF-RTMS_CM_RPS_Stroop RT (seconds)_1 [ 0.7627; 1.4925]
## mondino, 2015_TDCS_10-20EG_P_PANSS_1 [-3.9072; 0.0122]
## mondino, 2015_TDCS_10-20EG_N_PANSS_1 [-3.9072; 0.0122]
## mondino, 2015_TDCS_10-20EG_G_PANSS_1 [-3.9072; 0.0122]
## mondino, 2015_TDCS_10-20EG_P_AHRS_1 [-3.9072; 0.0122]
## novak, 2006_HF-RTMS_CM_T_PANSS_1 [ 0.7627; 1.4925]
## novak, 2006_HF-RTMS_CM_P_PANSS_1 [ 0.7627; 1.4925]
## novak, 2006_HF-RTMS_CM_N_PANSS_1 [ 0.7627; 1.4925]
## novak, 2006_HF-RTMS_CM_G_PANSS_1 [ 0.7627; 1.4925]
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_SAPS_1 [-1.2116; 1.5433]
## paillere-martinot, 2017_LF-RTMS_NEURONAV_N_SANS_1 [-1.2116; 1.5433]
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_AHRS_1 [-1.2116; 1.5433]
## palm, 2016_TDCS_10-20EEG_T_PANSS_1 [-0.6463; -0.0821]
## palm, 2016_TDCS_10-20EEG_P_PANSS_1 [-0.6463; -0.0821]
## palm, 2016_TDCS_10-20EEG_N_PANSS_1 [-0.6463; -0.0821]
## palm, 2016_TDCS_10-20EEG_N_SANS_1 [-0.6463; -0.0821]
## palm, 2016_TDCS_10-20EEG_WM_SOPT_1 [-0.6463; -0.0821]
## palm, 2016_TDCS_10-20EEG_PS_TMT-A_1 [-0.6463; -0.0821]
## palm, 2016_TDCS_10-20EEG_RPS_TMT-B_1 [-0.6463; -0.0821]
## prikryl, 2007_HF-RTMS_CM_T_PANSS_1 [ 0.7627; 1.4925]
## prikryl, 2007_HF-RTMS_CM_P_PANSS_1 [ 0.7627; 1.4925]
## prikryl, 2007_HF-RTMS_CM_N_PANSS_1 [ 0.7627; 1.4925]
## prikryl, 2007_HF-RTMS_CM_N_SANS_1 [ 0.7627; 1.4925]
## prikryl, 2007_HF-RTMS_CM_P_SAPS_1 [ 0.7627; 1.4925]
## prikryl, 2012_HF-RTMS_CM_P_PANSS_1 [ 0.7627; 1.4925]
## prikryl, 2012_HF-RTMS_CM_N_PANSS_1 [ 0.7627; 1.4925]
## prikryl, 2012_HF-RTMS_CM_G_PANSS_1 [ 0.7627; 1.4925]
## prikryl, 2012_HF-RTMS_CM_T_PANSS_1 [ 0.7627; 1.4925]
## prikryl, 2012_HF-RTMS_CM_PS_VFT_1 [ 0.7627; 1.4925]
## prikryl, 2014_HF-RTMS_CM_T_PANSS_1 [ 0.7627; 1.4925]
## prikryl, 2014_HF-RTMS_CM_P_PANSS_1 [ 0.7627; 1.4925]
## prikryl, 2014_HF-RTMS_CM_N_PANSS_1 [ 0.7627; 1.4925]
## prikryl, 2014_HF-RTMS_CM_G_PANSS_1 [ 0.7627; 1.4925]
## prikryl, 2013_HF-RTMS_CM_N_SANS_1 [ 0.7627; 1.4925]
## prikryl, 2013_HF-RTMS_CM_P_SAPS_1 [ 0.7627; 1.4925]
## quan, 2015_HF-RTMS_CM_T_PANSS_1 [ 0.7627; 1.4925]
## quan, 2015_HF-RTMS_CM_P_PANSS_1 [ 0.7627; 1.4925]
## quan, 2015_HF-RTMS_CM_N_PANSS_1 [ 0.7627; 1.4925]
## quan, 2015_HF-RTMS_CM_G_PANSS_1 [ 0.7627; 1.4925]
## quan, 2015_HF-RTMS_CM_N_SANS_1 [ 0.7627; 1.4925]
## rabany, 2014_DTMS_CM_T_PANSS_1 [-0.5366; 0.9031]
## rabany, 2014_DTMS_CM_N_PANSS_1 [-0.5366; 0.9031]
## rabany, 2014_DTMS_CM_N_SANS_1 [-0.5366; 0.9031]
## rabany, 2014_DTMS_CM_AV_RVP-A_1 [-0.5366; 0.9031]
## rabany, 2014_DTMS_CM_AV_RVP-B_1 [-0.5366; 0.9031]
## rabany, 2014_DTMS_CM_WM_SWM (Total between search errors)_1 [-0.5366; 0.9031]
## rabany, 2014_DTMS_CM_WM_SWM (Strategy score)_1 [-0.5366; 0.9031]
## rabany, 2014_DTMS_CM_RPS_SOC (Minimum move solutions for test trials)_1 [-0.5366; 0.9031]
## rabany, 2014_DTMS_CM_RPS_SOC (Initial times for 5 move problems)_1 [-0.5366; 0.9031]
## rabany, 2014_DTMS_CM_RPS_SOC (Subsequent times for 5 move problems)_1 [-0.5366; 0.9031]
## rabany, 2014_DTMS_CM_PS_RTI (Mean reaction time, stages 4 and 5)_1 [-0.5366; 0.9031]
## rabany, 2014_DTMS_CM_PS_RTI (Mean movement time, stages 4 and 5)_1 [-0.5366; 0.9031]
## rollnik, 2000_HF-RTMS_CM_T_BPRS_1 [ 0.7627; 1.4925]
## rollnik, 2000_HF-RTMS_CM_PS_NCT (seconds)_1 [ 0.7627; 1.4925]
## rosa, 2007_LF-RTMS_10-20EEG_T_PANSS_1 [ 1.8489; 2.6528]
## rosa, 2007_LF-RTMS_10-20EEG_P_PANSS_1 [ 1.8489; 2.6528]
## rosa, 2007_LF-RTMS_10-20EEG_N_PANSS_1 [ 1.8489; 2.6528]
## rosa, 2007_LF-RTMS_10-20EEG_G_PANSS_1 [ 1.8489; 2.6528]
## rosenberg, 2012_LF-RTMS_CM_P_AHRS_1 [-1.9085; 0.6340]
## saba, 2006_LF-RTMS_CM_T_PANSS_1 [-1.9085; 0.6340]
## saba, 2006_LF-RTMS_CM_P_PANSS_1 [-1.9085; 0.6340]
## saba, 2006_LF-RTMS_CM_N_PANSS_1 [-1.9085; 0.6340]
## saba, 2006_LF-RTMS_CM_G_PANSS_1 [-1.9085; 0.6340]
## schilling, 2021_TDCS_10-20EEG_WM_Verbal Working Memory Reaction Time (t-score)_1 [-0.6463; -0.0821]
## schilling, 2021_TDCS_10-20EEG_WM_Verbal Working Memory d-prime (z-score)_1 [-0.6463; -0.0821]
## schilling, 2021_TDCS_10-20EEG_RPS_Response Inhibition Reaction Time (t-score)_1 [-0.6463; -0.0821]
## schilling, 2021_TDCS_10-20EEG_RPS_Response Inhibition Errors (t-scores)_1 [-0.6463; -0.0821]
## schilling, 2021_TDCS_10-20EEG_RPS_Problem solving t-score_1 [-0.6463; -0.0821]
## schilling, 2021_TDCS_10-20EEG_RPS_Mental Flexibility Speed (t-score)_1 [-0.6463; -0.0821]
## schilling, 2021_TDCS_10-20EEG_RPS_Mental Flexibility Accuracy (t-score)_1 [-0.6463; -0.0821]
## singh, 2020_HF-RTMS_CM_P_PANSS_1 [ 0.7627; 1.4925]
## singh, 2020_HF-RTMS_CM_N_PANSS_1 [ 0.7627; 1.4925]
## singh, 2020_HF-RTMS_CM_N_SANS_1 [ 0.7627; 1.4925]
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_AHRS_1 [-1.2116; 1.5433]
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_PANSS_1 [-1.2116; 1.5433]
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_AHRS_1 [ 1.8489; 2.6528]
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_PANSS_1 [ 1.8489; 2.6528]
## smith, 2015_TDCS_10-20EEG_GC_MCCB_1 [-0.6463; -0.0821]
## smith, 2015_TDCS_10-20EEG_WM_MCCB_1 [-0.6463; -0.0821]
## smith, 2015_TDCS_10-20EEG_AV_MCCB_1 [-0.6463; -0.0821]
## smith, 2015_TDCS_10-20EEG_RPS_MCCB_1 [-0.6463; -0.0821]
## smith, 2015_TDCS_10-20EEG_VerL_MCCB_1 [-0.6463; -0.0821]
## smith, 2015_TDCS_10-20EEG_VisL_MCCB_1 [-0.6463; -0.0821]
## smith, 2015_TDCS_10-20EEG_PS_MCCB_1 [-0.6463; -0.0821]
## smith, 2015_TDCS_10-20EEG_SC_MCCB_1 [-0.6463; -0.0821]
## smith, 2015_TDCS_10-20EEG_T_PANSS_1 [-0.6463; -0.0821]
## smith, 2015_TDCS_10-20EEG_P_PANSS_1 [-0.6463; -0.0821]
## smith, 2015_TDCS_10-20EEG_N_PANSS_1 [-0.6463; -0.0821]
## smith, 2015_TDCS_10-20EEG_G_PANSS_1 [-0.6463; -0.0821]
## smith, 2020_TDCS_10-20EEG_GC_MCCB_1 [-0.6463; -0.0821]
## smith, 2020_TDCS_10-20EEG_PS_MCCB_1 [-0.6463; -0.0821]
## smith, 2020_TDCS_10-20EEG_AV_MCCB_1 [-0.6463; -0.0821]
## smith, 2020_TDCS_10-20EEG_WM_MCCB_1 [-0.6463; -0.0821]
## smith, 2020_TDCS_10-20EEG_VerL_MCCB_1 [-0.6463; -0.0821]
## smith, 2020_TDCS_10-20EEG_VisL_MCCB_1 [-0.6463; -0.0821]
## smith, 2020_TDCS_10-20EEG_RPS_MCCB_1 [-0.6463; -0.0821]
## smith, 2020_TDCS_10-20EEG_SC_MCCB_1 [-0.6463; -0.0821]
## smith, 2020_TDCS_10-20EEG_AV_PASAT (Number Correct)_1 [-0.6463; -0.0821]
## smith, 2020_TDCS_10-20EEG_T_PANSS_1 [-0.6463; -0.0821]
## smith, 2020_TDCS_10-20EEG_P_PANSS_1 [-0.6463; -0.0821]
## smith, 2020_TDCS_10-20EEG_N_PANSS_1 [-0.6463; -0.0821]
## su, 2023b_HF-RTMS_NEURONAV_T_PANSS_1 [ 0.0140; 1.2286]
## su, 2023b_HF-RTMS_NEURONAV_P_PANSS_1 [ 0.0140; 1.2286]
## su, 2023b_HF-RTMS_NEURONAV_N_PANSS_1 [ 0.0140; 1.2286]
## su, 2023b_HF-RTMS_NEURONAV_G_PANSS_1 [ 0.0140; 1.2286]
## su, 2022_HF-RTMS_NEURONAV_T_PANSS_1 [ 0.0140; 1.2286]
## su, 2022_HF-RTMS_NEURONAV_P_PANSS_1 [ 0.0140; 1.2286]
## su, 2022_HF-RTMS_NEURONAV_N_PANSS_1 [ 0.0140; 1.2286]
## su, 2022_HF-RTMS_NEURONAV_G_PANSS_1 [ 0.0140; 1.2286]
## tikka, 2017_CTBS_NEURONAV_P_PANSS_1 [-1.2958; 0.9364]
## tikka, 2017_CTBS_NEURONAV_N_PANSS_1 [-1.2958; 0.9364]
## tikka, 2017_CTBS_NEURONAV_G_PANSS_1 [-1.2958; 0.9364]
## tikka, 2017_CTBS_NEURONAV_T_PANSS_1 [-1.2958; 0.9364]
## tikka, 2017_CTBS_NEURONAV_RPS_Self-Monitoring Task_1 [-1.2958; 0.9364]
## tikka, 2017_CTBS_NEURONAV_WM_Visual Memory Task_1 [-1.2958; 0.9364]
## tyagi, 2022_CTBS_10-20EEG_P_PANSS_1 [-3.1344; -1.3830]
## tyagi, 2022_CTBS_10-20EEG_N_PANSS_1 [-3.1344; -1.3830]
## tyagi, 2022_CTBS_10-20EEG_T_PANSS_1 [-3.1344; -1.3830]
## tyagi, 2022_CTBS_10-20EEG_G_PANSS_1 [-3.1344; -1.3830]
## tyagi, 2022_CTBS_10-20EEG_P_AVHRS_1 [-3.1344; -1.3830]
## tyagi, 2022_CTBS_10-20EEG_P_PSYRAT-AH_1 [-3.1344; -1.3830]
## valiengo, 2020_TDCS_10-20EEG_N_PANSS_1 [-0.6463; -0.0821]
## valiengo, 2020_TDCS_10-20EEG_P_PANSS_1 [-0.6463; -0.0821]
## valiengo, 2020_TDCS_10-20EEG_T_PANSS_1 [-0.6463; -0.0821]
## valiengo, 2020_TDCS_10-20EEG_G_PANSS_1 [-0.6463; -0.0821]
## valiengo, 2020_TDCS_10-20EEG_P_AVHRS_1 [-0.6463; -0.0821]
## vercammen, 2011_TDCS_10-20EEG_RPS_Weather Prediction Test_1 [-0.6463; -0.0821]
## vergallito, 2024_ITBS_10-20EEG_T_PANSS_1 [ 1.2009; 2.2101]
## vergallito, 2024_ITBS_10-20EEG_P_PANSS_1 [ 1.2009; 2.2101]
## vergallito, 2024_ITBS_10-20EEG_N_PANSS_1 [ 1.2009; 2.2101]
## vergallito, 2024_ITBS_10-20EEG_N_BNSS_1 [ 1.2009; 2.2101]
## vergallito, 2024_ITBS_10-20EEG_GC_MCCB_1 [ 1.2009; 2.2101]
## vergallito, 2024_ITBS_10-20EEG_PS_MCCB_1 [ 1.2009; 2.2101]
## vergallito, 2024_ITBS_10-20EEG_AV_MCCB_1 [ 1.2009; 2.2101]
## vergallito, 2024_ITBS_10-20EEG_WM_MCCB_1 [ 1.2009; 2.2101]
## vergallito, 2024_ITBS_10-20EEG_VerL_MCCB_1 [ 1.2009; 2.2101]
## vergallito, 2024_ITBS_10-20EEG_VisL_MCCB_1 [ 1.2009; 2.2101]
## vergallito, 2024_ITBS_10-20EEG_RPS_MCCB_1 [ 1.2009; 2.2101]
## vergallito, 2024_ITBS_10-20EEG_SC_MCCB_1 [ 1.2009; 2.2101]
## walther-lft, 2024_UNKNOWN_STANDARD_T_PANSS_1 [-1.8311; -0.3112]
## walther-lft, 2024_UNKNOWN_STANDARD_P_PANSS_1 [-1.8311; -0.3112]
## walther-lft, 2024_UNKNOWN_STANDARD_N_PANSS_1 [-1.8311; -0.3112]
## walther-lft, 2024_UNKNOWN_STANDARD_G_PANSS_1 [-1.8311; -0.3112]
## walther-lft, 2024_UNKNOWN_STANDARD_N_BNSS_1 [-1.8311; -0.3112]
## walther-itbs, 2024_ITBS_CM_T_PANSS_1 [ 0.8792; 2.3279]
## walther-itbs, 2024_ITBS_CM_P_PANSS_1 [ 0.8792; 2.3279]
## walther-itbs, 2024_ITBS_CM_N_PANSS_1 [ 0.8792; 2.3279]
## walther-itbs, 2024_ITBS_CM_G_PANSS_1 [ 0.8792; 2.3279]
## walther-itbs, 2024_ITBS_CM_N_BNSS_1 [ 0.8792; 2.3279]
## wang, 2020_ITBS_NEURONAV_T_PANSS_1 [-0.0443; 0.5644]
## wang, 2020_ITBS_NEURONAV_P_PANSS_1 [-0.0443; 0.5644]
## wang, 2020_ITBS_NEURONAV_N_PANSS_1 [-0.0443; 0.5644]
## wang, 2020_ITBS_NEURONAV_G_PANSS_1 [-0.0443; 0.5644]
## wang, 2020_ITBS_NEURONAV_P_SAPS_1 [-0.0443; 0.5644]
## wang, 2020_ITBS_NEURONAV_N_SANS_1 [-0.0443; 0.5644]
## wang, 2020_ITBS_NEURONAV_GC_MoCA_1 [-0.0443; 0.5644]
## wang, 2020_ITBS_NEURONAV_PS_VFT_1 [-0.0443; 0.5644]
## wang, 2020_ITBS_NEURONAV_WM_Digit span (forward)_1 [-0.0443; 0.5644]
## wang, 2020_ITBS_NEURONAV_WM_Digit span (backward)_1 [-0.0443; 0.5644]
## wang, 2020_ITBS_NEURONAV_RPS_Stroop Color Test_1 [-0.0443; 0.5644]
## wang, 2020_ITBS_NEURONAV_RPS_Stroop Word Test_1 [-0.0443; 0.5644]
## wang, 2020_ITBS_NEURONAV_RPS_Stroop Interference Test_1 [-0.0443; 0.5644]
## wang, 2020_ITBS_NEURONAV_PS_TMT-A_1 [-0.0443; 0.5644]
## wang, 2020_ITBS_NEURONAV_RPS_TMT-B_1 [-0.0443; 0.5644]
## wang, 2022_ITBS_NEURONAV_P_PANSS_1 [-0.0443; 0.5644]
## wang, 2022_ITBS_NEURONAV_N_PANSS_1 [-0.0443; 0.5644]
## wang, 2022_ITBS_NEURONAV_G_PANSS_1 [-0.0443; 0.5644]
## wang, 2022_ITBS_NEURONAV_T_PANSS_1 [-0.0443; 0.5644]
## wang, 2022_ITBS_NEURONAV_P_SAPS_1 [-0.0443; 0.5644]
## wang, 2022_ITBS_NEURONAV_N_SANS_1 [-0.0443; 0.5644]
## wang, 2022_ITBS_NEURONAV_GC_MoCA_1 [-0.0443; 0.5644]
## wang, 2022_ITBS_NEURONAV_WM_3-back RT_1 [-0.0443; 0.5644]
## weickert, 2019_TDCS_10-20EEG_T_PANSS_1 [-0.6463; -0.0821]
## weickert, 2019_TDCS_10-20EEG_P_PANSS_1 [-0.6463; -0.0821]
## weickert, 2019_TDCS_10-20EEG_N_PANSS_1 [-0.6463; -0.0821]
## weickert, 2019_TDCS_10-20EEG_G_PANSS_1 [-0.6463; -0.0821]
## weickert, 2019_TDCS_10-20EEG_P_AHRS_1 [-0.6463; -0.0821]
## weickert, 2019_TDCS_10-20EEG_PS_BACS sc_1 [-0.6463; -0.0821]
## weickert, 2019_TDCS_10-20EEG_PS_TMT-A_1 [-0.6463; -0.0821]
## weickert, 2019_TDCS_10-20EEG_WM_LNS_1 [-0.6463; -0.0821]
## weickert, 2019_TDCS_10-20EEG_VerL_HVLTr_1 [-0.6463; -0.0821]
## weickert, 2019_TDCS_10-20EEG_VisL_BVMT_1 [-0.6463; -0.0821]
## weickert, 2019_TDCS_10-20EEG_RPS_NAB maze_1 [-0.6463; -0.0821]
## weickert, 2019_TDCS_10-20EEG_PS_fluency_1 [-0.6463; -0.0821]
## wen, 2021_HF-RTMS_CM_T_PANSS_1 [ 0.7627; 1.4925]
## wen, 2021_HF-RTMS_CM_P_PANSS_1 [ 0.7627; 1.4925]
## wen, 2021_HF-RTMS_CM_N_PANSS_1 [ 0.7627; 1.4925]
## wen, 2021_HF-RTMS_CM_G_PANSS_1 [ 0.7627; 1.4925]
## wen, 2021_HF-RTMS_CM_GC_RBANS-T_1 [ 0.7627; 1.4925]
## wen, 2021_HF-RTMS_CM_VerL_RBANS\r\nImmediate memory_1 [ 0.7627; 1.4925]
## wen, 2021_HF-RTMS_CM_WM_RBANS\r\nAttention_1 [ 0.7627; 1.4925]
## wen, 2021_HF-RTMS_CM_VisL_RBANS\r\nVisuospatial_1 [ 0.7627; 1.4925]
## wen, 2021_HF-RTMS_CM_VisL_RBANS\r\nDelayed memory_1 [ 0.7627; 1.4925]
## wen, 2021_HF-RTMS_CM_VerL_RBANS\r\nLanguage_1 [ 0.7627; 1.4925]
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n1 word (s)_1 [ 0.7627; 1.4925]
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n2 word (s)_1 [ 0.7627; 1.4925]
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n3 word (s)_1 [ 0.7627; 1.4925]
## wen, 2021_HF-RTMS_CM_RPS_SCWT\r\n3 color (s)_1 [ 0.7627; 1.4925]
## wobrock, 2015_HF-RTMS_10-20EEG_T_PANSS_1 [ 0.8610; 1.4821]
## wobrock, 2015_HF-RTMS_10-20EEG_P_PANSS_1 [ 0.8610; 1.4821]
## wobrock, 2015_HF-RTMS_10-20EEG_N_PANSS_1 [ 0.8610; 1.4821]
## xie, 2023-a_LF-RTMS_10-20EEG_T_PANSS_1 [ 1.8489; 2.6528]
## xie, 2023-a_LF-RTMS_10-20EEG_P_PANSS_1 [ 1.8489; 2.6528]
## xie, 2023-a_LF-RTMS_10-20EEG_N_PANSS_1 [ 1.8489; 2.6528]
## xie, 2023-a_LF-RTMS_10-20EEG_G_PANSS_1 [ 1.8489; 2.6528]
## xie, 2023-a_LF-RTMS_10-20EEG_P_AHRS_1 [ 1.8489; 2.6528]
## xiu-10hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 [ 0.0140; 1.2286]
## xiu-10hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 [ 0.0140; 1.2286]
## xiu-10hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 [ 0.0140; 1.2286]
## xiu-10hz, 2020_HF-RTMS_NEURONAV_G_PANSS_1 [ 0.0140; 1.2286]
## xiu-10hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 [ 0.0140; 1.2286]
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nImmediate memory_1 [ 0.0140; 1.2286]
## xiu-10hz, 2020_HF-RTMS_NEURONAV_WM_RBANS\r\nAttention_1 [ 0.0140; 1.2286]
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nVisuospatial_1 [ 0.0140; 1.2286]
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nDelayed memory_1 [ 0.0140; 1.2286]
## xiu-10hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nLanguage_1 [ 0.0140; 1.2286]
## xiu-20hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 [ 0.0140; 1.2286]
## xiu-20hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 [ 0.0140; 1.2286]
## xiu-20hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 [ 0.0140; 1.2286]
## xiu-20hz, 2020_HF-RTMS_NEURONAV_G_PANSS_1 [ 0.0140; 1.2286]
## xiu-20hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 [ 0.0140; 1.2286]
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nImmediate memory_1 [ 0.0140; 1.2286]
## xiu-20hz, 2020_HF-RTMS_NEURONAV_WM_RBANS\r\nAttention_1 [ 0.0140; 1.2286]
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nVisuospatial_1 [ 0.0140; 1.2286]
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VisL_RBANS\r\nDelayed memory_1 [ 0.0140; 1.2286]
## xiu-20hz, 2020_HF-RTMS_NEURONAV_VerL_RBANS\r\nLanguage_1 [ 0.0140; 1.2286]
## xu, 2023_HD-TDCS_10-20EEG_T_PANSS_1 [-0.5560; 2.9093]
## xu, 2023_HD-TDCS_10-20EEG_P_PANSS_1 [-0.5560; 2.9093]
## xu, 2023_HD-TDCS_10-20EEG_N_PANSS_1 [-0.5560; 2.9093]
## xu, 2023_HD-TDCS_10-20EEG_G_PANSS_1 [-0.5560; 2.9093]
## xu, 2023_HD-TDCS_10-20EEG_GC_RBANS_1 [-0.5560; 2.9093]
## ye-20hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 [ 0.0140; 1.2286]
## ye-20hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Immediate memory_1 [ 0.0140; 1.2286]
## ye-20hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Visuospatial_1 [ 0.0140; 1.2286]
## ye-20hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Language_1 [ 0.0140; 1.2286]
## ye-20hz, 2024_HF-RTMS_NEURONAV_WM_RBANS - Attention_1 [ 0.0140; 1.2286]
## ye-20hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Delayed memory_1 [ 0.0140; 1.2286]
## ye-10hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 [ 0.0140; 1.2286]
## ye-10hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Immediate memory_1 [ 0.0140; 1.2286]
## ye-10hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Visuospatial_1 [ 0.0140; 1.2286]
## ye-10hz, 2024_HF-RTMS_NEURONAV_VerL_RBANS - Language_1 [ 0.0140; 1.2286]
## ye-10hz, 2024_HF-RTMS_NEURONAV_WM_RBANS - Attention_1 [ 0.0140; 1.2286]
## ye-10hz, 2024_HF-RTMS_NEURONAV_VisL_RBANS - Delayed memory_1 [ 0.0140; 1.2286]
## yuanjun, 2024_LF-RTMS_10-20EEG_T_PANSS_1 [ 1.8489; 2.6528]
## yuanjun, 2024_LF-RTMS_10-20EEG_P_PANSS_1 [ 1.8489; 2.6528]
## yuanjun, 2024_LF-RTMS_10-20EEG_N_PANSS_1 [ 1.8489; 2.6528]
## yuanjun, 2024_LF-RTMS_10-20EEG_G_PANSS_1 [ 1.8489; 2.6528]
## yuanjun, 2024_LF-RTMS_10-20EEG_P_AHRS_1 [ 1.8489; 2.6528]
## zhai-a, 2023_HF-RTMS_NA_T_PANSS_1 [-0.9948; 1.5954]
## zhang, 2022_TACS_10-20EEG_T_PANSS_1 [-2.0805; 0.1966]
## zhang, 2022_TACS_10-20EEG_P_PANSS_1 [-2.0805; 0.1966]
## zhang, 2022_TACS_10-20EEG_N_PANSS_1 [-2.0805; 0.1966]
## zhang, 2022_TACS_10-20EEG_P_AHRS_1 [-2.0805; 0.1966]
## zhao-tbs, 2014_ITBS_10-20EEG_T_PANSS_1 [ 1.2009; 2.2101]
## zhao-tbs, 2014_ITBS_10-20EEG_P_PANSS_1 [ 1.2009; 2.2101]
## zhao-tbs, 2014_ITBS_10-20EEG_N_PANSS_1 [ 1.2009; 2.2101]
## zhao-tbs, 2014_ITBS_10-20EEG_G_PANSS_1 [ 1.2009; 2.2101]
## zhao-tbs, 2014_ITBS_10-20EEG_N_SANS_1 [ 1.2009; 2.2101]
## zhao-20hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 [ 0.8610; 1.4821]
## zhao-20hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 [ 0.8610; 1.4821]
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 [ 0.8610; 1.4821]
## zhao-20hz, 2014_HF-RTMS_10-20EEG_G_PANSS_1 [ 0.8610; 1.4821]
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 [ 0.8610; 1.4821]
## zhao-10hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 [ 0.8610; 1.4821]
## zhao-10hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 [ 0.8610; 1.4821]
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 [ 0.8610; 1.4821]
## zhao-10hz, 2014_HF-RTMS_10-20EEG_G_PANSS_1 [ 0.8610; 1.4821]
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 [ 0.8610; 1.4821]
## zhou, 2024_HF-RTMS_10-20EEG_P_PANSS_1 [ 0.8610; 1.4821]
## zhou, 2024_HF-RTMS_10-20EEG_N_PANSS_1 [ 0.8610; 1.4821]
## zhou, 2024_HF-RTMS_10-20EEG_T_PANSS_1 [ 0.8610; 1.4821]
## zhou, 2024_HF-RTMS_10-20EEG_G_PANSS_1 [ 0.8610; 1.4821]
## zhou, 2024_HF-RTMS_10-20EEG_GC_RBANS-T_1 [ 0.8610; 1.4821]
## zhou, 2024_HF-RTMS_10-20EEG_VerL_RBANS\r\nImmediate memory_1 [ 0.8610; 1.4821]
## zhou, 2024_HF-RTMS_10-20EEG_VisL_RBANS\r\nVisuospatial_1 [ 0.8610; 1.4821]
## zhou, 2024_HF-RTMS_10-20EEG_VerL_RBANS\r\nLanguage_1 [ 0.8610; 1.4821]
## zhou, 2024_HF-RTMS_10-20EEG_WM_RBANS\r\nAttention_1 [ 0.8610; 1.4821]
## zhou, 2024_HF-RTMS_10-20EEG_VisL_RBANS\r\nDelayed memory_1 [ 0.8610; 1.4821]
## zhou, 2024_HF-RTMS_10-20EEG_RPS_SCWT \r\nInference scores_1 [ 0.8610; 1.4821]
## zhou, 2023_TDCS_10-20EEG_T_PANSS_1 [-0.6463; -0.0821]
## zhou, 2023_TDCS_10-20EEG_N_SANS_1 [-0.6463; -0.0821]
## zhou, 2023_TDCS_10-20EEG_RPS_IED total errors_1 [-0.6463; -0.0821]
## zhu, 2021_ITBS_CM_N_PANSS_1 [ 0.8792; 2.3279]
## zhuo, 2019_HF-RTMS_10-20EEG_T_PANSS_1 [ 0.8610; 1.4821]
## zhuo, 2019_HF-RTMS_10-20EEG_P_PANSS_1 [ 0.8610; 1.4821]
## zhuo, 2019_HF-RTMS_10-20EEG_N_PANSS_1 [ 0.8610; 1.4821]
## zhuo, 2019_HF-RTMS_10-20EEG_G_PANSS_1 [ 0.8610; 1.4821]
## zhuo, 2019_HF-RTMS_10-20EEG_N_SANS_1 [ 0.8610; 1.4821]
## zhuo, 2019_HF-RTMS_10-20EEG_PS_MCCB TMT-A_1 [ 0.8610; 1.4821]
## zhuo, 2019_HF-RTMS_10-20EEG_PS_MCCB BACS_1 [ 0.8610; 1.4821]
## zhuo, 2019_HF-RTMS_10-20EEG_PS_MCCB Fluency_1 [ 0.8610; 1.4821]
## zhuo, 2019_HF-RTMS_10-20EEG_WM_MCCB Working memory (WMS-SS)_1 [ 0.8610; 1.4821]
## zhuo, 2019_HF-RTMS_10-20EEG_VerL_MCCB Verbal learning (HVLT-R)_1 [ 0.8610; 1.4821]
## zhuo, 2019_HF-RTMS_10-20EEG_VisL_MCCB Visual learning (BVMT-R)_1 [ 0.8610; 1.4821]
## zhuo, 2019_HF-RTMS_10-20EEG_RPS_MCCB Reasoning/problem solving (NAB)_1 [ 0.8610; 1.4821]
## zhuo, 2019_HF-RTMS_10-20EEG_SC_MCCB Social cognition (MSCEIT)_1 [ 0.8610; 1.4821]
## zhuo, 2019_HF-RTMS_10-20EEG_GC_MCCB Composite score_1 [ 0.8610; 1.4821]
##
## Number of studies: k = 677
## Number of pairwise comparisons: m = 677
## Number of treatments: n = 25
## Number of designs: d = 24
##
## Random effects model
##
## Treatment estimate (sm = 'MD', comparison: other treatments vs 'SHAM'):
## MD 95%-CI z p-value
## CTBS_10-20EEG -2.2587 [-3.1344; -1.3830] -5.06 < 0.0001
## CTBS_CM 1.9362 [ 0.1221; 3.7502] 2.09 0.0364
## CTBS_NEURONAV -0.1797 [-1.2958; 0.9364] -0.32 0.7523
## DTMS_CM 0.1833 [-0.5366; 0.9031] 0.50 0.6178
## HD-TDCS_10-10EEG 1.2666 [-0.3399; 2.8731] 1.55 0.1223
## HD-TDCS_10-20EEG 1.1766 [-0.5560; 2.9093] 1.33 0.1832
## HF-RTMS_10-20EEG 1.1715 [ 0.8610; 1.4821] 7.39 < 0.0001
## HF-RTMS_CM 1.1276 [ 0.7627; 1.4925] 6.06 < 0.0001
## HF-RTMS_NA 0.3003 [-0.9948; 1.5954] 0.45 0.6495
## HF-RTMS_NEURONAV 0.6213 [ 0.0140; 1.2286] 2.01 0.0450
## ITBS_10-20EEG 1.7055 [ 1.2009; 2.2101] 6.62 < 0.0001
## ITBS_CM 1.6035 [ 0.8792; 2.3279] 4.34 < 0.0001
## ITBS_NA 0.8017 [ 0.1130; 1.4904] 2.28 0.0225
## ITBS_NEURONAV 0.2601 [-0.0443; 0.5644] 1.67 0.0940
## LF-RTMS_10-10EEG 2.7018 [ 1.8523; 3.5514] 6.23 < 0.0001
## LF-RTMS_10-20EEG 2.2509 [ 1.8489; 2.6528] 10.97 < 0.0001
## LF-RTMS_CM -0.6373 [-1.9085; 0.6340] -0.98 0.3259
## LF-RTMS_NEURONAV 0.1658 [-1.2116; 1.5433] 0.24 0.8135
## PRM-RTMS_NEURONAV 0.9325 [-0.9417; 2.8067] 0.98 0.3295
## SHAM . . . .
## TACS_10-20EEG 0.9420 [-0.1966; 2.0805] 1.62 0.1049
## TDCS_10-20 EEG 1.3936 [ 0.5916; 2.1956] 3.41 0.0007
## TDCS_10-20EEG 0.3642 [ 0.0821; 0.6463] 2.53 0.0114
## TDCS_10-20EG 1.9475 [-0.0122; 3.9072] 1.95 0.0514
## UNKNOWN_STANDARD 1.0712 [ 0.3112; 1.8311] 2.76 0.0057
##
## Quantifying heterogeneity / inconsistency:
## tau^2 = 0.4638; tau = 0.6811; I^2 = 81.6% [80.2%; 82.8%]
##
## Tests of heterogeneity (within designs) and inconsistency (between designs):
## Q d.f. p-value
## Total 3540.43 653 0
## Within designs 3540.43 653 0
## Between designs 0.00 0 --
##
## Details of network meta-analysis methods:
## - Frequentist graph-theoretical approach
## - DerSimonian-Laird estimator for tau^2
## - Calculation of I^2 based on Q
##
## Forest Plot:
##
## Network Graph:
##
## League Table for All Domains :
## CTBS_10-20EEG CTBS_CM
## CTBS_10-20EEG CTBS_10-20EEG .
## CTBS_CM -4.19 [-6.21; -2.18] CTBS_CM
## CTBS_NEURONAV -2.08 [-3.50; -0.66] 2.12 [-0.01; 4.25]
## DTMS_CM -2.44 [-3.58; -1.31] 1.75 [-0.20; 3.70]
## HD-TDCS_10-10EEG -3.53 [-5.35; -1.70] 0.67 [-1.75; 3.09]
## HD-TDCS_10-20EEG -3.44 [-5.38; -1.49] 0.76 [-1.75; 3.27]
## HF-RTMS_10-20EEG -3.43 [-4.36; -2.50] 0.76 [-1.08; 2.61]
## HF-RTMS_CM -3.39 [-4.33; -2.44] 0.81 [-1.04; 2.66]
## HF-RTMS_NA -2.56 [-4.12; -1.00] 1.64 [-0.59; 3.86]
## HF-RTMS_NEURONAV -2.88 [-3.95; -1.81] 1.31 [-0.60; 3.23]
## ITBS_10-20EEG -3.96 [-4.97; -2.95] 0.23 [-1.65; 2.11]
## ITBS_CM -3.86 [-5.00; -2.73] 0.33 [-1.62; 2.29]
## ITBS_NA -3.06 [-4.17; -1.95] 1.13 [-0.81; 3.07]
## ITBS_NEURONAV -2.52 [-3.45; -1.59] 1.68 [-0.16; 3.52]
## LF-RTMS_10-10EEG -4.96 [-6.18; -3.74] -0.77 [-2.77; 1.24]
## LF-RTMS_10-20EEG -4.51 [-5.47; -3.55] -0.31 [-2.17; 1.54]
## LF-RTMS_CM -1.62 [-3.17; -0.08] 2.57 [ 0.36; 4.79]
## LF-RTMS_NEURONAV -2.42 [-4.06; -0.79] 1.77 [-0.51; 4.05]
## PRM-RTMS_NEURONAV -3.19 [-5.26; -1.12] 1.00 [-1.60; 3.61]
## SHAM -2.26 [-3.13; -1.38] 1.94 [ 0.12; 3.75]
## TACS_10-20EEG -3.20 [-4.64; -1.76] 0.99 [-1.15; 3.14]
## TDCS_10-20 EEG -3.65 [-4.84; -2.46] 0.54 [-1.44; 2.53]
## TDCS_10-20EEG -2.62 [-3.54; -1.70] 1.57 [-0.26; 3.41]
## TDCS_10-20EG -4.21 [-6.35; -2.06] -0.01 [-2.68; 2.66]
## UNKNOWN_STANDARD -3.33 [-4.49; -2.17] 0.87 [-1.10; 2.83]
## CTBS_NEURONAV DTMS_CM
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV CTBS_NEURONAV .
## DTMS_CM -0.36 [-1.69; 0.97] DTMS_CM
## HD-TDCS_10-10EEG -1.45 [-3.40; 0.51] -1.08 [-2.84; 0.68]
## HD-TDCS_10-20EEG -1.36 [-3.42; 0.70] -0.99 [-2.87; 0.88]
## HF-RTMS_10-20EEG -1.35 [-2.51; -0.19] -0.99 [-1.77; -0.20]
## HF-RTMS_CM -1.31 [-2.48; -0.13] -0.94 [-1.75; -0.14]
## HF-RTMS_NA -0.48 [-2.19; 1.23] -0.12 [-1.60; 1.36]
## HF-RTMS_NEURONAV -0.80 [-2.07; 0.47] -0.44 [-1.38; 0.50]
## ITBS_10-20EEG -1.89 [-3.11; -0.66] -1.52 [-2.40; -0.64]
## ITBS_CM -1.78 [-3.11; -0.45] -1.42 [-2.44; -0.40]
## ITBS_NA -0.98 [-2.29; 0.33] -0.62 [-1.61; 0.38]
## ITBS_NEURONAV -0.44 [-1.60; 0.72] -0.08 [-0.86; 0.70]
## LF-RTMS_10-10EEG -2.88 [-4.28; -1.48] -2.52 [-3.63; -1.41]
## LF-RTMS_10-20EEG -2.43 [-3.62; -1.24] -2.07 [-2.89; -1.24]
## LF-RTMS_CM 0.46 [-1.23; 2.15] 0.82 [-0.64; 2.28]
## LF-RTMS_NEURONAV -0.35 [-2.12; 1.43] 0.02 [-1.54; 1.57]
## PRM-RTMS_NEURONAV -1.11 [-3.29; 1.07] -0.75 [-2.76; 1.26]
## SHAM -0.18 [-1.30; 0.94] 0.18 [-0.54; 0.90]
## TACS_10-20EEG -1.12 [-2.72; 0.47] -0.76 [-2.11; 0.59]
## TDCS_10-20 EEG -1.57 [-2.95; -0.20] -1.21 [-2.29; -0.13]
## TDCS_10-20EEG -0.54 [-1.70; 0.61] -0.18 [-0.95; 0.59]
## TDCS_10-20EG -2.13 [-4.38; 0.13] -1.76 [-3.85; 0.32]
## UNKNOWN_STANDARD -1.25 [-2.60; 0.10] -0.89 [-1.93; 0.16]
## HD-TDCS_10-10EEG HD-TDCS_10-20EEG
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-10EEG HD-TDCS_10-10EEG .
## HD-TDCS_10-20EEG 0.09 [-2.27; 2.45] HD-TDCS_10-20EEG
## HF-RTMS_10-20EEG 0.10 [-1.54; 1.73] 0.01 [-1.76; 1.77]
## HF-RTMS_CM 0.14 [-1.51; 1.79] 0.05 [-1.72; 1.82]
## HF-RTMS_NA 0.97 [-1.10; 3.03] 0.88 [-1.29; 3.04]
## HF-RTMS_NEURONAV 0.65 [-1.07; 2.36] 0.56 [-1.28; 2.39]
## ITBS_10-20EEG -0.44 [-2.12; 1.24] -0.53 [-2.33; 1.28]
## ITBS_CM -0.34 [-2.10; 1.43] -0.43 [-2.30; 1.45]
## ITBS_NA 0.46 [-1.28; 2.21] 0.37 [-1.49; 2.24]
## ITBS_NEURONAV 1.01 [-0.63; 2.64] 0.92 [-0.84; 2.68]
## LF-RTMS_10-10EEG -1.44 [-3.25; 0.38] -1.53 [-3.45; 0.40]
## LF-RTMS_10-20EEG -0.98 [-2.64; 0.67] -1.07 [-2.85; 0.70]
## LF-RTMS_CM 1.90 [-0.14; 3.95] 1.81 [-0.34; 3.96]
## LF-RTMS_NEURONAV 1.10 [-1.02; 3.22] 1.01 [-1.20; 3.22]
## PRM-RTMS_NEURONAV 0.33 [-2.13; 2.80] 0.24 [-2.31; 2.80]
## SHAM 1.27 [-0.34; 2.87] 1.18 [-0.56; 2.91]
## TACS_10-20EEG 0.32 [-1.64; 2.29] 0.23 [-1.84; 2.31]
## TDCS_10-20 EEG -0.13 [-1.92; 1.67] -0.22 [-2.13; 1.69]
## TDCS_10-20EEG 0.90 [-0.73; 2.53] 0.81 [-0.94; 2.57]
## TDCS_10-20EG -0.68 [-3.21; 1.85] -0.77 [-3.39; 1.84]
## UNKNOWN_STANDARD 0.20 [-1.58; 1.97] 0.11 [-1.79; 2.00]
## HF-RTMS_10-20EEG HF-RTMS_CM
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-10EEG . .
## HD-TDCS_10-20EEG . .
## HF-RTMS_10-20EEG HF-RTMS_10-20EEG .
## HF-RTMS_CM 0.04 [-0.44; 0.52] HF-RTMS_CM
## HF-RTMS_NA 0.87 [-0.46; 2.20] 0.83 [-0.52; 2.17]
## HF-RTMS_NEURONAV 0.55 [-0.13; 1.23] 0.51 [-0.20; 1.21]
## ITBS_10-20EEG -0.53 [-1.13; 0.06] -0.58 [-1.20; 0.04]
## ITBS_CM -0.43 [-1.22; 0.36] -0.48 [-1.29; 0.34]
## ITBS_NA 0.37 [-0.39; 1.13] 0.33 [-0.45; 1.11]
## ITBS_NEURONAV 0.91 [ 0.48; 1.35] 0.87 [ 0.39; 1.34]
## LF-RTMS_10-10EEG -1.53 [-2.43; -0.63] -1.57 [-2.50; -0.65]
## LF-RTMS_10-20EEG -1.08 [-1.59; -0.57] -1.12 [-1.67; -0.58]
## LF-RTMS_CM 1.81 [ 0.50; 3.12] 1.76 [ 0.44; 3.09]
## LF-RTMS_NEURONAV 1.01 [-0.41; 2.42] 0.96 [-0.46; 2.39]
## PRM-RTMS_NEURONAV 0.24 [-1.66; 2.14] 0.20 [-1.71; 2.10]
## SHAM 1.17 [ 0.86; 1.48] 1.13 [ 0.76; 1.49]
## TACS_10-20EEG 0.23 [-0.95; 1.41] 0.19 [-1.01; 1.38]
## TDCS_10-20 EEG -0.22 [-1.08; 0.64] -0.27 [-1.15; 0.62]
## TDCS_10-20EEG 0.81 [ 0.39; 1.23] 0.76 [ 0.30; 1.22]
## TDCS_10-20EG -0.78 [-2.76; 1.21] -0.82 [-2.81; 1.17]
## UNKNOWN_STANDARD 0.10 [-0.72; 0.92] 0.06 [-0.79; 0.90]
## HF-RTMS_NA HF-RTMS_NEURONAV
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-10EEG . .
## HD-TDCS_10-20EEG . .
## HF-RTMS_10-20EEG . .
## HF-RTMS_CM . .
## HF-RTMS_NA HF-RTMS_NA .
## HF-RTMS_NEURONAV -0.32 [-1.75; 1.11] HF-RTMS_NEURONAV
## ITBS_10-20EEG -1.41 [-2.80; -0.02] -1.08 [-1.87; -0.29]
## ITBS_CM -1.30 [-2.79; 0.18] -0.98 [-1.93; -0.04]
## ITBS_NA -0.50 [-1.97; 0.97] -0.18 [-1.10; 0.74]
## ITBS_NEURONAV 0.04 [-1.29; 1.37] 0.36 [-0.32; 1.04]
## LF-RTMS_10-10EEG -2.40 [-3.95; -0.85] -2.08 [-3.12; -1.04]
## LF-RTMS_10-20EEG -1.95 [-3.31; -0.59] -1.63 [-2.36; -0.90]
## LF-RTMS_CM 0.94 [-0.88; 2.75] 1.26 [-0.15; 2.67]
## LF-RTMS_NEURONAV 0.13 [-1.76; 2.03] 0.46 [-1.05; 1.96]
## PRM-RTMS_NEURONAV -0.63 [-2.91; 1.65] -0.31 [-2.28; 1.66]
## SHAM 0.30 [-0.99; 1.60] 0.62 [ 0.01; 1.23]
## TACS_10-20EEG -0.64 [-2.37; 1.08] -0.32 [-1.61; 0.97]
## TDCS_10-20 EEG -1.09 [-2.62; 0.43] -0.77 [-1.78; 0.23]
## TDCS_10-20EEG -0.06 [-1.39; 1.26] 0.26 [-0.41; 0.93]
## TDCS_10-20EG -1.65 [-4.00; 0.70] -1.33 [-3.38; 0.73]
## UNKNOWN_STANDARD -0.77 [-2.27; 0.73] -0.45 [-1.42; 0.52]
## ITBS_10-20EEG ITBS_CM
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-10EEG . .
## HD-TDCS_10-20EEG . .
## HF-RTMS_10-20EEG . .
## HF-RTMS_CM . .
## HF-RTMS_NA . .
## HF-RTMS_NEURONAV . .
## ITBS_10-20EEG ITBS_10-20EEG .
## ITBS_CM 0.10 [-0.78; 0.98] ITBS_CM
## ITBS_NA 0.90 [ 0.05; 1.76] 0.80 [-0.20; 1.80]
## ITBS_NEURONAV 1.45 [ 0.86; 2.03] 1.34 [ 0.56; 2.13]
## LF-RTMS_10-10EEG -1.00 [-1.98; -0.01] -1.10 [-2.21; 0.02]
## LF-RTMS_10-20EEG -0.55 [-1.19; 0.10] -0.65 [-1.48; 0.18]
## LF-RTMS_CM 2.34 [ 0.98; 3.71] 2.24 [ 0.78; 3.70]
## LF-RTMS_NEURONAV 1.54 [ 0.07; 3.01] 1.44 [-0.12; 2.99]
## PRM-RTMS_NEURONAV 0.77 [-1.17; 2.71] 0.67 [-1.34; 2.68]
## SHAM 1.71 [ 1.20; 2.21] 1.60 [ 0.88; 2.33]
## TACS_10-20EEG 0.76 [-0.48; 2.01] 0.66 [-0.69; 2.01]
## TDCS_10-20 EEG 0.31 [-0.64; 1.26] 0.21 [-0.87; 1.29]
## TDCS_10-20EEG 1.34 [ 0.76; 1.92] 1.24 [ 0.46; 2.02]
## TDCS_10-20EG -0.24 [-2.27; 1.78] -0.34 [-2.43; 1.75]
## UNKNOWN_STANDARD 0.63 [-0.28; 1.55] 0.53 [-0.52; 1.58]
## ITBS_NA ITBS_NEURONAV LF-RTMS_10-10EEG
## CTBS_10-20EEG . . .
## CTBS_CM . . .
## CTBS_NEURONAV . . .
## DTMS_CM . . .
## HD-TDCS_10-10EEG . . .
## HD-TDCS_10-20EEG . . .
## HF-RTMS_10-20EEG . . .
## HF-RTMS_CM . . .
## HF-RTMS_NA . . .
## HF-RTMS_NEURONAV . . .
## ITBS_10-20EEG . . .
## ITBS_CM . . .
## ITBS_NA ITBS_NA . .
## ITBS_NEURONAV 0.54 [-0.21; 1.29] ITBS_NEURONAV .
## LF-RTMS_10-10EEG -1.90 [-2.99; -0.81] -2.44 [-3.34; -1.54] LF-RTMS_10-10EEG
## LF-RTMS_10-20EEG -1.45 [-2.25; -0.65] -1.99 [-2.49; -1.49] 0.45 [-0.49; 1.39]
## LF-RTMS_CM 1.44 [-0.01; 2.88] 0.90 [-0.41; 2.20] 3.34 [ 1.81; 4.87]
## LF-RTMS_NEURONAV 0.64 [-0.90; 2.18] 0.09 [-1.32; 1.50] 2.54 [ 0.92; 4.15]
## PRM-RTMS_NEURONAV -0.13 [-2.13; 1.87] -0.67 [-2.57; 1.23] 1.77 [-0.29; 3.83]
## SHAM 0.80 [ 0.11; 1.49] 0.26 [-0.04; 0.56] 2.70 [ 1.85; 3.55]
## TACS_10-20EEG -0.14 [-1.47; 1.19] -0.68 [-1.86; 0.50] 1.76 [ 0.34; 3.18]
## TDCS_10-20 EEG -0.59 [-1.65; 0.47] -1.13 [-1.99; -0.28] 1.31 [ 0.14; 2.48]
## TDCS_10-20EEG 0.44 [-0.31; 1.18] -0.10 [-0.52; 0.31] 2.34 [ 1.44; 3.23]
## TDCS_10-20EG -1.15 [-3.22; 0.93] -1.69 [-3.67; 0.30] 0.75 [-1.38; 2.89]
## UNKNOWN_STANDARD -0.27 [-1.30; 0.76] -0.81 [-1.63; 0.01] 1.63 [ 0.49; 2.77]
## LF-RTMS_10-20EEG LF-RTMS_CM LF-RTMS_NEURONAV
## CTBS_10-20EEG . . .
## CTBS_CM . . .
## CTBS_NEURONAV . . .
## DTMS_CM . . .
## HD-TDCS_10-10EEG . . .
## HD-TDCS_10-20EEG . . .
## HF-RTMS_10-20EEG . . .
## HF-RTMS_CM . . .
## HF-RTMS_NA . . .
## HF-RTMS_NEURONAV . . .
## ITBS_10-20EEG . . .
## ITBS_CM . . .
## ITBS_NA . . .
## ITBS_NEURONAV . . .
## LF-RTMS_10-10EEG . . .
## LF-RTMS_10-20EEG LF-RTMS_10-20EEG . .
## LF-RTMS_CM 2.89 [ 1.55; 4.22] LF-RTMS_CM .
## LF-RTMS_NEURONAV 2.09 [ 0.65; 3.52] -0.80 [-2.68; 1.07] LF-RTMS_NEURONAV
## PRM-RTMS_NEURONAV 1.32 [-0.60; 3.24] -1.57 [-3.83; 0.69] -0.77 [-3.09; 1.56]
## SHAM 2.25 [ 1.85; 2.65] -0.64 [-1.91; 0.63] 0.17 [-1.21; 1.54]
## TACS_10-20EEG 1.31 [ 0.10; 2.52] -1.58 [-3.29; 0.13] -0.78 [-2.56; 1.01]
## TDCS_10-20 EEG 0.86 [-0.04; 1.75] -2.03 [-3.53; -0.53] -1.23 [-2.82; 0.37]
## TDCS_10-20EEG 1.89 [ 1.40; 2.38] -1.00 [-2.30; 0.30] -0.20 [-1.60; 1.21]
## TDCS_10-20EG 0.30 [-1.70; 2.30] -2.58 [-4.92; -0.25] -1.78 [-4.18; 0.61]
## UNKNOWN_STANDARD 1.18 [ 0.32; 2.04] -1.71 [-3.19; -0.23] -0.91 [-2.48; 0.67]
## PRM-RTMS_NEURONAV SHAM
## CTBS_10-20EEG . -2.26 [-3.13; -1.38]
## CTBS_CM . 1.94 [ 0.12; 3.75]
## CTBS_NEURONAV . -0.18 [-1.30; 0.94]
## DTMS_CM . 0.18 [-0.54; 0.90]
## HD-TDCS_10-10EEG . 1.27 [-0.34; 2.87]
## HD-TDCS_10-20EEG . 1.18 [-0.56; 2.91]
## HF-RTMS_10-20EEG . 1.17 [ 0.86; 1.48]
## HF-RTMS_CM . 1.13 [ 0.76; 1.49]
## HF-RTMS_NA . 0.30 [-0.99; 1.60]
## HF-RTMS_NEURONAV . 0.62 [ 0.01; 1.23]
## ITBS_10-20EEG . 1.71 [ 1.20; 2.21]
## ITBS_CM . 1.60 [ 0.88; 2.33]
## ITBS_NA . 0.80 [ 0.11; 1.49]
## ITBS_NEURONAV . 0.26 [-0.04; 0.56]
## LF-RTMS_10-10EEG . 2.70 [ 1.85; 3.55]
## LF-RTMS_10-20EEG . 2.25 [ 1.85; 2.65]
## LF-RTMS_CM . -0.64 [-1.91; 0.63]
## LF-RTMS_NEURONAV . 0.17 [-1.21; 1.54]
## PRM-RTMS_NEURONAV PRM-RTMS_NEURONAV 0.93 [-0.94; 2.81]
## SHAM 0.93 [-0.94; 2.81] SHAM
## TACS_10-20EEG -0.01 [-2.20; 2.18] -0.94 [-2.08; 0.20]
## TDCS_10-20 EEG -0.46 [-2.50; 1.58] -1.39 [-2.20; -0.59]
## TDCS_10-20EEG 0.57 [-1.33; 2.46] -0.36 [-0.65; -0.08]
## TDCS_10-20EG -1.02 [-3.73; 1.70] -1.95 [-3.91; 0.01]
## UNKNOWN_STANDARD -0.14 [-2.16; 1.88] -1.07 [-1.83; -0.31]
## TACS_10-20EEG TDCS_10-20 EEG
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-10EEG . .
## HD-TDCS_10-20EEG . .
## HF-RTMS_10-20EEG . .
## HF-RTMS_CM . .
## HF-RTMS_NA . .
## HF-RTMS_NEURONAV . .
## ITBS_10-20EEG . .
## ITBS_CM . .
## ITBS_NA . .
## ITBS_NEURONAV . .
## LF-RTMS_10-10EEG . .
## LF-RTMS_10-20EEG . .
## LF-RTMS_CM . .
## LF-RTMS_NEURONAV . .
## PRM-RTMS_NEURONAV . .
## SHAM -0.94 [-2.08; 0.20] -1.39 [-2.20; -0.59]
## TACS_10-20EEG TACS_10-20EEG .
## TDCS_10-20 EEG -0.45 [-1.84; 0.94] TDCS_10-20 EEG
## TDCS_10-20EEG 0.58 [-0.60; 1.75] 1.03 [ 0.18; 1.88]
## TDCS_10-20EG -1.01 [-3.27; 1.26] -0.55 [-2.67; 1.56]
## UNKNOWN_STANDARD -0.13 [-1.50; 1.24] 0.32 [-0.78; 1.43]
## TDCS_10-20EEG TDCS_10-20EG
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-10EEG . .
## HD-TDCS_10-20EEG . .
## HF-RTMS_10-20EEG . .
## HF-RTMS_CM . .
## HF-RTMS_NA . .
## HF-RTMS_NEURONAV . .
## ITBS_10-20EEG . .
## ITBS_CM . .
## ITBS_NA . .
## ITBS_NEURONAV . .
## LF-RTMS_10-10EEG . .
## LF-RTMS_10-20EEG . .
## LF-RTMS_CM . .
## LF-RTMS_NEURONAV . .
## PRM-RTMS_NEURONAV . .
## SHAM -0.36 [-0.65; -0.08] -1.95 [-3.91; 0.01]
## TACS_10-20EEG . .
## TDCS_10-20 EEG . .
## TDCS_10-20EEG TDCS_10-20EEG .
## TDCS_10-20EG -1.58 [-3.56; 0.40] TDCS_10-20EG
## UNKNOWN_STANDARD -0.71 [-1.52; 0.10] 0.88 [-1.23; 2.98]
## UNKNOWN_STANDARD
## CTBS_10-20EEG .
## CTBS_CM .
## CTBS_NEURONAV .
## DTMS_CM .
## HD-TDCS_10-10EEG .
## HD-TDCS_10-20EEG .
## HF-RTMS_10-20EEG .
## HF-RTMS_CM .
## HF-RTMS_NA .
## HF-RTMS_NEURONAV .
## ITBS_10-20EEG .
## ITBS_CM .
## ITBS_NA .
## ITBS_NEURONAV .
## LF-RTMS_10-10EEG .
## LF-RTMS_10-20EEG .
## LF-RTMS_CM .
## LF-RTMS_NEURONAV .
## PRM-RTMS_NEURONAV .
## SHAM -1.07 [-1.83; -0.31]
## TACS_10-20EEG .
## TDCS_10-20 EEG .
## TDCS_10-20EEG .
## TDCS_10-20EG .
## UNKNOWN_STANDARD UNKNOWN_STANDARD
##
## Upper triangle: MD (95% CI); lower triangle: p-value
## Positive values favor the column-defining treatment
##
## Treatment Rankings (SUCRA values):
## SUCRA values not available in netrank output
##
## ==================================================
## Network Meta-Analysis for Positive Symptoms
## ==================================================
##
## Available treatments for Positive Symptoms NMA:
##
## CTBS_10-20EEG CTBS_CM CTBS_NEURONAV DTMS_CM
## 6 2 1 2
## HD-TDCS_10-10EEG HD-TDCS_10-20EEG HF-RTMS_10-20EEG HF-RTMS_CM
## 1 1 8 12
## HF-RTMS_NA HF-RTMS_NEURONAV ITBS_10-20EEG ITBS_CM
## 1 8 4 1
## ITBS_NA ITBS_NEURONAV LF-RTMS_10-10EEG LF-RTMS_10-20EEG
## 1 5 1 20
## LF-RTMS_CM LF-RTMS_NEURONAV PRM-RTMS_NEURONAV SHAM
## 4 7 3 119
## TACS_10-20EEG TDCS_10-20EEG TDCS_10-20EG UNKNOWN_STANDARD
## 4 24 2 1
##
## Running network meta-analysis for Positive Symptoms ...
##
## Summary of results:
## Original data:
##
## treat1
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## bais, 2014 - l_LF-RTMS_10-20EEG_P_AHRS_1 LF-RTMS_10-20EEG
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANAS_1 LF-RTMS_10-20EEG
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_AHRS_1 LF-RTMS_10-20EEG
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANAS_1 LF-RTMS_10-20EEG
## barr, 2012_HF-RTMS_NEURONAV_P_PANSS_1 HF-RTMS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_P_SAPS_1 ITBS_NEURONAV
## blumberger, 2012_LF-RTMS_NEURONAV_P_PSYRATS_1 LF-RTMS_NEURONAV
## blumberger, 2012_LF-RTMS_NEURONAV_P_PANSS_1 LF-RTMS_NEURONAV
## blumberger, 2012_LF-RTMS_NEURONAV_P_AHRS_1 LF-RTMS_NEURONAV
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PSYRATS_1 PRM-RTMS_NEURONAV
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PANSS_1 PRM-RTMS_NEURONAV
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_AHRS_1 PRM-RTMS_NEURONAV
## bose, 2018_TDCS_10-20EEG_P_SAPS_1 SHAM
## bose, 2018_TDCS_10-20EEG_P_AHRS_1 SHAM
## brunelin, 2012_TDCS_10-20EEG_P_AHRS_1 SHAM
## brunelin, 2006_LF-RTMS_10-20EEG_P_AHRS_1 LF-RTMS_10-20EEG
## brunelin, 2006_LF-RTMS_10-20EEG_P_SAPS_1 LF-RTMS_10-20EEG
## chauhan, 2021_ITBS_10-20EEG_P_PANSS_1 ITBS_10-20EEG
## de jesus, 2011_LF-RTMS_10-20EEG_P_BPRS_1 LF-RTMS_10-20EEG
## de jesus, 2011_LF-RTMS_10-20EEG_P_AHRS_1 LF-RTMS_10-20EEG
## dharani, 2021_HD-TDCS_10-10EEG_P_PANSS_1 HD-TDCS_10-10EEG
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## dolfus, 2018_HF-RTMS_NEURONAV_P_AHRS_1 HF-RTMS_NEURONAV
## du, 2024_HF-RTMS_NEURONAV_P_BPRS_1 HF-RTMS_NEURONAV
## du, 2022_HF-RTMS_10-20EEG_P_PANSS_1 HF-RTMS_10-20EEG
## fitzerald, 2008_LF-RTMS_CM_P_PANSS_1 LF-RTMS_CM
## fitzerald-l, 2014_TDCS_10-20EEG_P_PANSS_1 SHAM
## fitzerald-bi, 2014_TDCS_10-20EEG_P_PANSS_1 SHAM
## frohlich, 2016_TDCS_10-20EEG_P_AHRS_1 SHAM
## frohlich, 2016_TDCS_10-20EEG_P_PANSS_1 SHAM
## gao, 2024_ITBS_10-20EEG_P_PANSS_1 ITBS_10-20EEG
## garg, 2016_DTMS_CM_P_PANSS_1 DTMS_CM
## gomes, 2018_TDCS_10-20EEG_P_PANSS_1 SHAM
## guan, 2020_HF-RTMS_NEURONAV_P_PANSS_1 HF-RTMS_NEURONAV
## guleken, 2020_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## holi, 2004_HF-RTMS_10-20EEG_P_PANSS_1 HF-RTMS_10-20EEG
## hu, 2024_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## hu, 2023_LF-RTMS_10-10EEG_P_PANSS_1 LF-RTMS_10-10EEG
## huang, 2016_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## jeon, 2018_TDCS_10-20EEG_P_PANSS_1 SHAM
## jin, 2023_ITBS_NA_P_PANSS_1 ITBS_NA
## kang, 2024_CTBS_CM_P_PANSS_1 CTBS_CM
## kang, 2024_CTBS_CM_P_AHRS_1 CTBS_CM
## kantrowitz, 2019_TDCS_10-20EEG_P_AHRS_1 SHAM
## kimura, 2016_HF-RTMS_10-20EEG_P_AHRS_1 HF-RTMS_10-20EEG
## klein, 1999_LF-RTMS_CM_P_PANSS_1 LF-RTMS_CM
## koops, 2018_TDCS_10-20EEG_P_AHRS_1 SHAM
## koops, 2018_TDCS_10-20EEG_P_PANSS_1 SHAM
## koops, 2016_CTBS_10-20EEG_P_PANSS_1 CTBS_10-20EEG
## koops, 2016_CTBS_10-20EEG_P_AHRS_1 CTBS_10-20EEG
## koops, 2016_CTBS_10-20EEG_P_PSYRATS_1 CTBS_10-20EEG
## liu, 2024_HF-RTMS_NA_P_PANSS_1 HF-RTMS_NA
## lyu, 2024_TDCS_10-20EEG_P_PANSS_1 SHAM
## mao, 2023_HF-RTMS_CM_P_AHRS_1 HF-RTMS_CM
## marquardt, 2022_TDCS_10-20EEG_P_PANSS_1 SHAM
## marquardt, 2022_TDCS_10-20EEG_P_AHRS_1 SHAM
## mcintosh, 2004_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## mellin-tacs, 2018_TACS_10-20EEG_P_AHRS_1 SHAM
## mellin-tacs, 2018_TACS_10-20EEG_P_PANSS-P_1 SHAM
## mellin-tdcs, 2018_TDCS_10-20EEG_P_AHRS_1 SHAM
## mellin-tdcs, 2018_TDCS_10-20EEG_P_PANSS_1 SHAM
## moeller, 2022_DTMS_CM_P_PANSS_1 DTMS_CM
## mondino, 2015_TDCS_10-20EG_P_PANSS_1 SHAM
## mondino, 2015_TDCS_10-20EG_P_AHRS_1 SHAM
## novak, 2006_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_SAPS_1 LF-RTMS_NEURONAV
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_AHRS_1 LF-RTMS_NEURONAV
## palm, 2016_TDCS_10-20EEG_P_PANSS_1 SHAM
## prikryl, 2007_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## prikryl, 2007_HF-RTMS_CM_P_SAPS_1 HF-RTMS_CM
## prikryl, 2012_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## prikryl, 2014_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## prikryl, 2013_HF-RTMS_CM_P_SAPS_1 HF-RTMS_CM
## quan, 2015_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## rosa, 2007_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## rosenberg, 2012_LF-RTMS_CM_P_AHRS_1 LF-RTMS_CM
## saba, 2006_LF-RTMS_CM_P_PANSS_1 LF-RTMS_CM
## singh, 2020_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_AHRS_1 LF-RTMS_NEURONAV
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_PANSS_1 LF-RTMS_NEURONAV
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_AHRS_1 LF-RTMS_10-20EEG
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## smith, 2015_TDCS_10-20EEG_P_PANSS_1 SHAM
## smith, 2020_TDCS_10-20EEG_P_PANSS_1 SHAM
## su, 2023b_HF-RTMS_NEURONAV_P_PANSS_1 HF-RTMS_NEURONAV
## su, 2022_HF-RTMS_NEURONAV_P_PANSS_1 HF-RTMS_NEURONAV
## tikka, 2017_CTBS_NEURONAV_P_PANSS_1 CTBS_NEURONAV
## tyagi, 2022_CTBS_10-20EEG_P_PANSS_1 CTBS_10-20EEG
## tyagi, 2022_CTBS_10-20EEG_P_AVHRS_1 CTBS_10-20EEG
## tyagi, 2022_CTBS_10-20EEG_P_PSYRAT-AH_1 CTBS_10-20EEG
## valiengo, 2020_TDCS_10-20EEG_P_PANSS_1 SHAM
## valiengo, 2020_TDCS_10-20EEG_P_AVHRS_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_P_PANSS_1 ITBS_10-20EEG
## walther-lft, 2024_UNKNOWN_STANDARD_P_PANSS_1 SHAM
## walther-itbs, 2024_ITBS_CM_P_PANSS_1 ITBS_CM
## wang, 2020_ITBS_NEURONAV_P_PANSS_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_P_SAPS_1 ITBS_NEURONAV
## wang, 2022_ITBS_NEURONAV_P_PANSS_1 ITBS_NEURONAV
## wang, 2022_ITBS_NEURONAV_P_SAPS_1 ITBS_NEURONAV
## weickert, 2019_TDCS_10-20EEG_P_PANSS_1 SHAM
## weickert, 2019_TDCS_10-20EEG_P_AHRS_1 SHAM
## wen, 2021_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## wobrock, 2015_HF-RTMS_10-20EEG_P_PANSS_1 HF-RTMS_10-20EEG
## xie, 2023-a_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## xie, 2023-a_LF-RTMS_10-20EEG_P_AHRS_1 LF-RTMS_10-20EEG
## xiu-10hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 HF-RTMS_NEURONAV
## xiu-20hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 HF-RTMS_NEURONAV
## xu, 2023_HD-TDCS_10-20EEG_P_PANSS_1 HD-TDCS_10-20EEG
## yuanjun, 2024_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## yuanjun, 2024_LF-RTMS_10-20EEG_P_AHRS_1 LF-RTMS_10-20EEG
## zhang, 2022_TACS_10-20EEG_P_PANSS_1 SHAM
## zhang, 2022_TACS_10-20EEG_P_AHRS_1 SHAM
## zhao-tbs, 2014_ITBS_10-20EEG_P_PANSS_1 ITBS_10-20EEG
## zhao-20hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 HF-RTMS_10-20EEG
## zhao-10hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 HF-RTMS_10-20EEG
## zhou, 2024_HF-RTMS_10-20EEG_P_PANSS_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_P_PANSS_1 HF-RTMS_10-20EEG
## treat2 TE
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANSS_1 SHAM 1.1200
## bais, 2014 - l_LF-RTMS_10-20EEG_P_AHRS_1 SHAM -0.9400
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANAS_1 SHAM -2.3800
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANSS_1 SHAM 0.4600
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_AHRS_1 SHAM -0.7900
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANAS_1 SHAM -3.8000
## barr, 2012_HF-RTMS_NEURONAV_P_PANSS_1 SHAM 2.2700
## basavaraju, 2021_ITBS_NEURONAV_P_SAPS_1 SHAM -0.1667
## blumberger, 2012_LF-RTMS_NEURONAV_P_PSYRATS_1 SHAM 1.6200
## blumberger, 2012_LF-RTMS_NEURONAV_P_PANSS_1 SHAM 0.5200
## blumberger, 2012_LF-RTMS_NEURONAV_P_AHRS_1 SHAM 2.3300
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PSYRATS_1 SHAM 1.0100
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PANSS_1 SHAM 0.5500
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_AHRS_1 SHAM 0.8600
## bose, 2018_TDCS_10-20EEG_P_SAPS_1 TDCS_10-20EEG -0.4500
## bose, 2018_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG -7.5900
## brunelin, 2012_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG -6.0000
## brunelin, 2006_LF-RTMS_10-20EEG_P_AHRS_1 SHAM 10.4000
## brunelin, 2006_LF-RTMS_10-20EEG_P_SAPS_1 SHAM 9.7000
## chauhan, 2021_ITBS_10-20EEG_P_PANSS_1 SHAM -0.0000
## de jesus, 2011_LF-RTMS_10-20EEG_P_BPRS_1 SHAM -1.4600
## de jesus, 2011_LF-RTMS_10-20EEG_P_AHRS_1 SHAM 3.5600
## dharani, 2021_HD-TDCS_10-10EEG_P_PANSS_1 SHAM 0.5700
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_P_PANSS_1 SHAM -0.1000
## dolfus, 2018_HF-RTMS_NEURONAV_P_AHRS_1 SHAM -0.5600
## du, 2024_HF-RTMS_NEURONAV_P_BPRS_1 SHAM -0.4100
## du, 2022_HF-RTMS_10-20EEG_P_PANSS_1 SHAM 0.7000
## fitzerald, 2008_LF-RTMS_CM_P_PANSS_1 SHAM -2.3000
## fitzerald-l, 2014_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG -1.2000
## fitzerald-bi, 2014_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG -1.7000
## frohlich, 2016_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG 2.1600
## frohlich, 2016_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG 2.7000
## gao, 2024_ITBS_10-20EEG_P_PANSS_1 SHAM -0.0800
## garg, 2016_DTMS_CM_P_PANSS_1 SHAM 0.5000
## gomes, 2018_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG -0.7500
## guan, 2020_HF-RTMS_NEURONAV_P_PANSS_1 SHAM -0.8000
## guleken, 2020_HF-RTMS_CM_P_PANSS_1 SHAM 19.9900
## holi, 2004_HF-RTMS_10-20EEG_P_PANSS_1 SHAM -4.3000
## hu, 2024_LF-RTMS_10-20EEG_P_PANSS_1 SHAM 2.5000
## hu, 2023_LF-RTMS_10-10EEG_P_PANSS_1 SHAM 2.0400
## huang, 2016_HF-RTMS_CM_P_PANSS_1 SHAM -0.5200
## jeon, 2018_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG -1.6200
## jin, 2023_ITBS_NA_P_PANSS_1 SHAM 0.3400
## kang, 2024_CTBS_CM_P_PANSS_1 SHAM 2.9000
## kang, 2024_CTBS_CM_P_AHRS_1 SHAM 0.0700
## kantrowitz, 2019_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG -0.8000
## kimura, 2016_HF-RTMS_10-20EEG_P_AHRS_1 SHAM 2.1000
## klein, 1999_LF-RTMS_CM_P_PANSS_1 SHAM -2.8000
## koops, 2018_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG 0.0000
## koops, 2018_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG -0.6500
## koops, 2016_CTBS_10-20EEG_P_PANSS_1 SHAM -0.0000
## koops, 2016_CTBS_10-20EEG_P_AHRS_1 SHAM -0.0000
## koops, 2016_CTBS_10-20EEG_P_PSYRATS_1 SHAM -19.0000
## liu, 2024_HF-RTMS_NA_P_PANSS_1 SHAM -0.2100
## lyu, 2024_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG -0.1300
## mao, 2023_HF-RTMS_CM_P_AHRS_1 SHAM 0.2600
## marquardt, 2022_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG 3.8700
## marquardt, 2022_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG 0.2600
## mcintosh, 2004_LF-RTMS_10-20EEG_P_PANSS_1 SHAM 2.1300
## mellin-tacs, 2018_TACS_10-20EEG_P_AHRS_1 TACS_10-20EEG -1.4700
## mellin-tacs, 2018_TACS_10-20EEG_P_PANSS-P_1 TACS_10-20EEG 0.8100
## mellin-tdcs, 2018_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG 1.1400
## mellin-tdcs, 2018_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG -0.7400
## moeller, 2022_DTMS_CM_P_PANSS_1 SHAM 2.2000
## mondino, 2015_TDCS_10-20EG_P_PANSS_1 TDCS_10-20EG -0.2000
## mondino, 2015_TDCS_10-20EG_P_AHRS_1 TDCS_10-20EG -5.2000
## novak, 2006_HF-RTMS_CM_P_PANSS_1 SHAM -0.5000
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_SAPS_1 SHAM -4.7300
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_AHRS_1 SHAM -2.9900
## palm, 2016_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG 0.1000
## prikryl, 2007_HF-RTMS_CM_P_PANSS_1 SHAM -0.1900
## prikryl, 2007_HF-RTMS_CM_P_SAPS_1 SHAM 0.1800
## prikryl, 2012_HF-RTMS_CM_P_PANSS_1 SHAM 0.5500
## prikryl, 2014_HF-RTMS_CM_P_PANSS_1 SHAM 0.4100
## prikryl, 2013_HF-RTMS_CM_P_SAPS_1 SHAM -0.5700
## quan, 2015_HF-RTMS_CM_P_PANSS_1 SHAM 0.3100
## rosa, 2007_LF-RTMS_10-20EEG_P_PANSS_1 SHAM -0.4300
## rosenberg, 2012_LF-RTMS_CM_P_AHRS_1 SHAM -0.6000
## saba, 2006_LF-RTMS_CM_P_PANSS_1 SHAM -0.3100
## singh, 2020_HF-RTMS_CM_P_PANSS_1 SHAM -0.3900
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_AHRS_1 SHAM 0.7000
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_PANSS_1 SHAM -1.3000
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_AHRS_1 SHAM 0.0000
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_PANSS_1 SHAM -1.9000
## smith, 2015_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG 0.6600
## smith, 2020_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG -0.2500
## su, 2023b_HF-RTMS_NEURONAV_P_PANSS_1 SHAM 0.3000
## su, 2022_HF-RTMS_NEURONAV_P_PANSS_1 SHAM 0.4000
## tikka, 2017_CTBS_NEURONAV_P_PANSS_1 SHAM 0.8500
## tyagi, 2022_CTBS_10-20EEG_P_PANSS_1 SHAM 1.1800
## tyagi, 2022_CTBS_10-20EEG_P_AVHRS_1 SHAM -1.7200
## tyagi, 2022_CTBS_10-20EEG_P_PSYRAT-AH_1 SHAM -1.4700
## valiengo, 2020_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG -0.0400
## valiengo, 2020_TDCS_10-20EEG_P_AVHRS_1 TDCS_10-20EEG 0.8400
## vergallito, 2024_ITBS_10-20EEG_P_PANSS_1 SHAM 0.8600
## walther-lft, 2024_UNKNOWN_STANDARD_P_PANSS_1 UNKNOWN_STANDARD -1.5000
## walther-itbs, 2024_ITBS_CM_P_PANSS_1 SHAM 1.7000
## wang, 2020_ITBS_NEURONAV_P_PANSS_1 SHAM 1.3200
## wang, 2020_ITBS_NEURONAV_P_SAPS_1 SHAM 5.7200
## wang, 2022_ITBS_NEURONAV_P_PANSS_1 SHAM 3.5520
## wang, 2022_ITBS_NEURONAV_P_SAPS_1 SHAM 8.4730
## weickert, 2019_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG -0.3000
## weickert, 2019_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG 5.0000
## wen, 2021_HF-RTMS_CM_P_PANSS_1 SHAM 0.6000
## wobrock, 2015_HF-RTMS_10-20EEG_P_PANSS_1 SHAM 1.3000
## xie, 2023-a_LF-RTMS_10-20EEG_P_PANSS_1 SHAM 6.6600
## xie, 2023-a_LF-RTMS_10-20EEG_P_AHRS_1 SHAM 13.5000
## xiu-10hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 SHAM 0.6000
## xiu-20hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 SHAM 1.7000
## xu, 2023_HD-TDCS_10-20EEG_P_PANSS_1 SHAM 1.2800
## yuanjun, 2024_LF-RTMS_10-20EEG_P_PANSS_1 SHAM 6.2200
## yuanjun, 2024_LF-RTMS_10-20EEG_P_AHRS_1 SHAM 14.7000
## zhang, 2022_TACS_10-20EEG_P_PANSS_1 TACS_10-20EEG -0.2800
## zhang, 2022_TACS_10-20EEG_P_AHRS_1 TACS_10-20EEG 0.6000
## zhao-tbs, 2014_ITBS_10-20EEG_P_PANSS_1 SHAM -3.8000
## zhao-20hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 SHAM 0.7000
## zhao-10hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 SHAM -0.2000
## zhou, 2024_HF-RTMS_10-20EEG_P_PANSS_1 SHAM 0.5000
## zhuo, 2019_HF-RTMS_10-20EEG_P_PANSS_1 SHAM -0.0400
## seTE
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANSS_1 1.3255
## bais, 2014 - l_LF-RTMS_10-20EEG_P_AHRS_1 2.0973
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANAS_1 2.5683
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANSS_1 1.1614
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_AHRS_1 2.2660
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANAS_1 2.3828
## barr, 2012_HF-RTMS_NEURONAV_P_PANSS_1 1.6327
## basavaraju, 2021_ITBS_NEURONAV_P_SAPS_1 1.4690
## blumberger, 2012_LF-RTMS_NEURONAV_P_PSYRATS_1 1.8025
## blumberger, 2012_LF-RTMS_NEURONAV_P_PANSS_1 1.1321
## blumberger, 2012_LF-RTMS_NEURONAV_P_AHRS_1 2.1992
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PSYRATS_1 1.7663
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PANSS_1 1.1092
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_AHRS_1 2.2547
## bose, 2018_TDCS_10-20EEG_P_SAPS_1 4.0637
## bose, 2018_TDCS_10-20EEG_P_AHRS_1 1.2546
## brunelin, 2012_TDCS_10-20EEG_P_AHRS_1 1.8797
## brunelin, 2006_LF-RTMS_10-20EEG_P_AHRS_1 2.8113
## brunelin, 2006_LF-RTMS_10-20EEG_P_SAPS_1 7.6631
## chauhan, 2021_ITBS_10-20EEG_P_PANSS_1 0.6438
## de jesus, 2011_LF-RTMS_10-20EEG_P_BPRS_1 1.3133
## de jesus, 2011_LF-RTMS_10-20EEG_P_AHRS_1 2.4688
## dharani, 2021_HD-TDCS_10-10EEG_P_PANSS_1 0.7670
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_P_PANSS_1 1.3667
## dolfus, 2018_HF-RTMS_NEURONAV_P_AHRS_1 1.3188
## du, 2024_HF-RTMS_NEURONAV_P_BPRS_1 1.7912
## du, 2022_HF-RTMS_10-20EEG_P_PANSS_1 0.9283
## fitzerald, 2008_LF-RTMS_CM_P_PANSS_1 1.8085
## fitzerald-l, 2014_TDCS_10-20EEG_P_PANSS_1 1.2507
## fitzerald-bi, 2014_TDCS_10-20EEG_P_PANSS_1 1.4911
## frohlich, 2016_TDCS_10-20EEG_P_AHRS_1 2.7155
## frohlich, 2016_TDCS_10-20EEG_P_PANSS_1 1.6340
## gao, 2024_ITBS_10-20EEG_P_PANSS_1 0.2932
## garg, 2016_DTMS_CM_P_PANSS_1 1.4551
## gomes, 2018_TDCS_10-20EEG_P_PANSS_1 1.1160
## guan, 2020_HF-RTMS_NEURONAV_P_PANSS_1 0.9430
## guleken, 2020_HF-RTMS_CM_P_PANSS_1 2.9696
## holi, 2004_HF-RTMS_10-20EEG_P_PANSS_1 2.8458
## hu, 2024_LF-RTMS_10-20EEG_P_PANSS_1 0.7220
## hu, 2023_LF-RTMS_10-10EEG_P_PANSS_1 0.7056
## huang, 2016_HF-RTMS_CM_P_PANSS_1 0.5152
## jeon, 2018_TDCS_10-20EEG_P_PANSS_1 1.2663
## jin, 2023_ITBS_NA_P_PANSS_1 0.5304
## kang, 2024_CTBS_CM_P_PANSS_1 1.3518
## kang, 2024_CTBS_CM_P_AHRS_1 3.1187
## kantrowitz, 2019_TDCS_10-20EEG_P_AHRS_1 1.6017
## kimura, 2016_HF-RTMS_10-20EEG_P_AHRS_1 2.6065
## klein, 1999_LF-RTMS_CM_P_PANSS_1 1.7339
## koops, 2018_TDCS_10-20EEG_P_AHRS_1 1.4537
## koops, 2018_TDCS_10-20EEG_P_PANSS_1 1.1593
## koops, 2016_CTBS_10-20EEG_P_PANSS_1 1.1347
## koops, 2016_CTBS_10-20EEG_P_AHRS_1 1.0897
## koops, 2016_CTBS_10-20EEG_P_PSYRATS_1 1.0695
## liu, 2024_HF-RTMS_NA_P_PANSS_1 1.5038
## lyu, 2024_TDCS_10-20EEG_P_PANSS_1 1.0278
## mao, 2023_HF-RTMS_CM_P_AHRS_1 0.8545
## marquardt, 2022_TDCS_10-20EEG_P_PANSS_1 2.6330
## marquardt, 2022_TDCS_10-20EEG_P_AHRS_1 2.4844
## mcintosh, 2004_LF-RTMS_10-20EEG_P_PANSS_1 2.0684
## mellin-tacs, 2018_TACS_10-20EEG_P_AHRS_1 2.3049
## mellin-tacs, 2018_TACS_10-20EEG_P_PANSS-P_1 1.7592
## mellin-tdcs, 2018_TDCS_10-20EEG_P_AHRS_1 2.9478
## mellin-tdcs, 2018_TDCS_10-20EEG_P_PANSS_1 1.5366
## moeller, 2022_DTMS_CM_P_PANSS_1 1.7880
## mondino, 2015_TDCS_10-20EG_P_PANSS_1 1.3530
## mondino, 2015_TDCS_10-20EG_P_AHRS_1 2.6696
## novak, 2006_HF-RTMS_CM_P_PANSS_1 1.7379
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_SAPS_1 7.6626
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_AHRS_1 3.0737
## palm, 2016_TDCS_10-20EEG_P_PANSS_1 1.3441
## prikryl, 2007_HF-RTMS_CM_P_PANSS_1 0.5493
## prikryl, 2007_HF-RTMS_CM_P_SAPS_1 0.9915
## prikryl, 2012_HF-RTMS_CM_P_PANSS_1 0.5810
## prikryl, 2014_HF-RTMS_CM_P_PANSS_1 0.5266
## prikryl, 2013_HF-RTMS_CM_P_SAPS_1 0.6823
## quan, 2015_HF-RTMS_CM_P_PANSS_1 0.7982
## rosa, 2007_LF-RTMS_10-20EEG_P_PANSS_1 2.0184
## rosenberg, 2012_LF-RTMS_CM_P_AHRS_1 2.2944
## saba, 2006_LF-RTMS_CM_P_PANSS_1 1.8520
## singh, 2020_HF-RTMS_CM_P_PANSS_1 0.8812
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_AHRS_1 1.7910
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_PANSS_1 1.1814
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_AHRS_1 1.7037
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_PANSS_1 1.0081
## smith, 2015_TDCS_10-20EEG_P_PANSS_1 1.7653
## smith, 2020_TDCS_10-20EEG_P_PANSS_1 1.0846
## su, 2023b_HF-RTMS_NEURONAV_P_PANSS_1 1.9428
## su, 2022_HF-RTMS_NEURONAV_P_PANSS_1 1.8284
## tikka, 2017_CTBS_NEURONAV_P_PANSS_1 1.4881
## tyagi, 2022_CTBS_10-20EEG_P_PANSS_1 0.8044
## tyagi, 2022_CTBS_10-20EEG_P_AVHRS_1 1.5987
## tyagi, 2022_CTBS_10-20EEG_P_PSYRAT-AH_1 1.0437
## valiengo, 2020_TDCS_10-20EEG_P_PANSS_1 0.7269
## valiengo, 2020_TDCS_10-20EEG_P_AVHRS_1 1.9181
## vergallito, 2024_ITBS_10-20EEG_P_PANSS_1 2.0579
## walther-lft, 2024_UNKNOWN_STANDARD_P_PANSS_1 0.2928
## walther-itbs, 2024_ITBS_CM_P_PANSS_1 0.2745
## wang, 2020_ITBS_NEURONAV_P_PANSS_1 1.2092
## wang, 2020_ITBS_NEURONAV_P_SAPS_1 2.4192
## wang, 2022_ITBS_NEURONAV_P_PANSS_1 1.3926
## wang, 2022_ITBS_NEURONAV_P_SAPS_1 3.6999
## weickert, 2019_TDCS_10-20EEG_P_PANSS_1 2.3094
## weickert, 2019_TDCS_10-20EEG_P_AHRS_1 5.3424
## wen, 2021_HF-RTMS_CM_P_PANSS_1 0.8888
## wobrock, 2015_HF-RTMS_10-20EEG_P_PANSS_1 0.5978
## xie, 2023-a_LF-RTMS_10-20EEG_P_PANSS_1 0.8203
## xie, 2023-a_LF-RTMS_10-20EEG_P_AHRS_1 1.2347
## xiu-10hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 0.9447
## xiu-20hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 0.7855
## xu, 2023_HD-TDCS_10-20EEG_P_PANSS_1 1.4000
## yuanjun, 2024_LF-RTMS_10-20EEG_P_PANSS_1 0.8576
## yuanjun, 2024_LF-RTMS_10-20EEG_P_AHRS_1 1.2685
## zhang, 2022_TACS_10-20EEG_P_PANSS_1 1.3451
## zhang, 2022_TACS_10-20EEG_P_AHRS_1 2.1433
## zhao-tbs, 2014_ITBS_10-20EEG_P_PANSS_1 0.7147
## zhao-20hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 0.9163
## zhao-10hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 0.4153
## zhou, 2024_HF-RTMS_10-20EEG_P_PANSS_1 0.4355
## zhuo, 2019_HF-RTMS_10-20EEG_P_PANSS_1 0.5742
##
## Number of treatment arms (by study):
## narms
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANSS_1 2
## bais, 2014 - l_LF-RTMS_10-20EEG_P_AHRS_1 2
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANAS_1 2
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANSS_1 2
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_AHRS_1 2
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANAS_1 2
## barr, 2012_HF-RTMS_NEURONAV_P_PANSS_1 2
## basavaraju, 2021_ITBS_NEURONAV_P_SAPS_1 2
## blumberger, 2012_LF-RTMS_NEURONAV_P_PSYRATS_1 2
## blumberger, 2012_LF-RTMS_NEURONAV_P_PANSS_1 2
## blumberger, 2012_LF-RTMS_NEURONAV_P_AHRS_1 2
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PSYRATS_1 2
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PANSS_1 2
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_AHRS_1 2
## bose, 2018_TDCS_10-20EEG_P_SAPS_1 2
## bose, 2018_TDCS_10-20EEG_P_AHRS_1 2
## brunelin, 2012_TDCS_10-20EEG_P_AHRS_1 2
## brunelin, 2006_LF-RTMS_10-20EEG_P_AHRS_1 2
## brunelin, 2006_LF-RTMS_10-20EEG_P_SAPS_1 2
## chauhan, 2021_ITBS_10-20EEG_P_PANSS_1 2
## de jesus, 2011_LF-RTMS_10-20EEG_P_BPRS_1 2
## de jesus, 2011_LF-RTMS_10-20EEG_P_AHRS_1 2
## dharani, 2021_HD-TDCS_10-10EEG_P_PANSS_1 2
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_P_PANSS_1 2
## dolfus, 2018_HF-RTMS_NEURONAV_P_AHRS_1 2
## du, 2024_HF-RTMS_NEURONAV_P_BPRS_1 2
## du, 2022_HF-RTMS_10-20EEG_P_PANSS_1 2
## fitzerald, 2008_LF-RTMS_CM_P_PANSS_1 2
## fitzerald-l, 2014_TDCS_10-20EEG_P_PANSS_1 2
## fitzerald-bi, 2014_TDCS_10-20EEG_P_PANSS_1 2
## frohlich, 2016_TDCS_10-20EEG_P_AHRS_1 2
## frohlich, 2016_TDCS_10-20EEG_P_PANSS_1 2
## gao, 2024_ITBS_10-20EEG_P_PANSS_1 2
## garg, 2016_DTMS_CM_P_PANSS_1 2
## gomes, 2018_TDCS_10-20EEG_P_PANSS_1 2
## guan, 2020_HF-RTMS_NEURONAV_P_PANSS_1 2
## guleken, 2020_HF-RTMS_CM_P_PANSS_1 2
## holi, 2004_HF-RTMS_10-20EEG_P_PANSS_1 2
## hu, 2024_LF-RTMS_10-20EEG_P_PANSS_1 2
## hu, 2023_LF-RTMS_10-10EEG_P_PANSS_1 2
## huang, 2016_HF-RTMS_CM_P_PANSS_1 2
## jeon, 2018_TDCS_10-20EEG_P_PANSS_1 2
## jin, 2023_ITBS_NA_P_PANSS_1 2
## kang, 2024_CTBS_CM_P_PANSS_1 2
## kang, 2024_CTBS_CM_P_AHRS_1 2
## kantrowitz, 2019_TDCS_10-20EEG_P_AHRS_1 2
## kimura, 2016_HF-RTMS_10-20EEG_P_AHRS_1 2
## klein, 1999_LF-RTMS_CM_P_PANSS_1 2
## koops, 2018_TDCS_10-20EEG_P_AHRS_1 2
## koops, 2018_TDCS_10-20EEG_P_PANSS_1 2
## koops, 2016_CTBS_10-20EEG_P_PANSS_1 2
## koops, 2016_CTBS_10-20EEG_P_AHRS_1 2
## koops, 2016_CTBS_10-20EEG_P_PSYRATS_1 2
## liu, 2024_HF-RTMS_NA_P_PANSS_1 2
## lyu, 2024_TDCS_10-20EEG_P_PANSS_1 2
## mao, 2023_HF-RTMS_CM_P_AHRS_1 2
## marquardt, 2022_TDCS_10-20EEG_P_PANSS_1 2
## marquardt, 2022_TDCS_10-20EEG_P_AHRS_1 2
## mcintosh, 2004_LF-RTMS_10-20EEG_P_PANSS_1 2
## mellin-tacs, 2018_TACS_10-20EEG_P_AHRS_1 2
## mellin-tacs, 2018_TACS_10-20EEG_P_PANSS-P_1 2
## mellin-tdcs, 2018_TDCS_10-20EEG_P_AHRS_1 2
## mellin-tdcs, 2018_TDCS_10-20EEG_P_PANSS_1 2
## moeller, 2022_DTMS_CM_P_PANSS_1 2
## mondino, 2015_TDCS_10-20EG_P_PANSS_1 2
## mondino, 2015_TDCS_10-20EG_P_AHRS_1 2
## novak, 2006_HF-RTMS_CM_P_PANSS_1 2
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_SAPS_1 2
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_AHRS_1 2
## palm, 2016_TDCS_10-20EEG_P_PANSS_1 2
## prikryl, 2007_HF-RTMS_CM_P_PANSS_1 2
## prikryl, 2007_HF-RTMS_CM_P_SAPS_1 2
## prikryl, 2012_HF-RTMS_CM_P_PANSS_1 2
## prikryl, 2014_HF-RTMS_CM_P_PANSS_1 2
## prikryl, 2013_HF-RTMS_CM_P_SAPS_1 2
## quan, 2015_HF-RTMS_CM_P_PANSS_1 2
## rosa, 2007_LF-RTMS_10-20EEG_P_PANSS_1 2
## rosenberg, 2012_LF-RTMS_CM_P_AHRS_1 2
## saba, 2006_LF-RTMS_CM_P_PANSS_1 2
## singh, 2020_HF-RTMS_CM_P_PANSS_1 2
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_AHRS_1 2
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_PANSS_1 2
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_AHRS_1 2
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_PANSS_1 2
## smith, 2015_TDCS_10-20EEG_P_PANSS_1 2
## smith, 2020_TDCS_10-20EEG_P_PANSS_1 2
## su, 2023b_HF-RTMS_NEURONAV_P_PANSS_1 2
## su, 2022_HF-RTMS_NEURONAV_P_PANSS_1 2
## tikka, 2017_CTBS_NEURONAV_P_PANSS_1 2
## tyagi, 2022_CTBS_10-20EEG_P_PANSS_1 2
## tyagi, 2022_CTBS_10-20EEG_P_AVHRS_1 2
## tyagi, 2022_CTBS_10-20EEG_P_PSYRAT-AH_1 2
## valiengo, 2020_TDCS_10-20EEG_P_PANSS_1 2
## valiengo, 2020_TDCS_10-20EEG_P_AVHRS_1 2
## vergallito, 2024_ITBS_10-20EEG_P_PANSS_1 2
## walther-lft, 2024_UNKNOWN_STANDARD_P_PANSS_1 2
## walther-itbs, 2024_ITBS_CM_P_PANSS_1 2
## wang, 2020_ITBS_NEURONAV_P_PANSS_1 2
## wang, 2020_ITBS_NEURONAV_P_SAPS_1 2
## wang, 2022_ITBS_NEURONAV_P_PANSS_1 2
## wang, 2022_ITBS_NEURONAV_P_SAPS_1 2
## weickert, 2019_TDCS_10-20EEG_P_PANSS_1 2
## weickert, 2019_TDCS_10-20EEG_P_AHRS_1 2
## wen, 2021_HF-RTMS_CM_P_PANSS_1 2
## wobrock, 2015_HF-RTMS_10-20EEG_P_PANSS_1 2
## xie, 2023-a_LF-RTMS_10-20EEG_P_PANSS_1 2
## xie, 2023-a_LF-RTMS_10-20EEG_P_AHRS_1 2
## xiu-10hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 2
## xiu-20hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 2
## xu, 2023_HD-TDCS_10-20EEG_P_PANSS_1 2
## yuanjun, 2024_LF-RTMS_10-20EEG_P_PANSS_1 2
## yuanjun, 2024_LF-RTMS_10-20EEG_P_AHRS_1 2
## zhang, 2022_TACS_10-20EEG_P_PANSS_1 2
## zhang, 2022_TACS_10-20EEG_P_AHRS_1 2
## zhao-tbs, 2014_ITBS_10-20EEG_P_PANSS_1 2
## zhao-20hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 2
## zhao-10hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 2
## zhou, 2024_HF-RTMS_10-20EEG_P_PANSS_1 2
## zhuo, 2019_HF-RTMS_10-20EEG_P_PANSS_1 2
##
## Results (random effects model):
##
## treat1
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## bais, 2014 - l_LF-RTMS_10-20EEG_P_AHRS_1 LF-RTMS_10-20EEG
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANAS_1 LF-RTMS_10-20EEG
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_AHRS_1 LF-RTMS_10-20EEG
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANAS_1 LF-RTMS_10-20EEG
## barr, 2012_HF-RTMS_NEURONAV_P_PANSS_1 HF-RTMS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_P_SAPS_1 ITBS_NEURONAV
## blumberger, 2012_LF-RTMS_NEURONAV_P_PSYRATS_1 LF-RTMS_NEURONAV
## blumberger, 2012_LF-RTMS_NEURONAV_P_PANSS_1 LF-RTMS_NEURONAV
## blumberger, 2012_LF-RTMS_NEURONAV_P_AHRS_1 LF-RTMS_NEURONAV
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PSYRATS_1 PRM-RTMS_NEURONAV
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PANSS_1 PRM-RTMS_NEURONAV
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_AHRS_1 PRM-RTMS_NEURONAV
## bose, 2018_TDCS_10-20EEG_P_SAPS_1 SHAM
## bose, 2018_TDCS_10-20EEG_P_AHRS_1 SHAM
## brunelin, 2012_TDCS_10-20EEG_P_AHRS_1 SHAM
## brunelin, 2006_LF-RTMS_10-20EEG_P_AHRS_1 LF-RTMS_10-20EEG
## brunelin, 2006_LF-RTMS_10-20EEG_P_SAPS_1 LF-RTMS_10-20EEG
## chauhan, 2021_ITBS_10-20EEG_P_PANSS_1 ITBS_10-20EEG
## de jesus, 2011_LF-RTMS_10-20EEG_P_BPRS_1 LF-RTMS_10-20EEG
## de jesus, 2011_LF-RTMS_10-20EEG_P_AHRS_1 LF-RTMS_10-20EEG
## dharani, 2021_HD-TDCS_10-10EEG_P_PANSS_1 HD-TDCS_10-10EEG
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## dolfus, 2018_HF-RTMS_NEURONAV_P_AHRS_1 HF-RTMS_NEURONAV
## du, 2024_HF-RTMS_NEURONAV_P_BPRS_1 HF-RTMS_NEURONAV
## du, 2022_HF-RTMS_10-20EEG_P_PANSS_1 HF-RTMS_10-20EEG
## fitzerald, 2008_LF-RTMS_CM_P_PANSS_1 LF-RTMS_CM
## fitzerald-l, 2014_TDCS_10-20EEG_P_PANSS_1 SHAM
## fitzerald-bi, 2014_TDCS_10-20EEG_P_PANSS_1 SHAM
## frohlich, 2016_TDCS_10-20EEG_P_AHRS_1 SHAM
## frohlich, 2016_TDCS_10-20EEG_P_PANSS_1 SHAM
## gao, 2024_ITBS_10-20EEG_P_PANSS_1 ITBS_10-20EEG
## garg, 2016_DTMS_CM_P_PANSS_1 DTMS_CM
## gomes, 2018_TDCS_10-20EEG_P_PANSS_1 SHAM
## guan, 2020_HF-RTMS_NEURONAV_P_PANSS_1 HF-RTMS_NEURONAV
## guleken, 2020_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## holi, 2004_HF-RTMS_10-20EEG_P_PANSS_1 HF-RTMS_10-20EEG
## hu, 2024_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## hu, 2023_LF-RTMS_10-10EEG_P_PANSS_1 LF-RTMS_10-10EEG
## huang, 2016_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## jeon, 2018_TDCS_10-20EEG_P_PANSS_1 SHAM
## jin, 2023_ITBS_NA_P_PANSS_1 ITBS_NA
## kang, 2024_CTBS_CM_P_PANSS_1 CTBS_CM
## kang, 2024_CTBS_CM_P_AHRS_1 CTBS_CM
## kantrowitz, 2019_TDCS_10-20EEG_P_AHRS_1 SHAM
## kimura, 2016_HF-RTMS_10-20EEG_P_AHRS_1 HF-RTMS_10-20EEG
## klein, 1999_LF-RTMS_CM_P_PANSS_1 LF-RTMS_CM
## koops, 2018_TDCS_10-20EEG_P_AHRS_1 SHAM
## koops, 2018_TDCS_10-20EEG_P_PANSS_1 SHAM
## koops, 2016_CTBS_10-20EEG_P_PANSS_1 CTBS_10-20EEG
## koops, 2016_CTBS_10-20EEG_P_AHRS_1 CTBS_10-20EEG
## koops, 2016_CTBS_10-20EEG_P_PSYRATS_1 CTBS_10-20EEG
## liu, 2024_HF-RTMS_NA_P_PANSS_1 HF-RTMS_NA
## lyu, 2024_TDCS_10-20EEG_P_PANSS_1 SHAM
## mao, 2023_HF-RTMS_CM_P_AHRS_1 HF-RTMS_CM
## marquardt, 2022_TDCS_10-20EEG_P_PANSS_1 SHAM
## marquardt, 2022_TDCS_10-20EEG_P_AHRS_1 SHAM
## mcintosh, 2004_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## mellin-tacs, 2018_TACS_10-20EEG_P_AHRS_1 SHAM
## mellin-tacs, 2018_TACS_10-20EEG_P_PANSS-P_1 SHAM
## mellin-tdcs, 2018_TDCS_10-20EEG_P_AHRS_1 SHAM
## mellin-tdcs, 2018_TDCS_10-20EEG_P_PANSS_1 SHAM
## moeller, 2022_DTMS_CM_P_PANSS_1 DTMS_CM
## mondino, 2015_TDCS_10-20EG_P_PANSS_1 SHAM
## mondino, 2015_TDCS_10-20EG_P_AHRS_1 SHAM
## novak, 2006_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_SAPS_1 LF-RTMS_NEURONAV
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_AHRS_1 LF-RTMS_NEURONAV
## palm, 2016_TDCS_10-20EEG_P_PANSS_1 SHAM
## prikryl, 2007_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## prikryl, 2007_HF-RTMS_CM_P_SAPS_1 HF-RTMS_CM
## prikryl, 2012_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## prikryl, 2014_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## prikryl, 2013_HF-RTMS_CM_P_SAPS_1 HF-RTMS_CM
## quan, 2015_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## rosa, 2007_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## rosenberg, 2012_LF-RTMS_CM_P_AHRS_1 LF-RTMS_CM
## saba, 2006_LF-RTMS_CM_P_PANSS_1 LF-RTMS_CM
## singh, 2020_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_AHRS_1 LF-RTMS_NEURONAV
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_PANSS_1 LF-RTMS_NEURONAV
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_AHRS_1 LF-RTMS_10-20EEG
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## smith, 2015_TDCS_10-20EEG_P_PANSS_1 SHAM
## smith, 2020_TDCS_10-20EEG_P_PANSS_1 SHAM
## su, 2023b_HF-RTMS_NEURONAV_P_PANSS_1 HF-RTMS_NEURONAV
## su, 2022_HF-RTMS_NEURONAV_P_PANSS_1 HF-RTMS_NEURONAV
## tikka, 2017_CTBS_NEURONAV_P_PANSS_1 CTBS_NEURONAV
## tyagi, 2022_CTBS_10-20EEG_P_PANSS_1 CTBS_10-20EEG
## tyagi, 2022_CTBS_10-20EEG_P_AVHRS_1 CTBS_10-20EEG
## tyagi, 2022_CTBS_10-20EEG_P_PSYRAT-AH_1 CTBS_10-20EEG
## valiengo, 2020_TDCS_10-20EEG_P_PANSS_1 SHAM
## valiengo, 2020_TDCS_10-20EEG_P_AVHRS_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_P_PANSS_1 ITBS_10-20EEG
## walther-lft, 2024_UNKNOWN_STANDARD_P_PANSS_1 SHAM
## walther-itbs, 2024_ITBS_CM_P_PANSS_1 ITBS_CM
## wang, 2020_ITBS_NEURONAV_P_PANSS_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_P_SAPS_1 ITBS_NEURONAV
## wang, 2022_ITBS_NEURONAV_P_PANSS_1 ITBS_NEURONAV
## wang, 2022_ITBS_NEURONAV_P_SAPS_1 ITBS_NEURONAV
## weickert, 2019_TDCS_10-20EEG_P_PANSS_1 SHAM
## weickert, 2019_TDCS_10-20EEG_P_AHRS_1 SHAM
## wen, 2021_HF-RTMS_CM_P_PANSS_1 HF-RTMS_CM
## wobrock, 2015_HF-RTMS_10-20EEG_P_PANSS_1 HF-RTMS_10-20EEG
## xie, 2023-a_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## xie, 2023-a_LF-RTMS_10-20EEG_P_AHRS_1 LF-RTMS_10-20EEG
## xiu-10hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 HF-RTMS_NEURONAV
## xiu-20hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 HF-RTMS_NEURONAV
## xu, 2023_HD-TDCS_10-20EEG_P_PANSS_1 HD-TDCS_10-20EEG
## yuanjun, 2024_LF-RTMS_10-20EEG_P_PANSS_1 LF-RTMS_10-20EEG
## yuanjun, 2024_LF-RTMS_10-20EEG_P_AHRS_1 LF-RTMS_10-20EEG
## zhang, 2022_TACS_10-20EEG_P_PANSS_1 SHAM
## zhang, 2022_TACS_10-20EEG_P_AHRS_1 SHAM
## zhao-tbs, 2014_ITBS_10-20EEG_P_PANSS_1 ITBS_10-20EEG
## zhao-20hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 HF-RTMS_10-20EEG
## zhao-10hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 HF-RTMS_10-20EEG
## zhou, 2024_HF-RTMS_10-20EEG_P_PANSS_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_P_PANSS_1 HF-RTMS_10-20EEG
## treat2 MD
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANSS_1 SHAM 2.8811
## bais, 2014 - l_LF-RTMS_10-20EEG_P_AHRS_1 SHAM 2.8811
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANAS_1 SHAM 2.8811
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANSS_1 SHAM 2.8811
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_AHRS_1 SHAM 2.8811
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANAS_1 SHAM 2.8811
## barr, 2012_HF-RTMS_NEURONAV_P_PANSS_1 SHAM 0.4432
## basavaraju, 2021_ITBS_NEURONAV_P_SAPS_1 SHAM 3.0155
## blumberger, 2012_LF-RTMS_NEURONAV_P_PSYRATS_1 SHAM 0.1225
## blumberger, 2012_LF-RTMS_NEURONAV_P_PANSS_1 SHAM 0.1225
## blumberger, 2012_LF-RTMS_NEURONAV_P_AHRS_1 SHAM 0.1225
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PSYRATS_1 SHAM 0.7860
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PANSS_1 SHAM 0.7860
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_AHRS_1 SHAM 0.7860
## bose, 2018_TDCS_10-20EEG_P_SAPS_1 TDCS_10-20EEG -0.5459
## bose, 2018_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG -0.5459
## brunelin, 2012_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG -0.5459
## brunelin, 2006_LF-RTMS_10-20EEG_P_AHRS_1 SHAM 2.8811
## brunelin, 2006_LF-RTMS_10-20EEG_P_SAPS_1 SHAM 2.8811
## chauhan, 2021_ITBS_10-20EEG_P_PANSS_1 SHAM -0.8783
## de jesus, 2011_LF-RTMS_10-20EEG_P_BPRS_1 SHAM 2.8811
## de jesus, 2011_LF-RTMS_10-20EEG_P_AHRS_1 SHAM 2.8811
## dharani, 2021_HD-TDCS_10-10EEG_P_PANSS_1 SHAM 0.5700
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_P_PANSS_1 SHAM 2.8811
## dolfus, 2018_HF-RTMS_NEURONAV_P_AHRS_1 SHAM 0.4432
## du, 2024_HF-RTMS_NEURONAV_P_BPRS_1 SHAM 0.4432
## du, 2022_HF-RTMS_10-20EEG_P_PANSS_1 SHAM 0.2671
## fitzerald, 2008_LF-RTMS_CM_P_PANSS_1 SHAM -1.5517
## fitzerald-l, 2014_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG -0.5459
## fitzerald-bi, 2014_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG -0.5459
## frohlich, 2016_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG -0.5459
## frohlich, 2016_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG -0.5459
## gao, 2024_ITBS_10-20EEG_P_PANSS_1 SHAM -0.8783
## garg, 2016_DTMS_CM_P_PANSS_1 SHAM 1.3052
## gomes, 2018_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG -0.5459
## guan, 2020_HF-RTMS_NEURONAV_P_PANSS_1 SHAM 0.4432
## guleken, 2020_HF-RTMS_CM_P_PANSS_1 SHAM 0.9002
## holi, 2004_HF-RTMS_10-20EEG_P_PANSS_1 SHAM 0.2671
## hu, 2024_LF-RTMS_10-20EEG_P_PANSS_1 SHAM 2.8811
## hu, 2023_LF-RTMS_10-10EEG_P_PANSS_1 SHAM 2.0400
## huang, 2016_HF-RTMS_CM_P_PANSS_1 SHAM 0.9002
## jeon, 2018_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG -0.5459
## jin, 2023_ITBS_NA_P_PANSS_1 SHAM 0.3400
## kang, 2024_CTBS_CM_P_PANSS_1 SHAM 1.9034
## kang, 2024_CTBS_CM_P_AHRS_1 SHAM 1.9034
## kantrowitz, 2019_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG -0.5459
## kimura, 2016_HF-RTMS_10-20EEG_P_AHRS_1 SHAM 0.2671
## klein, 1999_LF-RTMS_CM_P_PANSS_1 SHAM -1.5517
## koops, 2018_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG -0.5459
## koops, 2018_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG -0.5459
## koops, 2016_CTBS_10-20EEG_P_PANSS_1 SHAM -3.5062
## koops, 2016_CTBS_10-20EEG_P_AHRS_1 SHAM -3.5062
## koops, 2016_CTBS_10-20EEG_P_PSYRATS_1 SHAM -3.5062
## liu, 2024_HF-RTMS_NA_P_PANSS_1 SHAM -0.2100
## lyu, 2024_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG -0.5459
## mao, 2023_HF-RTMS_CM_P_AHRS_1 SHAM 0.9002
## marquardt, 2022_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG -0.5459
## marquardt, 2022_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG -0.5459
## mcintosh, 2004_LF-RTMS_10-20EEG_P_PANSS_1 SHAM 2.8811
## mellin-tacs, 2018_TACS_10-20EEG_P_AHRS_1 TACS_10-20EEG -0.0519
## mellin-tacs, 2018_TACS_10-20EEG_P_PANSS-P_1 TACS_10-20EEG -0.0519
## mellin-tdcs, 2018_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG -0.5459
## mellin-tdcs, 2018_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG -0.5459
## moeller, 2022_DTMS_CM_P_PANSS_1 SHAM 1.3052
## mondino, 2015_TDCS_10-20EG_P_PANSS_1 TDCS_10-20EG -2.1510
## mondino, 2015_TDCS_10-20EG_P_AHRS_1 TDCS_10-20EG -2.1510
## novak, 2006_HF-RTMS_CM_P_PANSS_1 SHAM 0.9002
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_SAPS_1 SHAM 0.1225
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_AHRS_1 SHAM 0.1225
## palm, 2016_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG -0.5459
## prikryl, 2007_HF-RTMS_CM_P_PANSS_1 SHAM 0.9002
## prikryl, 2007_HF-RTMS_CM_P_SAPS_1 SHAM 0.9002
## prikryl, 2012_HF-RTMS_CM_P_PANSS_1 SHAM 0.9002
## prikryl, 2014_HF-RTMS_CM_P_PANSS_1 SHAM 0.9002
## prikryl, 2013_HF-RTMS_CM_P_SAPS_1 SHAM 0.9002
## quan, 2015_HF-RTMS_CM_P_PANSS_1 SHAM 0.9002
## rosa, 2007_LF-RTMS_10-20EEG_P_PANSS_1 SHAM 2.8811
## rosenberg, 2012_LF-RTMS_CM_P_AHRS_1 SHAM -1.5517
## saba, 2006_LF-RTMS_CM_P_PANSS_1 SHAM -1.5517
## singh, 2020_HF-RTMS_CM_P_PANSS_1 SHAM 0.9002
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_AHRS_1 SHAM 0.1225
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_PANSS_1 SHAM 0.1225
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_AHRS_1 SHAM 2.8811
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_PANSS_1 SHAM 2.8811
## smith, 2015_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG -0.5459
## smith, 2020_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG -0.5459
## su, 2023b_HF-RTMS_NEURONAV_P_PANSS_1 SHAM 0.4432
## su, 2022_HF-RTMS_NEURONAV_P_PANSS_1 SHAM 0.4432
## tikka, 2017_CTBS_NEURONAV_P_PANSS_1 SHAM 0.8500
## tyagi, 2022_CTBS_10-20EEG_P_PANSS_1 SHAM -3.5062
## tyagi, 2022_CTBS_10-20EEG_P_AVHRS_1 SHAM -3.5062
## tyagi, 2022_CTBS_10-20EEG_P_PSYRAT-AH_1 SHAM -3.5062
## valiengo, 2020_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG -0.5459
## valiengo, 2020_TDCS_10-20EEG_P_AVHRS_1 TDCS_10-20EEG -0.5459
## vergallito, 2024_ITBS_10-20EEG_P_PANSS_1 SHAM -0.8783
## walther-lft, 2024_UNKNOWN_STANDARD_P_PANSS_1 UNKNOWN_STANDARD -1.5000
## walther-itbs, 2024_ITBS_CM_P_PANSS_1 SHAM 1.7000
## wang, 2020_ITBS_NEURONAV_P_PANSS_1 SHAM 3.0155
## wang, 2020_ITBS_NEURONAV_P_SAPS_1 SHAM 3.0155
## wang, 2022_ITBS_NEURONAV_P_PANSS_1 SHAM 3.0155
## wang, 2022_ITBS_NEURONAV_P_SAPS_1 SHAM 3.0155
## weickert, 2019_TDCS_10-20EEG_P_PANSS_1 TDCS_10-20EEG -0.5459
## weickert, 2019_TDCS_10-20EEG_P_AHRS_1 TDCS_10-20EEG -0.5459
## wen, 2021_HF-RTMS_CM_P_PANSS_1 SHAM 0.9002
## wobrock, 2015_HF-RTMS_10-20EEG_P_PANSS_1 SHAM 0.2671
## xie, 2023-a_LF-RTMS_10-20EEG_P_PANSS_1 SHAM 2.8811
## xie, 2023-a_LF-RTMS_10-20EEG_P_AHRS_1 SHAM 2.8811
## xiu-10hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 SHAM 0.4432
## xiu-20hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 SHAM 0.4432
## xu, 2023_HD-TDCS_10-20EEG_P_PANSS_1 SHAM 1.2800
## yuanjun, 2024_LF-RTMS_10-20EEG_P_PANSS_1 SHAM 2.8811
## yuanjun, 2024_LF-RTMS_10-20EEG_P_AHRS_1 SHAM 2.8811
## zhang, 2022_TACS_10-20EEG_P_PANSS_1 TACS_10-20EEG -0.0519
## zhang, 2022_TACS_10-20EEG_P_AHRS_1 TACS_10-20EEG -0.0519
## zhao-tbs, 2014_ITBS_10-20EEG_P_PANSS_1 SHAM -0.8783
## zhao-20hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 SHAM 0.2671
## zhao-10hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 SHAM 0.2671
## zhou, 2024_HF-RTMS_10-20EEG_P_PANSS_1 SHAM 0.2671
## zhuo, 2019_HF-RTMS_10-20EEG_P_PANSS_1 SHAM 0.2671
## 95%-CI
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANSS_1 [ 1.4435; 4.3186]
## bais, 2014 - l_LF-RTMS_10-20EEG_P_AHRS_1 [ 1.4435; 4.3186]
## bais, 2014 - l_LF-RTMS_10-20EEG_P_PANAS_1 [ 1.4435; 4.3186]
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANSS_1 [ 1.4435; 4.3186]
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_AHRS_1 [ 1.4435; 4.3186]
## bais, 2014 - bi_LF-RTMS_10-20EEG_P_PANAS_1 [ 1.4435; 4.3186]
## barr, 2012_HF-RTMS_NEURONAV_P_PANSS_1 [-1.7011; 2.5876]
## basavaraju, 2021_ITBS_NEURONAV_P_SAPS_1 [ 0.0602; 5.9708]
## blumberger, 2012_LF-RTMS_NEURONAV_P_PSYRATS_1 [-2.4880; 2.7330]
## blumberger, 2012_LF-RTMS_NEURONAV_P_PANSS_1 [-2.4880; 2.7330]
## blumberger, 2012_LF-RTMS_NEURONAV_P_AHRS_1 [-2.4880; 2.7330]
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PSYRATS_1 [-2.8792; 4.4512]
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_PANSS_1 [-2.8792; 4.4512]
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_P_AHRS_1 [-2.8792; 4.4512]
## bose, 2018_TDCS_10-20EEG_P_SAPS_1 [-1.8662; 0.7744]
## bose, 2018_TDCS_10-20EEG_P_AHRS_1 [-1.8662; 0.7744]
## brunelin, 2012_TDCS_10-20EEG_P_AHRS_1 [-1.8662; 0.7744]
## brunelin, 2006_LF-RTMS_10-20EEG_P_AHRS_1 [ 1.4435; 4.3186]
## brunelin, 2006_LF-RTMS_10-20EEG_P_SAPS_1 [ 1.4435; 4.3186]
## chauhan, 2021_ITBS_10-20EEG_P_PANSS_1 [-3.7561; 1.9996]
## de jesus, 2011_LF-RTMS_10-20EEG_P_BPRS_1 [ 1.4435; 4.3186]
## de jesus, 2011_LF-RTMS_10-20EEG_P_AHRS_1 [ 1.4435; 4.3186]
## dharani, 2021_HD-TDCS_10-10EEG_P_PANSS_1 [-5.0312; 6.1712]
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_P_PANSS_1 [ 1.4435; 4.3186]
## dolfus, 2018_HF-RTMS_NEURONAV_P_AHRS_1 [-1.7011; 2.5876]
## du, 2024_HF-RTMS_NEURONAV_P_BPRS_1 [-1.7011; 2.5876]
## du, 2022_HF-RTMS_10-20EEG_P_PANSS_1 [-1.8213; 2.3554]
## fitzerald, 2008_LF-RTMS_CM_P_PANSS_1 [-4.8397; 1.7363]
## fitzerald-l, 2014_TDCS_10-20EEG_P_PANSS_1 [-1.8662; 0.7744]
## fitzerald-bi, 2014_TDCS_10-20EEG_P_PANSS_1 [-1.8662; 0.7744]
## frohlich, 2016_TDCS_10-20EEG_P_AHRS_1 [-1.8662; 0.7744]
## frohlich, 2016_TDCS_10-20EEG_P_PANSS_1 [-1.8662; 0.7744]
## gao, 2024_ITBS_10-20EEG_P_PANSS_1 [-3.7561; 1.9996]
## garg, 2016_DTMS_CM_P_PANSS_1 [-3.1227; 5.7330]
## gomes, 2018_TDCS_10-20EEG_P_PANSS_1 [-1.8662; 0.7744]
## guan, 2020_HF-RTMS_NEURONAV_P_PANSS_1 [-1.7011; 2.5876]
## guleken, 2020_HF-RTMS_CM_P_PANSS_1 [-0.7648; 2.5652]
## holi, 2004_HF-RTMS_10-20EEG_P_PANSS_1 [-1.8213; 2.3554]
## hu, 2024_LF-RTMS_10-20EEG_P_PANSS_1 [ 1.4435; 4.3186]
## hu, 2023_LF-RTMS_10-10EEG_P_PANSS_1 [-3.5301; 7.6101]
## huang, 2016_HF-RTMS_CM_P_PANSS_1 [-0.7648; 2.5652]
## jeon, 2018_TDCS_10-20EEG_P_PANSS_1 [-1.8662; 0.7744]
## jin, 2023_ITBS_NA_P_PANSS_1 [-5.1550; 5.8350]
## kang, 2024_CTBS_CM_P_PANSS_1 [-2.9349; 6.7418]
## kang, 2024_CTBS_CM_P_AHRS_1 [-2.9349; 6.7418]
## kantrowitz, 2019_TDCS_10-20EEG_P_AHRS_1 [-1.8662; 0.7744]
## kimura, 2016_HF-RTMS_10-20EEG_P_AHRS_1 [-1.8213; 2.3554]
## klein, 1999_LF-RTMS_CM_P_PANSS_1 [-4.8397; 1.7363]
## koops, 2018_TDCS_10-20EEG_P_AHRS_1 [-1.8662; 0.7744]
## koops, 2018_TDCS_10-20EEG_P_PANSS_1 [-1.8662; 0.7744]
## koops, 2016_CTBS_10-20EEG_P_PANSS_1 [-5.8881; -1.1244]
## koops, 2016_CTBS_10-20EEG_P_AHRS_1 [-5.8881; -1.1244]
## koops, 2016_CTBS_10-20EEG_P_PSYRATS_1 [-5.8881; -1.1244]
## liu, 2024_HF-RTMS_NA_P_PANSS_1 [-6.3582; 5.9382]
## lyu, 2024_TDCS_10-20EEG_P_PANSS_1 [-1.8662; 0.7744]
## mao, 2023_HF-RTMS_CM_P_AHRS_1 [-0.7648; 2.5652]
## marquardt, 2022_TDCS_10-20EEG_P_PANSS_1 [-1.8662; 0.7744]
## marquardt, 2022_TDCS_10-20EEG_P_AHRS_1 [-1.8662; 0.7744]
## mcintosh, 2004_LF-RTMS_10-20EEG_P_PANSS_1 [ 1.4435; 4.3186]
## mellin-tacs, 2018_TACS_10-20EEG_P_AHRS_1 [-3.3188; 3.2151]
## mellin-tacs, 2018_TACS_10-20EEG_P_PANSS-P_1 [-3.3188; 3.2151]
## mellin-tdcs, 2018_TDCS_10-20EEG_P_AHRS_1 [-1.8662; 0.7744]
## mellin-tdcs, 2018_TDCS_10-20EEG_P_PANSS_1 [-1.8662; 0.7744]
## moeller, 2022_DTMS_CM_P_PANSS_1 [-3.1227; 5.7330]
## mondino, 2015_TDCS_10-20EG_P_PANSS_1 [-6.8459; 2.5440]
## mondino, 2015_TDCS_10-20EG_P_AHRS_1 [-6.8459; 2.5440]
## novak, 2006_HF-RTMS_CM_P_PANSS_1 [-0.7648; 2.5652]
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_SAPS_1 [-2.4880; 2.7330]
## paillere-martinot, 2017_LF-RTMS_NEURONAV_P_AHRS_1 [-2.4880; 2.7330]
## palm, 2016_TDCS_10-20EEG_P_PANSS_1 [-1.8662; 0.7744]
## prikryl, 2007_HF-RTMS_CM_P_PANSS_1 [-0.7648; 2.5652]
## prikryl, 2007_HF-RTMS_CM_P_SAPS_1 [-0.7648; 2.5652]
## prikryl, 2012_HF-RTMS_CM_P_PANSS_1 [-0.7648; 2.5652]
## prikryl, 2014_HF-RTMS_CM_P_PANSS_1 [-0.7648; 2.5652]
## prikryl, 2013_HF-RTMS_CM_P_SAPS_1 [-0.7648; 2.5652]
## quan, 2015_HF-RTMS_CM_P_PANSS_1 [-0.7648; 2.5652]
## rosa, 2007_LF-RTMS_10-20EEG_P_PANSS_1 [ 1.4435; 4.3186]
## rosenberg, 2012_LF-RTMS_CM_P_AHRS_1 [-4.8397; 1.7363]
## saba, 2006_LF-RTMS_CM_P_PANSS_1 [-4.8397; 1.7363]
## singh, 2020_HF-RTMS_CM_P_PANSS_1 [-0.7648; 2.5652]
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_AHRS_1 [-2.4880; 2.7330]
## slotema-neuronav, 2011_LF-RTMS_NEURONAV_P_PANSS_1 [-2.4880; 2.7330]
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_AHRS_1 [ 1.4435; 4.3186]
## slotema-10-20eeg, 2011_LF-RTMS_10-20EEG_P_PANSS_1 [ 1.4435; 4.3186]
## smith, 2015_TDCS_10-20EEG_P_PANSS_1 [-1.8662; 0.7744]
## smith, 2020_TDCS_10-20EEG_P_PANSS_1 [-1.8662; 0.7744]
## su, 2023b_HF-RTMS_NEURONAV_P_PANSS_1 [-1.7011; 2.5876]
## su, 2022_HF-RTMS_NEURONAV_P_PANSS_1 [-1.7011; 2.5876]
## tikka, 2017_CTBS_NEURONAV_P_PANSS_1 [-5.2836; 6.9836]
## tyagi, 2022_CTBS_10-20EEG_P_PANSS_1 [-5.8881; -1.1244]
## tyagi, 2022_CTBS_10-20EEG_P_AVHRS_1 [-5.8881; -1.1244]
## tyagi, 2022_CTBS_10-20EEG_P_PSYRAT-AH_1 [-5.8881; -1.1244]
## valiengo, 2020_TDCS_10-20EEG_P_PANSS_1 [-1.8662; 0.7744]
## valiengo, 2020_TDCS_10-20EEG_P_AVHRS_1 [-1.8662; 0.7744]
## vergallito, 2024_ITBS_10-20EEG_P_PANSS_1 [-3.7561; 1.9996]
## walther-lft, 2024_UNKNOWN_STANDARD_P_PANSS_1 [-6.9262; 3.9262]
## walther-itbs, 2024_ITBS_CM_P_PANSS_1 [-3.7225; 7.1225]
## wang, 2020_ITBS_NEURONAV_P_PANSS_1 [ 0.0602; 5.9708]
## wang, 2020_ITBS_NEURONAV_P_SAPS_1 [ 0.0602; 5.9708]
## wang, 2022_ITBS_NEURONAV_P_PANSS_1 [ 0.0602; 5.9708]
## wang, 2022_ITBS_NEURONAV_P_SAPS_1 [ 0.0602; 5.9708]
## weickert, 2019_TDCS_10-20EEG_P_PANSS_1 [-1.8662; 0.7744]
## weickert, 2019_TDCS_10-20EEG_P_AHRS_1 [-1.8662; 0.7744]
## wen, 2021_HF-RTMS_CM_P_PANSS_1 [-0.7648; 2.5652]
## wobrock, 2015_HF-RTMS_10-20EEG_P_PANSS_1 [-1.8213; 2.3554]
## xie, 2023-a_LF-RTMS_10-20EEG_P_PANSS_1 [ 1.4435; 4.3186]
## xie, 2023-a_LF-RTMS_10-20EEG_P_AHRS_1 [ 1.4435; 4.3186]
## xiu-10hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 [-1.7011; 2.5876]
## xiu-20hz, 2020_HF-RTMS_NEURONAV_P_PANSS_1 [-1.7011; 2.5876]
## xu, 2023_HD-TDCS_10-20EEG_P_PANSS_1 [-4.7734; 7.3334]
## yuanjun, 2024_LF-RTMS_10-20EEG_P_PANSS_1 [ 1.4435; 4.3186]
## yuanjun, 2024_LF-RTMS_10-20EEG_P_AHRS_1 [ 1.4435; 4.3186]
## zhang, 2022_TACS_10-20EEG_P_PANSS_1 [-3.3188; 3.2151]
## zhang, 2022_TACS_10-20EEG_P_AHRS_1 [-3.3188; 3.2151]
## zhao-tbs, 2014_ITBS_10-20EEG_P_PANSS_1 [-3.7561; 1.9996]
## zhao-20hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 [-1.8213; 2.3554]
## zhao-10hz, 2014_HF-RTMS_10-20EEG_P_PANSS_1 [-1.8213; 2.3554]
## zhou, 2024_HF-RTMS_10-20EEG_P_PANSS_1 [-1.8213; 2.3554]
## zhuo, 2019_HF-RTMS_10-20EEG_P_PANSS_1 [-1.8213; 2.3554]
##
## Number of studies: k = 119
## Number of pairwise comparisons: m = 119
## Number of treatments: n = 24
## Number of designs: d = 23
##
## Random effects model
##
## Treatment estimate (sm = 'MD', comparison: other treatments vs 'SHAM'):
## MD 95%-CI z p-value
## CTBS_10-20EEG -3.5062 [-5.8881; -1.1244] -2.89 0.0039
## CTBS_CM 1.9034 [-2.9349; 6.7418] 0.77 0.4407
## CTBS_NEURONAV 0.8500 [-5.2836; 6.9836] 0.27 0.7859
## DTMS_CM 1.3052 [-3.1227; 5.7330] 0.58 0.5634
## HD-TDCS_10-10EEG 0.5700 [-5.0312; 6.1712] 0.20 0.8419
## HD-TDCS_10-20EEG 1.2800 [-4.7734; 7.3334] 0.41 0.6786
## HF-RTMS_10-20EEG 0.2671 [-1.8213; 2.3554] 0.25 0.8021
## HF-RTMS_CM 0.9002 [-0.7648; 2.5652] 1.06 0.2893
## HF-RTMS_NA -0.2100 [-6.3582; 5.9382] -0.07 0.9466
## HF-RTMS_NEURONAV 0.4432 [-1.7011; 2.5876] 0.41 0.6854
## ITBS_10-20EEG -0.8783 [-3.7561; 1.9996] -0.60 0.5497
## ITBS_CM 1.7000 [-3.7225; 7.1225] 0.61 0.5389
## ITBS_NA 0.3400 [-5.1550; 5.8350] 0.12 0.9035
## ITBS_NEURONAV 3.0155 [ 0.0602; 5.9708] 2.00 0.0455
## LF-RTMS_10-10EEG 2.0400 [-3.5301; 7.6101] 0.72 0.4729
## LF-RTMS_10-20EEG 2.8811 [ 1.4435; 4.3186] 3.93 < 0.0001
## LF-RTMS_CM -1.5517 [-4.8397; 1.7363] -0.92 0.3550
## LF-RTMS_NEURONAV 0.1225 [-2.4880; 2.7330] 0.09 0.9267
## PRM-RTMS_NEURONAV 0.7860 [-2.8792; 4.4512] 0.42 0.6743
## SHAM . . . .
## TACS_10-20EEG 0.0519 [-3.2151; 3.3188] 0.03 0.9752
## TDCS_10-20EEG 0.5459 [-0.7744; 1.8662] 0.81 0.4178
## TDCS_10-20EG 2.1510 [-2.5440; 6.8459] 0.90 0.3692
## UNKNOWN_STANDARD 1.5000 [-3.9262; 6.9262] 0.54 0.5880
##
## Quantifying heterogeneity / inconsistency:
## tau^2 = 7.5789; tau = 2.7530; I^2 = 86.2% [83.8%; 88.3%]
##
## Tests of heterogeneity (within designs) and inconsistency (between designs):
## Q d.f. p-value
## Total 697.04 96 < 0.0001
## Within designs 697.04 96 < 0.0001
## Between designs 0.00 0 --
##
## Details of network meta-analysis methods:
## - Frequentist graph-theoretical approach
## - DerSimonian-Laird estimator for tau^2
## - Calculation of I^2 based on Q
##
## Forest Plot:
##
## Network Graph:
##
## League Table for Positive Symptoms :
## CTBS_10-20EEG CTBS_CM
## CTBS_10-20EEG CTBS_10-20EEG .
## CTBS_CM -5.41 [-10.80; -0.02] CTBS_CM
## CTBS_NEURONAV -4.36 [-10.94; 2.22] 1.05 [ -6.76; 8.87]
## DTMS_CM -4.81 [ -9.84; 0.22] 0.60 [ -5.96; 7.16]
## HD-TDCS_10-10EEG -4.08 [-10.16; 2.01] 1.33 [ -6.07; 8.74]
## HD-TDCS_10-20EEG -4.79 [-11.29; 1.72] 0.62 [ -7.13; 8.37]
## HF-RTMS_10-20EEG -3.77 [ -6.94; -0.61] 1.64 [ -3.63; 6.91]
## HF-RTMS_CM -4.41 [ -7.31; -1.50] 1.00 [ -4.11; 6.12]
## HF-RTMS_NA -3.30 [ -9.89; 3.30] 2.11 [ -5.71; 9.94]
## HF-RTMS_NEURONAV -3.95 [ -7.15; -0.74] 1.46 [ -3.83; 6.75]
## ITBS_10-20EEG -2.63 [ -6.36; 1.11] 2.78 [ -2.85; 8.41]
## ITBS_CM -5.21 [-11.13; 0.72] 0.20 [ -7.06; 7.47]
## ITBS_NA -3.85 [ -9.84; 2.14] 1.56 [ -5.76; 8.88]
## ITBS_NEURONAV -6.52 [-10.32; -2.73] -1.11 [ -6.78; 4.56]
## LF-RTMS_10-10EEG -5.55 [-11.60; 0.51] -0.14 [ -7.51; 7.24]
## LF-RTMS_10-20EEG -6.39 [ -9.17; -3.61] -0.98 [ -6.02; 4.07]
## LF-RTMS_CM -1.95 [ -6.01; 2.11] 3.46 [ -2.39; 9.30]
## LF-RTMS_NEURONAV -3.63 [ -7.16; -0.09] 1.78 [ -3.72; 7.28]
## PRM-RTMS_NEURONAV -4.29 [ -8.66; 0.08] 1.12 [ -4.95; 7.19]
## SHAM -3.51 [ -5.89; -1.12] 1.90 [ -2.93; 6.74]
## TACS_10-20EEG -3.56 [ -7.60; 0.48] 1.85 [ -3.99; 7.69]
## TDCS_10-20EEG -4.05 [ -6.78; -1.33] 1.36 [ -3.66; 6.37]
## TDCS_10-20EG -5.66 [-10.92; -0.39] -0.25 [ -6.99; 6.49]
## UNKNOWN_STANDARD -5.01 [-10.93; 0.92] 0.40 [ -6.87; 7.67]
## CTBS_NEURONAV DTMS_CM
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV CTBS_NEURONAV .
## DTMS_CM -0.46 [ -8.02; 7.11] DTMS_CM
## HD-TDCS_10-10EEG 0.28 [ -8.03; 8.59] 0.74 [ -6.40; 7.88]
## HD-TDCS_10-20EEG -0.43 [ -9.05; 8.19] 0.03 [ -7.47; 7.53]
## HF-RTMS_10-20EEG 0.58 [ -5.90; 7.06] 1.04 [ -3.86; 5.93]
## HF-RTMS_CM -0.05 [ -6.41; 6.31] 0.40 [ -4.33; 5.14]
## HF-RTMS_NA 1.06 [ -7.62; 9.74] 1.52 [ -6.06; 9.09]
## HF-RTMS_NEURONAV 0.41 [ -6.09; 6.90] 0.86 [ -4.06; 5.78]
## ITBS_10-20EEG 1.73 [ -5.05; 8.50] 2.18 [ -3.10; 7.46]
## ITBS_CM -0.85 [ -9.04; 7.34] -0.39 [ -7.40; 6.61]
## ITBS_NA 0.51 [ -7.73; 8.75] 0.97 [ -6.09; 8.02]
## ITBS_NEURONAV -2.17 [ -8.97; 4.64] -1.71 [ -7.03; 3.61]
## LF-RTMS_10-10EEG -1.19 [ -9.48; 7.10] -0.73 [ -7.85; 6.38]
## LF-RTMS_10-20EEG -2.03 [ -8.33; 4.27] -1.58 [ -6.23; 3.08]
## LF-RTMS_CM 2.40 [ -4.56; 9.36] 2.86 [ -2.66; 8.37]
## LF-RTMS_NEURONAV 0.73 [ -5.94; 7.39] 1.18 [ -3.96; 6.32]
## PRM-RTMS_NEURONAV 0.06 [ -7.08; 7.21] 0.52 [ -5.23; 6.27]
## SHAM 0.85 [ -5.28; 6.98] 1.31 [ -3.12; 5.73]
## TACS_10-20EEG 0.80 [ -6.15; 7.75] 1.25 [ -4.25; 6.76]
## TDCS_10-20EEG 0.30 [ -5.97; 6.58] 0.76 [ -3.86; 5.38]
## TDCS_10-20EG -1.30 [ -9.03; 6.42] -0.85 [ -7.30; 5.61]
## UNKNOWN_STANDARD -0.65 [ -8.84; 7.54] -0.19 [ -7.20; 6.81]
## HD-TDCS_10-10EEG HD-TDCS_10-20EEG
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-10EEG HD-TDCS_10-10EEG .
## HD-TDCS_10-20EEG -0.71 [ -8.96; 7.54] HD-TDCS_10-20EEG
## HF-RTMS_10-20EEG 0.30 [ -5.67; 6.28] 1.01 [ -5.39; 7.42]
## HF-RTMS_CM -0.33 [ -6.17; 5.51] 0.38 [ -5.90; 6.66]
## HF-RTMS_NA 0.78 [ -7.54; 9.10] 1.49 [ -7.14; 10.12]
## HF-RTMS_NEURONAV 0.13 [ -5.87; 6.12] 0.84 [ -5.59; 7.26]
## ITBS_10-20EEG 1.45 [ -4.85; 7.75] 2.16 [ -4.54; 8.86]
## ITBS_CM -1.13 [ -8.93; 6.67] -0.42 [ -8.55; 7.71]
## ITBS_NA 0.23 [ -7.62; 8.08] 0.94 [ -7.24; 9.12]
## ITBS_NEURONAV -2.45 [ -8.78; 3.89] -1.74 [ -8.47; 5.00]
## LF-RTMS_10-10EEG -1.47 [ -9.37; 6.43] -0.76 [ -8.99; 7.47]
## LF-RTMS_10-20EEG -2.31 [ -8.09; 3.47] -1.60 [ -7.82; 4.62]
## LF-RTMS_CM 2.12 [ -4.37; 8.62] 2.83 [ -4.06; 9.72]
## LF-RTMS_NEURONAV 0.45 [ -5.73; 6.63] 1.16 [ -5.43; 7.75]
## PRM-RTMS_NEURONAV -0.22 [ -6.91; 6.48] 0.49 [ -6.58; 7.57]
## SHAM 0.57 [ -5.03; 6.17] 1.28 [ -4.77; 7.33]
## TACS_10-20EEG 0.52 [ -5.97; 7.00] 1.23 [ -5.65; 8.11]
## TDCS_10-20EEG 0.02 [ -5.73; 5.78] 0.73 [ -5.46; 6.93]
## TDCS_10-20EG -1.58 [ -8.89; 5.73] -0.87 [ -8.53; 6.79]
## UNKNOWN_STANDARD -0.93 [ -8.73; 6.87] -0.22 [ -8.35; 7.91]
## HF-RTMS_10-20EEG HF-RTMS_CM
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-10EEG . .
## HD-TDCS_10-20EEG . .
## HF-RTMS_10-20EEG HF-RTMS_10-20EEG .
## HF-RTMS_CM -0.63 [ -3.30; 2.04] HF-RTMS_CM
## HF-RTMS_NA 0.48 [ -6.02; 6.97] 1.11 [ -5.26; 7.48]
## HF-RTMS_NEURONAV -0.18 [ -3.17; 2.82] 0.46 [ -2.26; 3.17]
## ITBS_10-20EEG 1.15 [ -2.41; 4.70] 1.78 [ -1.55; 5.10]
## ITBS_CM -1.43 [ -7.24; 4.38] -0.80 [ -6.47; 4.87]
## ITBS_NA -0.07 [ -5.95; 5.81] 0.56 [ -5.18; 6.30]
## ITBS_NEURONAV -2.75 [ -6.37; 0.87] -2.12 [ -5.51; 1.28]
## LF-RTMS_10-10EEG -1.77 [ -7.72; 4.18] -1.14 [ -6.95; 4.67]
## LF-RTMS_10-20EEG -2.61 [ -5.15; -0.08] -1.98 [ -4.18; 0.22]
## LF-RTMS_CM 1.82 [ -2.08; 5.71] 2.45 [ -1.23; 6.14]
## LF-RTMS_NEURONAV 0.14 [ -3.20; 3.49] 0.78 [ -2.32; 3.87]
## PRM-RTMS_NEURONAV -0.52 [ -4.74; 3.70] 0.11 [ -3.91; 4.14]
## SHAM 0.27 [ -1.82; 2.36] 0.90 [ -0.76; 2.57]
## TACS_10-20EEG 0.22 [ -3.66; 4.09] 0.85 [ -2.82; 4.52]
## TDCS_10-20EEG -0.28 [ -2.75; 2.19] 0.35 [ -1.77; 2.48]
## TDCS_10-20EG -1.88 [ -7.02; 3.25] -1.25 [ -6.23; 3.73]
## UNKNOWN_STANDARD -1.23 [ -7.05; 4.58] -0.60 [ -6.28; 5.08]
## HF-RTMS_NA HF-RTMS_NEURONAV
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-10EEG . .
## HD-TDCS_10-20EEG . .
## HF-RTMS_10-20EEG . .
## HF-RTMS_CM . .
## HF-RTMS_NA HF-RTMS_NA .
## HF-RTMS_NEURONAV -0.65 [ -7.16; 5.86] HF-RTMS_NEURONAV
## ITBS_10-20EEG 0.67 [ -6.12; 7.46] 1.32 [ -2.27; 4.91]
## ITBS_CM -1.91 [-10.11; 6.29] -1.26 [ -7.09; 4.57]
## ITBS_NA -0.55 [ -8.80; 7.70] 0.10 [ -5.80; 6.00]
## ITBS_NEURONAV -3.23 [-10.05; 3.60] -2.57 [ -6.22; 1.08]
## LF-RTMS_10-10EEG -2.25 [-10.55; 6.05] -1.60 [ -7.57; 4.37]
## LF-RTMS_10-20EEG -3.09 [ -9.41; 3.22] -2.44 [ -5.02; 0.14]
## LF-RTMS_CM 1.34 [ -5.63; 8.31] 1.99 [ -1.93; 5.92]
## LF-RTMS_NEURONAV -0.33 [ -7.01; 6.35] 0.32 [ -3.06; 3.70]
## PRM-RTMS_NEURONAV -1.00 [ -8.15; 6.16] -0.34 [ -4.59; 3.90]
## SHAM -0.21 [ -6.36; 5.94] 0.44 [ -1.70; 2.59]
## TACS_10-20EEG -0.26 [ -7.22; 6.70] 0.39 [ -3.52; 4.30]
## TDCS_10-20EEG -0.76 [ -7.04; 5.53] -0.10 [ -2.62; 2.42]
## TDCS_10-20EG -2.36 [-10.10; 5.37] -1.71 [ -6.87; 3.45]
## UNKNOWN_STANDARD -1.71 [ -9.91; 6.49] -1.06 [ -6.89; 4.78]
## ITBS_10-20EEG ITBS_CM
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-10EEG . .
## HD-TDCS_10-20EEG . .
## HF-RTMS_10-20EEG . .
## HF-RTMS_CM . .
## HF-RTMS_NA . .
## HF-RTMS_NEURONAV . .
## ITBS_10-20EEG ITBS_10-20EEG .
## ITBS_CM -2.58 [ -8.72; 3.56] ITBS_CM
## ITBS_NA -1.22 [ -7.42; 4.98] 1.36 [ -6.36; 9.08]
## ITBS_NEURONAV -3.89 [ -8.02; 0.23] -1.32 [ -7.49; 4.86]
## LF-RTMS_10-10EEG -2.92 [ -9.19; 3.35] -0.34 [ -8.11; 7.43]
## LF-RTMS_10-20EEG -3.76 [ -6.98; -0.54] -1.18 [ -6.79; 4.43]
## LF-RTMS_CM 0.67 [ -3.70; 5.04] 3.25 [ -3.09; 9.59]
## LF-RTMS_NEURONAV -1.00 [ -4.89; 2.88] 1.58 [ -4.44; 7.60]
## PRM-RTMS_NEURONAV -1.66 [ -6.32; 3.00] 0.91 [ -5.63; 7.46]
## SHAM -0.88 [ -3.76; 2.00] 1.70 [ -3.72; 7.12]
## TACS_10-20EEG -0.93 [ -5.28; 3.42] 1.65 [ -4.68; 7.98]
## TDCS_10-20EEG -1.42 [ -4.59; 1.74] 1.15 [ -4.43; 6.74]
## TDCS_10-20EG -3.03 [ -8.54; 2.48] -0.45 [ -7.62; 6.72]
## UNKNOWN_STANDARD -2.38 [ -8.52; 3.76] 0.20 [ -7.47; 7.87]
## ITBS_NA ITBS_NEURONAV
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-10EEG . .
## HD-TDCS_10-20EEG . .
## HF-RTMS_10-20EEG . .
## HF-RTMS_CM . .
## HF-RTMS_NA . .
## HF-RTMS_NEURONAV . .
## ITBS_10-20EEG . .
## ITBS_CM . .
## ITBS_NA ITBS_NA .
## ITBS_NEURONAV -2.68 [ -8.91; 3.56] ITBS_NEURONAV
## LF-RTMS_10-10EEG -1.70 [ -9.52; 6.12] 0.98 [ -5.33; 7.28]
## LF-RTMS_10-20EEG -2.54 [ -8.22; 3.14] 0.13 [ -3.15; 3.42]
## LF-RTMS_CM 1.89 [ -4.51; 8.30] 4.57 [ 0.15; 8.99]
## LF-RTMS_NEURONAV 0.22 [ -5.87; 6.30] 2.89 [ -1.05; 6.84]
## PRM-RTMS_NEURONAV -0.45 [ -7.05; 6.16] 2.23 [ -2.48; 6.94]
## SHAM 0.34 [ -5.15; 5.83] 3.02 [ 0.06; 5.97]
## TACS_10-20EEG 0.29 [ -6.10; 6.68] 2.96 [ -1.44; 7.37]
## TDCS_10-20EEG -0.21 [ -5.86; 5.45] 2.47 [ -0.77; 5.71]
## TDCS_10-20EG -1.81 [ -9.04; 5.42] 0.86 [ -4.68; 6.41]
## UNKNOWN_STANDARD -1.16 [ -8.88; 6.56] 1.52 [ -4.66; 7.69]
## LF-RTMS_10-10EEG LF-RTMS_10-20EEG
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-10EEG . .
## HD-TDCS_10-20EEG . .
## HF-RTMS_10-20EEG . .
## HF-RTMS_CM . .
## HF-RTMS_NA . .
## HF-RTMS_NEURONAV . .
## ITBS_10-20EEG . .
## ITBS_CM . .
## ITBS_NA . .
## ITBS_NEURONAV . .
## LF-RTMS_10-10EEG LF-RTMS_10-10EEG .
## LF-RTMS_10-20EEG -0.84 [ -6.59; 4.91] LF-RTMS_10-20EEG
## LF-RTMS_CM 3.59 [ -2.88; 10.06] 4.43 [ 0.84; 8.02]
## LF-RTMS_NEURONAV 1.92 [ -4.23; 8.07] 2.76 [ -0.22; 5.74]
## PRM-RTMS_NEURONAV 1.25 [ -5.41; 7.92] 2.10 [ -1.84; 6.03]
## SHAM 2.04 [ -3.53; 7.61] 2.88 [ 1.44; 4.32]
## TACS_10-20EEG 1.99 [ -4.47; 8.45] 2.83 [ -0.74; 6.40]
## TDCS_10-20EEG 1.49 [ -4.23; 7.22] 2.34 [ 0.38; 4.29]
## TDCS_10-20EG -0.11 [ -7.40; 7.17] 0.73 [ -4.18; 5.64]
## UNKNOWN_STANDARD 0.54 [ -7.24; 8.32] 1.38 [ -4.23; 6.99]
## LF-RTMS_CM LF-RTMS_NEURONAV
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-10EEG . .
## HD-TDCS_10-20EEG . .
## HF-RTMS_10-20EEG . .
## HF-RTMS_CM . .
## HF-RTMS_NA . .
## HF-RTMS_NEURONAV . .
## ITBS_10-20EEG . .
## ITBS_CM . .
## ITBS_NA . .
## ITBS_NEURONAV . .
## LF-RTMS_10-10EEG . .
## LF-RTMS_10-20EEG . .
## LF-RTMS_CM LF-RTMS_CM .
## LF-RTMS_NEURONAV -1.67 [ -5.87; 2.52] LF-RTMS_NEURONAV
## PRM-RTMS_NEURONAV -2.34 [ -7.26; 2.59] -0.66 [ -5.16; 3.84]
## SHAM -1.55 [ -4.84; 1.74] 0.12 [ -2.49; 2.73]
## TACS_10-20EEG -1.60 [ -6.24; 3.03] 0.07 [ -4.11; 4.25]
## TDCS_10-20EEG -2.10 [ -5.64; 1.45] -0.42 [ -3.35; 2.50]
## TDCS_10-20EG -3.70 [ -9.43; 2.03] -2.03 [ -7.40; 3.34]
## UNKNOWN_STANDARD -3.05 [ -9.40; 3.29] -1.38 [ -7.40; 4.64]
## PRM-RTMS_NEURONAV SHAM
## CTBS_10-20EEG . -3.51 [-5.89; -1.12]
## CTBS_CM . 1.90 [-2.93; 6.74]
## CTBS_NEURONAV . 0.85 [-5.28; 6.98]
## DTMS_CM . 1.31 [-3.12; 5.73]
## HD-TDCS_10-10EEG . 0.57 [-5.03; 6.17]
## HD-TDCS_10-20EEG . 1.28 [-4.77; 7.33]
## HF-RTMS_10-20EEG . 0.27 [-1.82; 2.36]
## HF-RTMS_CM . 0.90 [-0.76; 2.57]
## HF-RTMS_NA . -0.21 [-6.36; 5.94]
## HF-RTMS_NEURONAV . 0.44 [-1.70; 2.59]
## ITBS_10-20EEG . -0.88 [-3.76; 2.00]
## ITBS_CM . 1.70 [-3.72; 7.12]
## ITBS_NA . 0.34 [-5.15; 5.83]
## ITBS_NEURONAV . 3.02 [ 0.06; 5.97]
## LF-RTMS_10-10EEG . 2.04 [-3.53; 7.61]
## LF-RTMS_10-20EEG . 2.88 [ 1.44; 4.32]
## LF-RTMS_CM . -1.55 [-4.84; 1.74]
## LF-RTMS_NEURONAV . 0.12 [-2.49; 2.73]
## PRM-RTMS_NEURONAV PRM-RTMS_NEURONAV 0.79 [-2.88; 4.45]
## SHAM 0.79 [ -2.88; 4.45] SHAM
## TACS_10-20EEG 0.73 [ -4.18; 5.64] -0.05 [ -3.32; 3.22]
## TDCS_10-20EEG 0.24 [ -3.66; 4.14] -0.55 [ -1.87; 0.77]
## TDCS_10-20EG -1.36 [ -7.32; 4.59] -2.15 [ -6.85; 2.54]
## UNKNOWN_STANDARD -0.71 [ -7.26; 5.83] -1.50 [ -6.93; 3.93]
## TACS_10-20EEG TDCS_10-20EEG
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-10EEG . .
## HD-TDCS_10-20EEG . .
## HF-RTMS_10-20EEG . .
## HF-RTMS_CM . .
## HF-RTMS_NA . .
## HF-RTMS_NEURONAV . .
## ITBS_10-20EEG . .
## ITBS_CM . .
## ITBS_NA . .
## ITBS_NEURONAV . .
## LF-RTMS_10-10EEG . .
## LF-RTMS_10-20EEG . .
## LF-RTMS_CM . .
## LF-RTMS_NEURONAV . .
## PRM-RTMS_NEURONAV . .
## SHAM -0.05 [-3.32; 3.22] -0.55 [-1.87; 0.77]
## TACS_10-20EEG TACS_10-20EEG .
## TDCS_10-20EEG -0.49 [ -4.02; 3.03] TDCS_10-20EEG
## TDCS_10-20EG -2.10 [ -7.82; 3.62] -1.61 [ -6.48; 3.27]
## UNKNOWN_STANDARD -1.45 [ -7.78; 4.89] -0.95 [ -6.54; 4.63]
## TDCS_10-20EG UNKNOWN_STANDARD
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-10EEG . .
## HD-TDCS_10-20EEG . .
## HF-RTMS_10-20EEG . .
## HF-RTMS_CM . .
## HF-RTMS_NA . .
## HF-RTMS_NEURONAV . .
## ITBS_10-20EEG . .
## ITBS_CM . .
## ITBS_NA . .
## ITBS_NEURONAV . .
## LF-RTMS_10-10EEG . .
## LF-RTMS_10-20EEG . .
## LF-RTMS_CM . .
## LF-RTMS_NEURONAV . .
## PRM-RTMS_NEURONAV . .
## SHAM -2.15 [-6.85; 2.54] -1.50 [-6.93; 3.93]
## TACS_10-20EEG . .
## TDCS_10-20EEG . .
## TDCS_10-20EG TDCS_10-20EG .
## UNKNOWN_STANDARD 0.65 [ -6.52; 7.83] UNKNOWN_STANDARD
##
## Upper triangle: MD (95% CI); lower triangle: p-value
## Positive values favor the column-defining treatment
##
## Treatment Rankings (SUCRA values):
## SUCRA values not available in netrank output
##
## ==================================================
## Network Meta-Analysis for Negative Symptoms
## ==================================================
##
## Available treatments for Negative Symptoms NMA:
##
## CTBS_10-20EEG CTBS_CM CTBS_NEURONAV DTMS_CM
## 1 1 1 4
## HD-TDCS_10-10EEG HD-TDCS_10-20EEG HF-RTMS_10-20EEG HF-RTMS_CM
## 2 1 11 13
## HF-RTMS_NA HF-RTMS_NEURONAV ITBS_10-20EEG ITBS_CM
## 1 8 7 5
## ITBS_NA ITBS_NEURONAV LF-RTMS_10-10EEG LF-RTMS_10-20EEG
## 1 5 1 12
## LF-RTMS_CM LF-RTMS_NEURONAV SHAM TACS_10-20EEG
## 4 1 108 4
## TDCS_10-20EEG TDCS_10-20EG UNKNOWN_STANDARD
## 22 1 2
##
## Running network meta-analysis for Negative Symptoms ...
##
## Summary of results:
## Original data:
##
## treat1
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANAS_1 LF-RTMS_10-20EEG
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANAS_1 LF-RTMS_10-20EEG
## barr, 2012_HF-RTMS_NEURONAV_N_PANSS_1 HF-RTMS_NEURONAV
## barr, 2012_HF-RTMS_NEURONAV_N_SANS_1 HF-RTMS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_N_SANS_1 ITBS_NEURONAV
## battion, 2021_ITBS_CM_N_SANS_1 ITBS_CM
## bodén, 2021_ITBS_CM_N_CAIN_1 ITBS_CM
## bose, 2018_TDCS_10-20EEG_N_SANS_1 SHAM
## chang-a, 2021_TACS_10-20EEG_N_PANSS_1 SHAM
## chang-a, 2021_TACS_10-20EEG_N_SANS_1 SHAM
## chauhan, 2021_ITBS_10-20EEG_N_PANSS_1 ITBS_10-20EEG
## de jesus, 2011_LF-RTMS_10-20EEG_N_BPRS_1 LF-RTMS_10-20EEG
## dharani, 2021_HD-TDCS_10-10EEG_N_PANSS_1 HD-TDCS_10-10EEG
## dharani, 2021_HD-TDCS_10-10EEG_N_SANS_1 HD-TDCS_10-10EEG
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_SANS_1 LF-RTMS_10-20EEG
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## du, 2024_HF-RTMS_NEURONAV_N_BPRS_1 HF-RTMS_NEURONAV
## du, 2022_HF-RTMS_10-20EEG_N_SANS_1 HF-RTMS_10-20EEG
## du, 2022_HF-RTMS_10-20EEG_N_PANSS_1 HF-RTMS_10-20EEG
## fitzerald, 2008_LF-RTMS_CM_N_SANS_1 LF-RTMS_CM
## fitzerald, 2008_LF-RTMS_CM_N_PANSS_1 LF-RTMS_CM
## fitzerald-l, 2014_TDCS_10-20EEG_N_PANSS_1 SHAM
## fitzerald-l, 2014_TDCS_10-20EEG_N_SANS_1 SHAM
## fitzerald-bi, 2014_TDCS_10-20EEG_N_PANSS_1 SHAM
## fitzerald-bi, 2014_TDCS_10-20EEG_N_SANS_1 SHAM
## frohlich, 2016_TDCS_10-20EEG_N_PANSS_1 SHAM
## gao, 2024_ITBS_10-20EEG_N_PANSS_1 ITBS_10-20EEG
## gao, 2024_ITBS_10-20EEG_N_SANS_1 ITBS_10-20EEG
## garg, 2016_DTMS_CM_N_PANSS_1 DTMS_CM
## gomes, 2018_TDCS_10-20EEG_N_PANSS-N_1 SHAM
## guan, 2020_HF-RTMS_NEURONAV_N_PANSS-N_1 HF-RTMS_NEURONAV
## guleken, 2020_HF-RTMS_CM_N_SANS_1 HF-RTMS_CM
## holi, 2004_HF-RTMS_10-20EEG_N_PANSS_1 HF-RTMS_10-20EEG
## hu, 2024_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## hu, 2023_LF-RTMS_10-10EEG_N_PANSS_1 LF-RTMS_10-10EEG
## huang, 2016_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## jeon, 2018_TDCS_10-20EEG_N_PANSS_1 SHAM
## jin, 2023_ITBS_NA_N_PANSS_1 ITBS_NA
## kang, 2024_CTBS_CM_N_PANSS_1 CTBS_CM
## klein, 1999_LF-RTMS_CM_N_PANSS_1 LF-RTMS_CM
## koops, 2018_TDCS_10-20EEG_N_PANSS_1 SHAM
## kos, 2024_TDCS_10-20EEG_N_SANS_1 SHAM
## kos, 2024_TDCS_10-20EEG_N_AES_1 SHAM
## liu, 2024_HF-RTMS_NA_N_PANSS_1 HF-RTMS_NA
## lyu, 2024_TDCS_10-20EEG_N_PANSS_1 SHAM
## lyu, 2024_TDCS_10-20EEG_N_SANS_1 SHAM
## marquardt, 2022_TDCS_10-20EEG_N_PANSS_1 SHAM
## mcintosh, 2004_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## mellin-tacs, 2018_TACS_10-20EEG_N_PANSS-N_1 SHAM
## mellin-tdcs, 2018_TDCS_10-20EEG_N_PANSS_1 SHAM
## moeller, 2022_DTMS_CM_N_PANSS_1 DTMS_CM
## mondino, 2015_TDCS_10-20EG_N_PANSS_1 SHAM
## novak, 2006_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## paillere-martinot, 2017_LF-RTMS_NEURONAV_N_SANS_1 LF-RTMS_NEURONAV
## palm, 2016_TDCS_10-20EEG_N_PANSS_1 SHAM
## palm, 2016_TDCS_10-20EEG_N_SANS_1 SHAM
## prikryl, 2007_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## prikryl, 2007_HF-RTMS_CM_N_SANS_1 HF-RTMS_CM
## prikryl, 2012_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## prikryl, 2014_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## prikryl, 2013_HF-RTMS_CM_N_SANS_1 HF-RTMS_CM
## quan, 2015_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## quan, 2015_HF-RTMS_CM_N_SANS_1 HF-RTMS_CM
## rabany, 2014_DTMS_CM_N_PANSS_1 DTMS_CM
## rabany, 2014_DTMS_CM_N_SANS_1 DTMS_CM
## rosa, 2007_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## saba, 2006_LF-RTMS_CM_N_PANSS_1 LF-RTMS_CM
## singh, 2020_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## singh, 2020_HF-RTMS_CM_N_SANS_1 HF-RTMS_CM
## smith, 2015_TDCS_10-20EEG_N_PANSS_1 SHAM
## smith, 2020_TDCS_10-20EEG_N_PANSS_1 SHAM
## su, 2023b_HF-RTMS_NEURONAV_N_PANSS_1 HF-RTMS_NEURONAV
## su, 2022_HF-RTMS_NEURONAV_N_PANSS_1 HF-RTMS_NEURONAV
## tikka, 2017_CTBS_NEURONAV_N_PANSS_1 CTBS_NEURONAV
## tyagi, 2022_CTBS_10-20EEG_N_PANSS_1 CTBS_10-20EEG
## valiengo, 2020_TDCS_10-20EEG_N_PANSS_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_N_PANSS_1 ITBS_10-20EEG
## vergallito, 2024_ITBS_10-20EEG_N_BNSS_1 ITBS_10-20EEG
## walther-lft, 2024_UNKNOWN_STANDARD_N_PANSS_1 SHAM
## walther-lft, 2024_UNKNOWN_STANDARD_N_BNSS_1 SHAM
## walther-itbs, 2024_ITBS_CM_N_PANSS_1 ITBS_CM
## walther-itbs, 2024_ITBS_CM_N_BNSS_1 ITBS_CM
## wang, 2020_ITBS_NEURONAV_N_PANSS_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_N_SANS_1 ITBS_NEURONAV
## wang, 2022_ITBS_NEURONAV_N_PANSS_1 ITBS_NEURONAV
## wang, 2022_ITBS_NEURONAV_N_SANS_1 ITBS_NEURONAV
## weickert, 2019_TDCS_10-20EEG_N_PANSS_1 SHAM
## wen, 2021_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## wobrock, 2015_HF-RTMS_10-20EEG_N_PANSS_1 HF-RTMS_10-20EEG
## xie, 2023-a_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## xiu-10hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 HF-RTMS_NEURONAV
## xiu-20hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 HF-RTMS_NEURONAV
## xu, 2023_HD-TDCS_10-20EEG_N_PANSS_1 HD-TDCS_10-20EEG
## yuanjun, 2024_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## zhang, 2022_TACS_10-20EEG_N_PANSS_1 SHAM
## zhao-tbs, 2014_ITBS_10-20EEG_N_PANSS_1 ITBS_10-20EEG
## zhao-tbs, 2014_ITBS_10-20EEG_N_SANS_1 ITBS_10-20EEG
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 HF-RTMS_10-20EEG
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 HF-RTMS_10-20EEG
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 HF-RTMS_10-20EEG
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 HF-RTMS_10-20EEG
## zhou, 2024_HF-RTMS_10-20EEG_N_PANSS_1 HF-RTMS_10-20EEG
## zhou, 2023_TDCS_10-20EEG_N_SANS_1 SHAM
## zhu, 2021_ITBS_CM_N_PANSS_1 ITBS_CM
## zhuo, 2019_HF-RTMS_10-20EEG_N_PANSS_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_N_SANS_1 HF-RTMS_10-20EEG
## treat2 TE
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANSS_1 SHAM 0.8000
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANAS_1 SHAM 2.6300
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANSS_1 SHAM -0.1500
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANAS_1 SHAM 2.4000
## barr, 2012_HF-RTMS_NEURONAV_N_PANSS_1 SHAM -2.9600
## barr, 2012_HF-RTMS_NEURONAV_N_SANS_1 SHAM -0.1200
## basavaraju, 2021_ITBS_NEURONAV_N_SANS_1 SHAM -2.5000
## battion, 2021_ITBS_CM_N_SANS_1 SHAM -0.2300
## bodén, 2021_ITBS_CM_N_CAIN_1 SHAM 0.6100
## bose, 2018_TDCS_10-20EEG_N_SANS_1 TDCS_10-20EEG 2.0600
## chang-a, 2021_TACS_10-20EEG_N_PANSS_1 TACS_10-20EEG -1.9500
## chang-a, 2021_TACS_10-20EEG_N_SANS_1 TACS_10-20EEG -4.9400
## chauhan, 2021_ITBS_10-20EEG_N_PANSS_1 SHAM -0.1200
## de jesus, 2011_LF-RTMS_10-20EEG_N_BPRS_1 SHAM 0.8500
## dharani, 2021_HD-TDCS_10-10EEG_N_PANSS_1 SHAM 2.8500
## dharani, 2021_HD-TDCS_10-10EEG_N_SANS_1 SHAM 6.8600
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_SANS_1 SHAM 6.2000
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_PANSS_1 SHAM 0.2000
## du, 2024_HF-RTMS_NEURONAV_N_BPRS_1 SHAM -0.1100
## du, 2022_HF-RTMS_10-20EEG_N_SANS_1 SHAM 4.6000
## du, 2022_HF-RTMS_10-20EEG_N_PANSS_1 SHAM 0.6000
## fitzerald, 2008_LF-RTMS_CM_N_SANS_1 SHAM 9.9000
## fitzerald, 2008_LF-RTMS_CM_N_PANSS_1 SHAM 0.6000
## fitzerald-l, 2014_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG 1.7000
## fitzerald-l, 2014_TDCS_10-20EEG_N_SANS_1 TDCS_10-20EEG 1.8000
## fitzerald-bi, 2014_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG -9.0000
## fitzerald-bi, 2014_TDCS_10-20EEG_N_SANS_1 TDCS_10-20EEG 3.2000
## frohlich, 2016_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG -0.0800
## gao, 2024_ITBS_10-20EEG_N_PANSS_1 SHAM 3.5600
## gao, 2024_ITBS_10-20EEG_N_SANS_1 SHAM 5.0000
## garg, 2016_DTMS_CM_N_PANSS_1 SHAM 1.4500
## gomes, 2018_TDCS_10-20EEG_N_PANSS-N_1 TDCS_10-20EEG -3.6600
## guan, 2020_HF-RTMS_NEURONAV_N_PANSS-N_1 SHAM -0.3000
## guleken, 2020_HF-RTMS_CM_N_SANS_1 SHAM 21.5000
## holi, 2004_HF-RTMS_10-20EEG_N_PANSS_1 SHAM -4.4000
## hu, 2024_LF-RTMS_10-20EEG_N_PANSS_1 SHAM 2.4000
## hu, 2023_LF-RTMS_10-10EEG_N_PANSS_1 SHAM 2.3100
## huang, 2016_HF-RTMS_CM_N_PANSS_1 SHAM 0.1400
## jeon, 2018_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG -0.4600
## jin, 2023_ITBS_NA_N_PANSS_1 SHAM 1.6000
## kang, 2024_CTBS_CM_N_PANSS_1 SHAM 0.0600
## klein, 1999_LF-RTMS_CM_N_PANSS_1 SHAM 0.3000
## koops, 2018_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG -0.7000
## kos, 2024_TDCS_10-20EEG_N_SANS_1 TDCS_10-20EEG -3.8000
## kos, 2024_TDCS_10-20EEG_N_AES_1 TDCS_10-20EEG 0.3000
## liu, 2024_HF-RTMS_NA_N_PANSS_1 SHAM 1.5000
## lyu, 2024_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG 1.6800
## lyu, 2024_TDCS_10-20EEG_N_SANS_1 TDCS_10-20EEG 0.5300
## marquardt, 2022_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG 1.7300
## mcintosh, 2004_LF-RTMS_10-20EEG_N_PANSS_1 SHAM 0.2500
## mellin-tacs, 2018_TACS_10-20EEG_N_PANSS-N_1 TACS_10-20EEG -1.0900
## mellin-tdcs, 2018_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG -1.4200
## moeller, 2022_DTMS_CM_N_PANSS_1 SHAM 4.1000
## mondino, 2015_TDCS_10-20EG_N_PANSS_1 TDCS_10-20EG -3.0000
## novak, 2006_HF-RTMS_CM_N_PANSS_1 SHAM -0.8750
## paillere-martinot, 2017_LF-RTMS_NEURONAV_N_SANS_1 SHAM -2.6300
## palm, 2016_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG -1.2000
## palm, 2016_TDCS_10-20EEG_N_SANS_1 TDCS_10-20EEG -9.7000
## prikryl, 2007_HF-RTMS_CM_N_PANSS_1 SHAM 4.3600
## prikryl, 2007_HF-RTMS_CM_N_SANS_1 SHAM 24.9900
## prikryl, 2012_HF-RTMS_CM_N_PANSS_1 SHAM 6.1700
## prikryl, 2014_HF-RTMS_CM_N_PANSS_1 SHAM 5.2300
## prikryl, 2013_HF-RTMS_CM_N_SANS_1 SHAM 23.6000
## quan, 2015_HF-RTMS_CM_N_PANSS_1 SHAM 1.7800
## quan, 2015_HF-RTMS_CM_N_SANS_1 SHAM 5.2900
## rabany, 2014_DTMS_CM_N_PANSS_1 SHAM -0.2000
## rabany, 2014_DTMS_CM_N_SANS_1 SHAM 7.3000
## rosa, 2007_LF-RTMS_10-20EEG_N_PANSS_1 SHAM -1.3000
## saba, 2006_LF-RTMS_CM_N_PANSS_1 SHAM -3.7500
## singh, 2020_HF-RTMS_CM_N_PANSS_1 SHAM 0.7400
## singh, 2020_HF-RTMS_CM_N_SANS_1 SHAM 5.7900
## smith, 2015_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG 2.4000
## smith, 2020_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG -0.2500
## su, 2023b_HF-RTMS_NEURONAV_N_PANSS_1 SHAM -0.1000
## su, 2022_HF-RTMS_NEURONAV_N_PANSS_1 SHAM -0.1000
## tikka, 2017_CTBS_NEURONAV_N_PANSS_1 SHAM 1.0200
## tyagi, 2022_CTBS_10-20EEG_N_PANSS_1 SHAM 0.3200
## valiengo, 2020_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG -0.7400
## vergallito, 2024_ITBS_10-20EEG_N_PANSS_1 SHAM -0.7100
## vergallito, 2024_ITBS_10-20EEG_N_BNSS_1 SHAM -15.1400
## walther-lft, 2024_UNKNOWN_STANDARD_N_PANSS_1 UNKNOWN_STANDARD 0.5000
## walther-lft, 2024_UNKNOWN_STANDARD_N_BNSS_1 UNKNOWN_STANDARD -1.7000
## walther-itbs, 2024_ITBS_CM_N_PANSS_1 SHAM 0.5000
## walther-itbs, 2024_ITBS_CM_N_BNSS_1 SHAM -0.5000
## wang, 2020_ITBS_NEURONAV_N_PANSS_1 SHAM 2.4400
## wang, 2020_ITBS_NEURONAV_N_SANS_1 SHAM 10.1600
## wang, 2022_ITBS_NEURONAV_N_PANSS_1 SHAM 4.3400
## wang, 2022_ITBS_NEURONAV_N_SANS_1 SHAM 11.5610
## weickert, 2019_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG 1.7000
## wen, 2021_HF-RTMS_CM_N_PANSS_1 SHAM -1.1000
## wobrock, 2015_HF-RTMS_10-20EEG_N_PANSS_1 SHAM 0.5000
## xie, 2023-a_LF-RTMS_10-20EEG_N_PANSS_1 SHAM 1.0000
## xiu-10hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 SHAM 3.4000
## xiu-20hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 SHAM 0.4000
## xu, 2023_HD-TDCS_10-20EEG_N_PANSS_1 SHAM 0.3200
## yuanjun, 2024_LF-RTMS_10-20EEG_N_PANSS_1 SHAM 1.3700
## zhang, 2022_TACS_10-20EEG_N_PANSS_1 TACS_10-20EEG -0.0900
## zhao-tbs, 2014_ITBS_10-20EEG_N_PANSS_1 SHAM 15.8000
## zhao-tbs, 2014_ITBS_10-20EEG_N_SANS_1 SHAM 19.7000
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 SHAM 10.3000
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 SHAM 14.8000
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 SHAM 7.2000
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 SHAM 10.8000
## zhou, 2024_HF-RTMS_10-20EEG_N_PANSS_1 SHAM 4.5000
## zhou, 2023_TDCS_10-20EEG_N_SANS_1 TDCS_10-20EEG -0.4600
## zhu, 2021_ITBS_CM_N_PANSS_1 SHAM 1.6600
## zhuo, 2019_HF-RTMS_10-20EEG_N_PANSS_1 SHAM 1.7200
## zhuo, 2019_HF-RTMS_10-20EEG_N_SANS_1 SHAM 4.8500
## seTE
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANSS_1 1.3607
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANAS_1 2.8163
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANSS_1 1.4143
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANAS_1 3.1294
## barr, 2012_HF-RTMS_NEURONAV_N_PANSS_1 2.2399
## barr, 2012_HF-RTMS_NEURONAV_N_SANS_1 4.2609
## basavaraju, 2021_ITBS_NEURONAV_N_SANS_1 2.6652
## battion, 2021_ITBS_CM_N_SANS_1 6.1623
## bodén, 2021_ITBS_CM_N_CAIN_1 3.7960
## bose, 2018_TDCS_10-20EEG_N_SANS_1 5.2239
## chang-a, 2021_TACS_10-20EEG_N_PANSS_1 1.0428
## chang-a, 2021_TACS_10-20EEG_N_SANS_1 3.0199
## chauhan, 2021_ITBS_10-20EEG_N_PANSS_1 0.9270
## de jesus, 2011_LF-RTMS_10-20EEG_N_BPRS_1 0.9318
## dharani, 2021_HD-TDCS_10-10EEG_N_PANSS_1 2.5493
## dharani, 2021_HD-TDCS_10-10EEG_N_SANS_1 7.3548
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_SANS_1 4.9744
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_PANSS_1 1.2209
## du, 2024_HF-RTMS_NEURONAV_N_BPRS_1 1.6458
## du, 2022_HF-RTMS_10-20EEG_N_SANS_1 4.5982
## du, 2022_HF-RTMS_10-20EEG_N_PANSS_1 1.8788
## fitzerald, 2008_LF-RTMS_CM_N_SANS_1 3.6051
## fitzerald, 2008_LF-RTMS_CM_N_PANSS_1 1.6912
## fitzerald-l, 2014_TDCS_10-20EEG_N_PANSS_1 1.4456
## fitzerald-l, 2014_TDCS_10-20EEG_N_SANS_1 3.3060
## fitzerald-bi, 2014_TDCS_10-20EEG_N_PANSS_1 1.6702
## fitzerald-bi, 2014_TDCS_10-20EEG_N_SANS_1 5.1356
## frohlich, 2016_TDCS_10-20EEG_N_PANSS_1 2.0833
## gao, 2024_ITBS_10-20EEG_N_PANSS_1 0.5119
## gao, 2024_ITBS_10-20EEG_N_SANS_1 0.8153
## garg, 2016_DTMS_CM_N_PANSS_1 2.0568
## gomes, 2018_TDCS_10-20EEG_N_PANSS-N_1 2.1458
## guan, 2020_HF-RTMS_NEURONAV_N_PANSS-N_1 1.9514
## guleken, 2020_HF-RTMS_CM_N_SANS_1 4.5186
## holi, 2004_HF-RTMS_10-20EEG_N_PANSS_1 3.1039
## hu, 2024_LF-RTMS_10-20EEG_N_PANSS_1 0.9296
## hu, 2023_LF-RTMS_10-10EEG_N_PANSS_1 0.9509
## huang, 2016_HF-RTMS_CM_N_PANSS_1 1.2151
## jeon, 2018_TDCS_10-20EEG_N_PANSS_1 1.3627
## jin, 2023_ITBS_NA_N_PANSS_1 0.5874
## kang, 2024_CTBS_CM_N_PANSS_1 1.6566
## klein, 1999_LF-RTMS_CM_N_PANSS_1 1.5868
## koops, 2018_TDCS_10-20EEG_N_PANSS_1 1.1318
## kos, 2024_TDCS_10-20EEG_N_SANS_1 4.2701
## kos, 2024_TDCS_10-20EEG_N_AES_1 2.0038
## liu, 2024_HF-RTMS_NA_N_PANSS_1 1.4242
## lyu, 2024_TDCS_10-20EEG_N_PANSS_1 1.4341
## lyu, 2024_TDCS_10-20EEG_N_SANS_1 3.6185
## marquardt, 2022_TDCS_10-20EEG_N_PANSS_1 2.7908
## mcintosh, 2004_LF-RTMS_10-20EEG_N_PANSS_1 2.3243
## mellin-tacs, 2018_TACS_10-20EEG_N_PANSS-N_1 1.7024
## mellin-tdcs, 2018_TDCS_10-20EEG_N_PANSS_1 2.2279
## moeller, 2022_DTMS_CM_N_PANSS_1 2.1254
## mondino, 2015_TDCS_10-20EG_N_PANSS_1 1.8472
## novak, 2006_HF-RTMS_CM_N_PANSS_1 2.4678
## paillere-martinot, 2017_LF-RTMS_NEURONAV_N_SANS_1 8.1293
## palm, 2016_TDCS_10-20EEG_N_PANSS_1 1.6956
## palm, 2016_TDCS_10-20EEG_N_SANS_1 6.4075
## prikryl, 2007_HF-RTMS_CM_N_PANSS_1 1.7147
## prikryl, 2007_HF-RTMS_CM_N_SANS_1 5.7979
## prikryl, 2012_HF-RTMS_CM_N_PANSS_1 1.3747
## prikryl, 2014_HF-RTMS_CM_N_PANSS_1 1.2594
## prikryl, 2013_HF-RTMS_CM_N_SANS_1 4.5538
## quan, 2015_HF-RTMS_CM_N_PANSS_1 0.7792
## quan, 2015_HF-RTMS_CM_N_SANS_1 2.0632
## rabany, 2014_DTMS_CM_N_PANSS_1 1.2658
## rabany, 2014_DTMS_CM_N_SANS_1 5.4064
## rosa, 2007_LF-RTMS_10-20EEG_N_PANSS_1 1.7696
## saba, 2006_LF-RTMS_CM_N_PANSS_1 2.0245
## singh, 2020_HF-RTMS_CM_N_PANSS_1 1.4935
## singh, 2020_HF-RTMS_CM_N_SANS_1 5.5172
## smith, 2015_TDCS_10-20EEG_N_PANSS_1 2.0675
## smith, 2020_TDCS_10-20EEG_N_PANSS_1 1.2865
## su, 2023b_HF-RTMS_NEURONAV_N_PANSS_1 2.1384
## su, 2022_HF-RTMS_NEURONAV_N_PANSS_1 2.0019
## tikka, 2017_CTBS_NEURONAV_N_PANSS_1 2.0779
## tyagi, 2022_CTBS_10-20EEG_N_PANSS_1 1.0987
## valiengo, 2020_TDCS_10-20EEG_N_PANSS_1 0.6836
## vergallito, 2024_ITBS_10-20EEG_N_PANSS_1 5.2587
## vergallito, 2024_ITBS_10-20EEG_N_BNSS_1 7.8701
## walther-lft, 2024_UNKNOWN_STANDARD_N_PANSS_1 0.3482
## walther-lft, 2024_UNKNOWN_STANDARD_N_BNSS_1 0.7000
## walther-itbs, 2024_ITBS_CM_N_PANSS_1 0.3334
## walther-itbs, 2024_ITBS_CM_N_BNSS_1 0.6720
## wang, 2020_ITBS_NEURONAV_N_PANSS_1 0.9863
## wang, 2020_ITBS_NEURONAV_N_SANS_1 2.5127
## wang, 2022_ITBS_NEURONAV_N_PANSS_1 0.8893
## wang, 2022_ITBS_NEURONAV_N_SANS_1 2.5920
## weickert, 2019_TDCS_10-20EEG_N_PANSS_1 1.7952
## wen, 2021_HF-RTMS_CM_N_PANSS_1 0.8401
## wobrock, 2015_HF-RTMS_10-20EEG_N_PANSS_1 0.7602
## xie, 2023-a_LF-RTMS_10-20EEG_N_PANSS_1 0.8569
## xiu-10hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 1.1028
## xiu-20hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 1.5069
## xu, 2023_HD-TDCS_10-20EEG_N_PANSS_1 1.3468
## yuanjun, 2024_LF-RTMS_10-20EEG_N_PANSS_1 0.8569
## zhang, 2022_TACS_10-20EEG_N_PANSS_1 1.6392
## zhao-tbs, 2014_ITBS_10-20EEG_N_PANSS_1 1.3317
## zhao-tbs, 2014_ITBS_10-20EEG_N_SANS_1 2.3221
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 1.4214
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 2.3276
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 1.1441
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 2.1682
## zhou, 2024_HF-RTMS_10-20EEG_N_PANSS_1 0.8641
## zhou, 2023_TDCS_10-20EEG_N_SANS_1 4.2033
## zhu, 2021_ITBS_CM_N_PANSS_1 1.5094
## zhuo, 2019_HF-RTMS_10-20EEG_N_PANSS_1 0.7287
## zhuo, 2019_HF-RTMS_10-20EEG_N_SANS_1 2.3424
##
## Number of treatment arms (by study):
## narms
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANSS_1 2
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANAS_1 2
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANSS_1 2
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANAS_1 2
## barr, 2012_HF-RTMS_NEURONAV_N_PANSS_1 2
## barr, 2012_HF-RTMS_NEURONAV_N_SANS_1 2
## basavaraju, 2021_ITBS_NEURONAV_N_SANS_1 2
## battion, 2021_ITBS_CM_N_SANS_1 2
## bodén, 2021_ITBS_CM_N_CAIN_1 2
## bose, 2018_TDCS_10-20EEG_N_SANS_1 2
## chang-a, 2021_TACS_10-20EEG_N_PANSS_1 2
## chang-a, 2021_TACS_10-20EEG_N_SANS_1 2
## chauhan, 2021_ITBS_10-20EEG_N_PANSS_1 2
## de jesus, 2011_LF-RTMS_10-20EEG_N_BPRS_1 2
## dharani, 2021_HD-TDCS_10-10EEG_N_PANSS_1 2
## dharani, 2021_HD-TDCS_10-10EEG_N_SANS_1 2
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_SANS_1 2
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_PANSS_1 2
## du, 2024_HF-RTMS_NEURONAV_N_BPRS_1 2
## du, 2022_HF-RTMS_10-20EEG_N_SANS_1 2
## du, 2022_HF-RTMS_10-20EEG_N_PANSS_1 2
## fitzerald, 2008_LF-RTMS_CM_N_SANS_1 2
## fitzerald, 2008_LF-RTMS_CM_N_PANSS_1 2
## fitzerald-l, 2014_TDCS_10-20EEG_N_PANSS_1 2
## fitzerald-l, 2014_TDCS_10-20EEG_N_SANS_1 2
## fitzerald-bi, 2014_TDCS_10-20EEG_N_PANSS_1 2
## fitzerald-bi, 2014_TDCS_10-20EEG_N_SANS_1 2
## frohlich, 2016_TDCS_10-20EEG_N_PANSS_1 2
## gao, 2024_ITBS_10-20EEG_N_PANSS_1 2
## gao, 2024_ITBS_10-20EEG_N_SANS_1 2
## garg, 2016_DTMS_CM_N_PANSS_1 2
## gomes, 2018_TDCS_10-20EEG_N_PANSS-N_1 2
## guan, 2020_HF-RTMS_NEURONAV_N_PANSS-N_1 2
## guleken, 2020_HF-RTMS_CM_N_SANS_1 2
## holi, 2004_HF-RTMS_10-20EEG_N_PANSS_1 2
## hu, 2024_LF-RTMS_10-20EEG_N_PANSS_1 2
## hu, 2023_LF-RTMS_10-10EEG_N_PANSS_1 2
## huang, 2016_HF-RTMS_CM_N_PANSS_1 2
## jeon, 2018_TDCS_10-20EEG_N_PANSS_1 2
## jin, 2023_ITBS_NA_N_PANSS_1 2
## kang, 2024_CTBS_CM_N_PANSS_1 2
## klein, 1999_LF-RTMS_CM_N_PANSS_1 2
## koops, 2018_TDCS_10-20EEG_N_PANSS_1 2
## kos, 2024_TDCS_10-20EEG_N_SANS_1 2
## kos, 2024_TDCS_10-20EEG_N_AES_1 2
## liu, 2024_HF-RTMS_NA_N_PANSS_1 2
## lyu, 2024_TDCS_10-20EEG_N_PANSS_1 2
## lyu, 2024_TDCS_10-20EEG_N_SANS_1 2
## marquardt, 2022_TDCS_10-20EEG_N_PANSS_1 2
## mcintosh, 2004_LF-RTMS_10-20EEG_N_PANSS_1 2
## mellin-tacs, 2018_TACS_10-20EEG_N_PANSS-N_1 2
## mellin-tdcs, 2018_TDCS_10-20EEG_N_PANSS_1 2
## moeller, 2022_DTMS_CM_N_PANSS_1 2
## mondino, 2015_TDCS_10-20EG_N_PANSS_1 2
## novak, 2006_HF-RTMS_CM_N_PANSS_1 2
## paillere-martinot, 2017_LF-RTMS_NEURONAV_N_SANS_1 2
## palm, 2016_TDCS_10-20EEG_N_PANSS_1 2
## palm, 2016_TDCS_10-20EEG_N_SANS_1 2
## prikryl, 2007_HF-RTMS_CM_N_PANSS_1 2
## prikryl, 2007_HF-RTMS_CM_N_SANS_1 2
## prikryl, 2012_HF-RTMS_CM_N_PANSS_1 2
## prikryl, 2014_HF-RTMS_CM_N_PANSS_1 2
## prikryl, 2013_HF-RTMS_CM_N_SANS_1 2
## quan, 2015_HF-RTMS_CM_N_PANSS_1 2
## quan, 2015_HF-RTMS_CM_N_SANS_1 2
## rabany, 2014_DTMS_CM_N_PANSS_1 2
## rabany, 2014_DTMS_CM_N_SANS_1 2
## rosa, 2007_LF-RTMS_10-20EEG_N_PANSS_1 2
## saba, 2006_LF-RTMS_CM_N_PANSS_1 2
## singh, 2020_HF-RTMS_CM_N_PANSS_1 2
## singh, 2020_HF-RTMS_CM_N_SANS_1 2
## smith, 2015_TDCS_10-20EEG_N_PANSS_1 2
## smith, 2020_TDCS_10-20EEG_N_PANSS_1 2
## su, 2023b_HF-RTMS_NEURONAV_N_PANSS_1 2
## su, 2022_HF-RTMS_NEURONAV_N_PANSS_1 2
## tikka, 2017_CTBS_NEURONAV_N_PANSS_1 2
## tyagi, 2022_CTBS_10-20EEG_N_PANSS_1 2
## valiengo, 2020_TDCS_10-20EEG_N_PANSS_1 2
## vergallito, 2024_ITBS_10-20EEG_N_PANSS_1 2
## vergallito, 2024_ITBS_10-20EEG_N_BNSS_1 2
## walther-lft, 2024_UNKNOWN_STANDARD_N_PANSS_1 2
## walther-lft, 2024_UNKNOWN_STANDARD_N_BNSS_1 2
## walther-itbs, 2024_ITBS_CM_N_PANSS_1 2
## walther-itbs, 2024_ITBS_CM_N_BNSS_1 2
## wang, 2020_ITBS_NEURONAV_N_PANSS_1 2
## wang, 2020_ITBS_NEURONAV_N_SANS_1 2
## wang, 2022_ITBS_NEURONAV_N_PANSS_1 2
## wang, 2022_ITBS_NEURONAV_N_SANS_1 2
## weickert, 2019_TDCS_10-20EEG_N_PANSS_1 2
## wen, 2021_HF-RTMS_CM_N_PANSS_1 2
## wobrock, 2015_HF-RTMS_10-20EEG_N_PANSS_1 2
## xie, 2023-a_LF-RTMS_10-20EEG_N_PANSS_1 2
## xiu-10hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 2
## xiu-20hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 2
## xu, 2023_HD-TDCS_10-20EEG_N_PANSS_1 2
## yuanjun, 2024_LF-RTMS_10-20EEG_N_PANSS_1 2
## zhang, 2022_TACS_10-20EEG_N_PANSS_1 2
## zhao-tbs, 2014_ITBS_10-20EEG_N_PANSS_1 2
## zhao-tbs, 2014_ITBS_10-20EEG_N_SANS_1 2
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 2
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 2
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 2
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 2
## zhou, 2024_HF-RTMS_10-20EEG_N_PANSS_1 2
## zhou, 2023_TDCS_10-20EEG_N_SANS_1 2
## zhu, 2021_ITBS_CM_N_PANSS_1 2
## zhuo, 2019_HF-RTMS_10-20EEG_N_PANSS_1 2
## zhuo, 2019_HF-RTMS_10-20EEG_N_SANS_1 2
##
## Results (random effects model):
##
## treat1
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANAS_1 LF-RTMS_10-20EEG
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANAS_1 LF-RTMS_10-20EEG
## barr, 2012_HF-RTMS_NEURONAV_N_PANSS_1 HF-RTMS_NEURONAV
## barr, 2012_HF-RTMS_NEURONAV_N_SANS_1 HF-RTMS_NEURONAV
## basavaraju, 2021_ITBS_NEURONAV_N_SANS_1 ITBS_NEURONAV
## battion, 2021_ITBS_CM_N_SANS_1 ITBS_CM
## bodén, 2021_ITBS_CM_N_CAIN_1 ITBS_CM
## bose, 2018_TDCS_10-20EEG_N_SANS_1 SHAM
## chang-a, 2021_TACS_10-20EEG_N_PANSS_1 SHAM
## chang-a, 2021_TACS_10-20EEG_N_SANS_1 SHAM
## chauhan, 2021_ITBS_10-20EEG_N_PANSS_1 ITBS_10-20EEG
## de jesus, 2011_LF-RTMS_10-20EEG_N_BPRS_1 LF-RTMS_10-20EEG
## dharani, 2021_HD-TDCS_10-10EEG_N_PANSS_1 HD-TDCS_10-10EEG
## dharani, 2021_HD-TDCS_10-10EEG_N_SANS_1 HD-TDCS_10-10EEG
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_SANS_1 LF-RTMS_10-20EEG
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## du, 2024_HF-RTMS_NEURONAV_N_BPRS_1 HF-RTMS_NEURONAV
## du, 2022_HF-RTMS_10-20EEG_N_SANS_1 HF-RTMS_10-20EEG
## du, 2022_HF-RTMS_10-20EEG_N_PANSS_1 HF-RTMS_10-20EEG
## fitzerald, 2008_LF-RTMS_CM_N_SANS_1 LF-RTMS_CM
## fitzerald, 2008_LF-RTMS_CM_N_PANSS_1 LF-RTMS_CM
## fitzerald-l, 2014_TDCS_10-20EEG_N_PANSS_1 SHAM
## fitzerald-l, 2014_TDCS_10-20EEG_N_SANS_1 SHAM
## fitzerald-bi, 2014_TDCS_10-20EEG_N_PANSS_1 SHAM
## fitzerald-bi, 2014_TDCS_10-20EEG_N_SANS_1 SHAM
## frohlich, 2016_TDCS_10-20EEG_N_PANSS_1 SHAM
## gao, 2024_ITBS_10-20EEG_N_PANSS_1 ITBS_10-20EEG
## gao, 2024_ITBS_10-20EEG_N_SANS_1 ITBS_10-20EEG
## garg, 2016_DTMS_CM_N_PANSS_1 DTMS_CM
## gomes, 2018_TDCS_10-20EEG_N_PANSS-N_1 SHAM
## guan, 2020_HF-RTMS_NEURONAV_N_PANSS-N_1 HF-RTMS_NEURONAV
## guleken, 2020_HF-RTMS_CM_N_SANS_1 HF-RTMS_CM
## holi, 2004_HF-RTMS_10-20EEG_N_PANSS_1 HF-RTMS_10-20EEG
## hu, 2024_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## hu, 2023_LF-RTMS_10-10EEG_N_PANSS_1 LF-RTMS_10-10EEG
## huang, 2016_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## jeon, 2018_TDCS_10-20EEG_N_PANSS_1 SHAM
## jin, 2023_ITBS_NA_N_PANSS_1 ITBS_NA
## kang, 2024_CTBS_CM_N_PANSS_1 CTBS_CM
## klein, 1999_LF-RTMS_CM_N_PANSS_1 LF-RTMS_CM
## koops, 2018_TDCS_10-20EEG_N_PANSS_1 SHAM
## kos, 2024_TDCS_10-20EEG_N_SANS_1 SHAM
## kos, 2024_TDCS_10-20EEG_N_AES_1 SHAM
## liu, 2024_HF-RTMS_NA_N_PANSS_1 HF-RTMS_NA
## lyu, 2024_TDCS_10-20EEG_N_PANSS_1 SHAM
## lyu, 2024_TDCS_10-20EEG_N_SANS_1 SHAM
## marquardt, 2022_TDCS_10-20EEG_N_PANSS_1 SHAM
## mcintosh, 2004_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## mellin-tacs, 2018_TACS_10-20EEG_N_PANSS-N_1 SHAM
## mellin-tdcs, 2018_TDCS_10-20EEG_N_PANSS_1 SHAM
## moeller, 2022_DTMS_CM_N_PANSS_1 DTMS_CM
## mondino, 2015_TDCS_10-20EG_N_PANSS_1 SHAM
## novak, 2006_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## paillere-martinot, 2017_LF-RTMS_NEURONAV_N_SANS_1 LF-RTMS_NEURONAV
## palm, 2016_TDCS_10-20EEG_N_PANSS_1 SHAM
## palm, 2016_TDCS_10-20EEG_N_SANS_1 SHAM
## prikryl, 2007_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## prikryl, 2007_HF-RTMS_CM_N_SANS_1 HF-RTMS_CM
## prikryl, 2012_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## prikryl, 2014_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## prikryl, 2013_HF-RTMS_CM_N_SANS_1 HF-RTMS_CM
## quan, 2015_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## quan, 2015_HF-RTMS_CM_N_SANS_1 HF-RTMS_CM
## rabany, 2014_DTMS_CM_N_PANSS_1 DTMS_CM
## rabany, 2014_DTMS_CM_N_SANS_1 DTMS_CM
## rosa, 2007_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## saba, 2006_LF-RTMS_CM_N_PANSS_1 LF-RTMS_CM
## singh, 2020_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## singh, 2020_HF-RTMS_CM_N_SANS_1 HF-RTMS_CM
## smith, 2015_TDCS_10-20EEG_N_PANSS_1 SHAM
## smith, 2020_TDCS_10-20EEG_N_PANSS_1 SHAM
## su, 2023b_HF-RTMS_NEURONAV_N_PANSS_1 HF-RTMS_NEURONAV
## su, 2022_HF-RTMS_NEURONAV_N_PANSS_1 HF-RTMS_NEURONAV
## tikka, 2017_CTBS_NEURONAV_N_PANSS_1 CTBS_NEURONAV
## tyagi, 2022_CTBS_10-20EEG_N_PANSS_1 CTBS_10-20EEG
## valiengo, 2020_TDCS_10-20EEG_N_PANSS_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_N_PANSS_1 ITBS_10-20EEG
## vergallito, 2024_ITBS_10-20EEG_N_BNSS_1 ITBS_10-20EEG
## walther-lft, 2024_UNKNOWN_STANDARD_N_PANSS_1 SHAM
## walther-lft, 2024_UNKNOWN_STANDARD_N_BNSS_1 SHAM
## walther-itbs, 2024_ITBS_CM_N_PANSS_1 ITBS_CM
## walther-itbs, 2024_ITBS_CM_N_BNSS_1 ITBS_CM
## wang, 2020_ITBS_NEURONAV_N_PANSS_1 ITBS_NEURONAV
## wang, 2020_ITBS_NEURONAV_N_SANS_1 ITBS_NEURONAV
## wang, 2022_ITBS_NEURONAV_N_PANSS_1 ITBS_NEURONAV
## wang, 2022_ITBS_NEURONAV_N_SANS_1 ITBS_NEURONAV
## weickert, 2019_TDCS_10-20EEG_N_PANSS_1 SHAM
## wen, 2021_HF-RTMS_CM_N_PANSS_1 HF-RTMS_CM
## wobrock, 2015_HF-RTMS_10-20EEG_N_PANSS_1 HF-RTMS_10-20EEG
## xie, 2023-a_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## xiu-10hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 HF-RTMS_NEURONAV
## xiu-20hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 HF-RTMS_NEURONAV
## xu, 2023_HD-TDCS_10-20EEG_N_PANSS_1 HD-TDCS_10-20EEG
## yuanjun, 2024_LF-RTMS_10-20EEG_N_PANSS_1 LF-RTMS_10-20EEG
## zhang, 2022_TACS_10-20EEG_N_PANSS_1 SHAM
## zhao-tbs, 2014_ITBS_10-20EEG_N_PANSS_1 ITBS_10-20EEG
## zhao-tbs, 2014_ITBS_10-20EEG_N_SANS_1 ITBS_10-20EEG
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 HF-RTMS_10-20EEG
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 HF-RTMS_10-20EEG
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 HF-RTMS_10-20EEG
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 HF-RTMS_10-20EEG
## zhou, 2024_HF-RTMS_10-20EEG_N_PANSS_1 HF-RTMS_10-20EEG
## zhou, 2023_TDCS_10-20EEG_N_SANS_1 SHAM
## zhu, 2021_ITBS_CM_N_PANSS_1 ITBS_CM
## zhuo, 2019_HF-RTMS_10-20EEG_N_PANSS_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_N_SANS_1 HF-RTMS_10-20EEG
## treat2 MD
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANSS_1 SHAM 1.0443
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANAS_1 SHAM 1.0443
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANSS_1 SHAM 1.0443
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANAS_1 SHAM 1.0443
## barr, 2012_HF-RTMS_NEURONAV_N_PANSS_1 SHAM 0.1790
## barr, 2012_HF-RTMS_NEURONAV_N_SANS_1 SHAM 0.1790
## basavaraju, 2021_ITBS_NEURONAV_N_SANS_1 SHAM 4.8971
## battion, 2021_ITBS_CM_N_SANS_1 SHAM 0.4612
## bodén, 2021_ITBS_CM_N_CAIN_1 SHAM 0.4612
## bose, 2018_TDCS_10-20EEG_N_SANS_1 TDCS_10-20EEG -0.5283
## chang-a, 2021_TACS_10-20EEG_N_PANSS_1 TACS_10-20EEG -1.7375
## chang-a, 2021_TACS_10-20EEG_N_SANS_1 TACS_10-20EEG -1.7375
## chauhan, 2021_ITBS_10-20EEG_N_PANSS_1 SHAM 6.7628
## de jesus, 2011_LF-RTMS_10-20EEG_N_BPRS_1 SHAM 1.0443
## dharani, 2021_HD-TDCS_10-10EEG_N_PANSS_1 SHAM 3.6259
## dharani, 2021_HD-TDCS_10-10EEG_N_SANS_1 SHAM 3.6259
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_SANS_1 SHAM 1.0443
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_PANSS_1 SHAM 1.0443
## du, 2024_HF-RTMS_NEURONAV_N_BPRS_1 SHAM 0.1790
## du, 2022_HF-RTMS_10-20EEG_N_SANS_1 SHAM 5.0551
## du, 2022_HF-RTMS_10-20EEG_N_PANSS_1 SHAM 5.0551
## fitzerald, 2008_LF-RTMS_CM_N_SANS_1 SHAM 0.7985
## fitzerald, 2008_LF-RTMS_CM_N_PANSS_1 SHAM 0.7985
## fitzerald-l, 2014_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG -0.5283
## fitzerald-l, 2014_TDCS_10-20EEG_N_SANS_1 TDCS_10-20EEG -0.5283
## fitzerald-bi, 2014_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG -0.5283
## fitzerald-bi, 2014_TDCS_10-20EEG_N_SANS_1 TDCS_10-20EEG -0.5283
## frohlich, 2016_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG -0.5283
## gao, 2024_ITBS_10-20EEG_N_PANSS_1 SHAM 6.7628
## gao, 2024_ITBS_10-20EEG_N_SANS_1 SHAM 6.7628
## garg, 2016_DTMS_CM_N_PANSS_1 SHAM 2.1464
## gomes, 2018_TDCS_10-20EEG_N_PANSS-N_1 TDCS_10-20EEG -0.5283
## guan, 2020_HF-RTMS_NEURONAV_N_PANSS-N_1 SHAM 0.1790
## guleken, 2020_HF-RTMS_CM_N_SANS_1 SHAM 4.4831
## holi, 2004_HF-RTMS_10-20EEG_N_PANSS_1 SHAM 5.0551
## hu, 2024_LF-RTMS_10-20EEG_N_PANSS_1 SHAM 1.0443
## hu, 2023_LF-RTMS_10-10EEG_N_PANSS_1 SHAM 2.3100
## huang, 2016_HF-RTMS_CM_N_PANSS_1 SHAM 4.4831
## jeon, 2018_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG -0.5283
## jin, 2023_ITBS_NA_N_PANSS_1 SHAM 1.6000
## kang, 2024_CTBS_CM_N_PANSS_1 SHAM 0.0600
## klein, 1999_LF-RTMS_CM_N_PANSS_1 SHAM 0.7985
## koops, 2018_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG -0.5283
## kos, 2024_TDCS_10-20EEG_N_SANS_1 TDCS_10-20EEG -0.5283
## kos, 2024_TDCS_10-20EEG_N_AES_1 TDCS_10-20EEG -0.5283
## liu, 2024_HF-RTMS_NA_N_PANSS_1 SHAM 1.5000
## lyu, 2024_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG -0.5283
## lyu, 2024_TDCS_10-20EEG_N_SANS_1 TDCS_10-20EEG -0.5283
## marquardt, 2022_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG -0.5283
## mcintosh, 2004_LF-RTMS_10-20EEG_N_PANSS_1 SHAM 1.0443
## mellin-tacs, 2018_TACS_10-20EEG_N_PANSS-N_1 TACS_10-20EEG -1.7375
## mellin-tdcs, 2018_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG -0.5283
## moeller, 2022_DTMS_CM_N_PANSS_1 SHAM 2.1464
## mondino, 2015_TDCS_10-20EG_N_PANSS_1 TDCS_10-20EG -3.0000
## novak, 2006_HF-RTMS_CM_N_PANSS_1 SHAM 4.4831
## paillere-martinot, 2017_LF-RTMS_NEURONAV_N_SANS_1 SHAM -2.6300
## palm, 2016_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG -0.5283
## palm, 2016_TDCS_10-20EEG_N_SANS_1 TDCS_10-20EEG -0.5283
## prikryl, 2007_HF-RTMS_CM_N_PANSS_1 SHAM 4.4831
## prikryl, 2007_HF-RTMS_CM_N_SANS_1 SHAM 4.4831
## prikryl, 2012_HF-RTMS_CM_N_PANSS_1 SHAM 4.4831
## prikryl, 2014_HF-RTMS_CM_N_PANSS_1 SHAM 4.4831
## prikryl, 2013_HF-RTMS_CM_N_SANS_1 SHAM 4.4831
## quan, 2015_HF-RTMS_CM_N_PANSS_1 SHAM 4.4831
## quan, 2015_HF-RTMS_CM_N_SANS_1 SHAM 4.4831
## rabany, 2014_DTMS_CM_N_PANSS_1 SHAM 2.1464
## rabany, 2014_DTMS_CM_N_SANS_1 SHAM 2.1464
## rosa, 2007_LF-RTMS_10-20EEG_N_PANSS_1 SHAM 1.0443
## saba, 2006_LF-RTMS_CM_N_PANSS_1 SHAM 0.7985
## singh, 2020_HF-RTMS_CM_N_PANSS_1 SHAM 4.4831
## singh, 2020_HF-RTMS_CM_N_SANS_1 SHAM 4.4831
## smith, 2015_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG -0.5283
## smith, 2020_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG -0.5283
## su, 2023b_HF-RTMS_NEURONAV_N_PANSS_1 SHAM 0.1790
## su, 2022_HF-RTMS_NEURONAV_N_PANSS_1 SHAM 0.1790
## tikka, 2017_CTBS_NEURONAV_N_PANSS_1 SHAM 1.0200
## tyagi, 2022_CTBS_10-20EEG_N_PANSS_1 SHAM 0.3200
## valiengo, 2020_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG -0.5283
## vergallito, 2024_ITBS_10-20EEG_N_PANSS_1 SHAM 6.7628
## vergallito, 2024_ITBS_10-20EEG_N_BNSS_1 SHAM 6.7628
## walther-lft, 2024_UNKNOWN_STANDARD_N_PANSS_1 UNKNOWN_STANDARD -0.5770
## walther-lft, 2024_UNKNOWN_STANDARD_N_BNSS_1 UNKNOWN_STANDARD -0.5770
## walther-itbs, 2024_ITBS_CM_N_PANSS_1 SHAM 0.4612
## walther-itbs, 2024_ITBS_CM_N_BNSS_1 SHAM 0.4612
## wang, 2020_ITBS_NEURONAV_N_PANSS_1 SHAM 4.8971
## wang, 2020_ITBS_NEURONAV_N_SANS_1 SHAM 4.8971
## wang, 2022_ITBS_NEURONAV_N_PANSS_1 SHAM 4.8971
## wang, 2022_ITBS_NEURONAV_N_SANS_1 SHAM 4.8971
## weickert, 2019_TDCS_10-20EEG_N_PANSS_1 TDCS_10-20EEG -0.5283
## wen, 2021_HF-RTMS_CM_N_PANSS_1 SHAM 4.4831
## wobrock, 2015_HF-RTMS_10-20EEG_N_PANSS_1 SHAM 5.0551
## xie, 2023-a_LF-RTMS_10-20EEG_N_PANSS_1 SHAM 1.0443
## xiu-10hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 SHAM 0.1790
## xiu-20hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 SHAM 0.1790
## xu, 2023_HD-TDCS_10-20EEG_N_PANSS_1 SHAM 0.3200
## yuanjun, 2024_LF-RTMS_10-20EEG_N_PANSS_1 SHAM 1.0443
## zhang, 2022_TACS_10-20EEG_N_PANSS_1 TACS_10-20EEG -1.7375
## zhao-tbs, 2014_ITBS_10-20EEG_N_PANSS_1 SHAM 6.7628
## zhao-tbs, 2014_ITBS_10-20EEG_N_SANS_1 SHAM 6.7628
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 SHAM 5.0551
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 SHAM 5.0551
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 SHAM 5.0551
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 SHAM 5.0551
## zhou, 2024_HF-RTMS_10-20EEG_N_PANSS_1 SHAM 5.0551
## zhou, 2023_TDCS_10-20EEG_N_SANS_1 TDCS_10-20EEG -0.5283
## zhu, 2021_ITBS_CM_N_PANSS_1 SHAM 0.4612
## zhuo, 2019_HF-RTMS_10-20EEG_N_PANSS_1 SHAM 5.0551
## zhuo, 2019_HF-RTMS_10-20EEG_N_SANS_1 SHAM 5.0551
## 95%-CI
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANSS_1 [ -0.8934; 2.9819]
## bais, 2014 - l_LF-RTMS_10-20EEG_N_PANAS_1 [ -0.8934; 2.9819]
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANSS_1 [ -0.8934; 2.9819]
## bais, 2014 - bi_LF-RTMS_10-20EEG_N_PANAS_1 [ -0.8934; 2.9819]
## barr, 2012_HF-RTMS_NEURONAV_N_PANSS_1 [ -2.2848; 2.6428]
## barr, 2012_HF-RTMS_NEURONAV_N_SANS_1 [ -2.2848; 2.6428]
## basavaraju, 2021_ITBS_NEURONAV_N_SANS_1 [ 1.8347; 7.9596]
## battion, 2021_ITBS_CM_N_SANS_1 [ -2.6981; 3.6205]
## bodén, 2021_ITBS_CM_N_CAIN_1 [ -2.6981; 3.6205]
## bose, 2018_TDCS_10-20EEG_N_SANS_1 [ -2.1001; 1.0436]
## chang-a, 2021_TACS_10-20EEG_N_PANSS_1 [ -5.1115; 1.6366]
## chang-a, 2021_TACS_10-20EEG_N_SANS_1 [ -5.1115; 1.6366]
## chauhan, 2021_ITBS_10-20EEG_N_PANSS_1 [ 4.0955; 9.4301]
## de jesus, 2011_LF-RTMS_10-20EEG_N_BPRS_1 [ -0.8934; 2.9819]
## dharani, 2021_HD-TDCS_10-10EEG_N_PANSS_1 [ -3.1965; 10.4484]
## dharani, 2021_HD-TDCS_10-10EEG_N_SANS_1 [ -3.1965; 10.4484]
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_SANS_1 [ -0.8934; 2.9819]
## dlabac-de lange, 2015_LF-RTMS_10-20EEG_N_PANSS_1 [ -0.8934; 2.9819]
## du, 2024_HF-RTMS_NEURONAV_N_BPRS_1 [ -2.2848; 2.6428]
## du, 2022_HF-RTMS_10-20EEG_N_SANS_1 [ 3.0062; 7.1040]
## du, 2022_HF-RTMS_10-20EEG_N_PANSS_1 [ 3.0062; 7.1040]
## fitzerald, 2008_LF-RTMS_CM_N_SANS_1 [ -2.7558; 4.3529]
## fitzerald, 2008_LF-RTMS_CM_N_PANSS_1 [ -2.7558; 4.3529]
## fitzerald-l, 2014_TDCS_10-20EEG_N_PANSS_1 [ -2.1001; 1.0436]
## fitzerald-l, 2014_TDCS_10-20EEG_N_SANS_1 [ -2.1001; 1.0436]
## fitzerald-bi, 2014_TDCS_10-20EEG_N_PANSS_1 [ -2.1001; 1.0436]
## fitzerald-bi, 2014_TDCS_10-20EEG_N_SANS_1 [ -2.1001; 1.0436]
## frohlich, 2016_TDCS_10-20EEG_N_PANSS_1 [ -2.1001; 1.0436]
## gao, 2024_ITBS_10-20EEG_N_PANSS_1 [ 4.0955; 9.4301]
## gao, 2024_ITBS_10-20EEG_N_SANS_1 [ 4.0955; 9.4301]
## garg, 2016_DTMS_CM_N_PANSS_1 [ -1.5556; 5.8484]
## gomes, 2018_TDCS_10-20EEG_N_PANSS-N_1 [ -2.1001; 1.0436]
## guan, 2020_HF-RTMS_NEURONAV_N_PANSS-N_1 [ -2.2848; 2.6428]
## guleken, 2020_HF-RTMS_CM_N_SANS_1 [ 2.4803; 6.4858]
## holi, 2004_HF-RTMS_10-20EEG_N_PANSS_1 [ 3.0062; 7.1040]
## hu, 2024_LF-RTMS_10-20EEG_N_PANSS_1 [ -0.8934; 2.9819]
## hu, 2023_LF-RTMS_10-10EEG_N_PANSS_1 [ -3.7085; 8.3285]
## huang, 2016_HF-RTMS_CM_N_PANSS_1 [ 2.4803; 6.4858]
## jeon, 2018_TDCS_10-20EEG_N_PANSS_1 [ -2.1001; 1.0436]
## jin, 2023_ITBS_NA_N_PANSS_1 [ -4.2373; 7.4373]
## kang, 2024_CTBS_CM_N_PANSS_1 [ -6.5196; 6.6396]
## klein, 1999_LF-RTMS_CM_N_PANSS_1 [ -2.7558; 4.3529]
## koops, 2018_TDCS_10-20EEG_N_PANSS_1 [ -2.1001; 1.0436]
## kos, 2024_TDCS_10-20EEG_N_SANS_1 [ -2.1001; 1.0436]
## kos, 2024_TDCS_10-20EEG_N_AES_1 [ -2.1001; 1.0436]
## liu, 2024_HF-RTMS_NA_N_PANSS_1 [ -4.8672; 7.8672]
## lyu, 2024_TDCS_10-20EEG_N_PANSS_1 [ -2.1001; 1.0436]
## lyu, 2024_TDCS_10-20EEG_N_SANS_1 [ -2.1001; 1.0436]
## marquardt, 2022_TDCS_10-20EEG_N_PANSS_1 [ -2.1001; 1.0436]
## mcintosh, 2004_LF-RTMS_10-20EEG_N_PANSS_1 [ -0.8934; 2.9819]
## mellin-tacs, 2018_TACS_10-20EEG_N_PANSS-N_1 [ -5.1115; 1.6366]
## mellin-tdcs, 2018_TDCS_10-20EEG_N_PANSS_1 [ -2.1001; 1.0436]
## moeller, 2022_DTMS_CM_N_PANSS_1 [ -1.5556; 5.8484]
## mondino, 2015_TDCS_10-20EG_N_PANSS_1 [ -9.7718; 3.7718]
## novak, 2006_HF-RTMS_CM_N_PANSS_1 [ 2.4803; 6.4858]
## paillere-martinot, 2017_LF-RTMS_NEURONAV_N_SANS_1 [-19.5597; 14.2997]
## palm, 2016_TDCS_10-20EEG_N_PANSS_1 [ -2.1001; 1.0436]
## palm, 2016_TDCS_10-20EEG_N_SANS_1 [ -2.1001; 1.0436]
## prikryl, 2007_HF-RTMS_CM_N_PANSS_1 [ 2.4803; 6.4858]
## prikryl, 2007_HF-RTMS_CM_N_SANS_1 [ 2.4803; 6.4858]
## prikryl, 2012_HF-RTMS_CM_N_PANSS_1 [ 2.4803; 6.4858]
## prikryl, 2014_HF-RTMS_CM_N_PANSS_1 [ 2.4803; 6.4858]
## prikryl, 2013_HF-RTMS_CM_N_SANS_1 [ 2.4803; 6.4858]
## quan, 2015_HF-RTMS_CM_N_PANSS_1 [ 2.4803; 6.4858]
## quan, 2015_HF-RTMS_CM_N_SANS_1 [ 2.4803; 6.4858]
## rabany, 2014_DTMS_CM_N_PANSS_1 [ -1.5556; 5.8484]
## rabany, 2014_DTMS_CM_N_SANS_1 [ -1.5556; 5.8484]
## rosa, 2007_LF-RTMS_10-20EEG_N_PANSS_1 [ -0.8934; 2.9819]
## saba, 2006_LF-RTMS_CM_N_PANSS_1 [ -2.7558; 4.3529]
## singh, 2020_HF-RTMS_CM_N_PANSS_1 [ 2.4803; 6.4858]
## singh, 2020_HF-RTMS_CM_N_SANS_1 [ 2.4803; 6.4858]
## smith, 2015_TDCS_10-20EEG_N_PANSS_1 [ -2.1001; 1.0436]
## smith, 2020_TDCS_10-20EEG_N_PANSS_1 [ -2.1001; 1.0436]
## su, 2023b_HF-RTMS_NEURONAV_N_PANSS_1 [ -2.2848; 2.6428]
## su, 2022_HF-RTMS_NEURONAV_N_PANSS_1 [ -2.2848; 2.6428]
## tikka, 2017_CTBS_NEURONAV_N_PANSS_1 [ -6.0039; 8.0439]
## tyagi, 2022_CTBS_10-20EEG_N_PANSS_1 [ -5.7944; 6.4344]
## valiengo, 2020_TDCS_10-20EEG_N_PANSS_1 [ -2.1001; 1.0436]
## vergallito, 2024_ITBS_10-20EEG_N_PANSS_1 [ 4.0955; 9.4301]
## vergallito, 2024_ITBS_10-20EEG_N_BNSS_1 [ 4.0955; 9.4301]
## walther-lft, 2024_UNKNOWN_STANDARD_N_PANSS_1 [ -4.6946; 3.5405]
## walther-lft, 2024_UNKNOWN_STANDARD_N_BNSS_1 [ -4.6946; 3.5405]
## walther-itbs, 2024_ITBS_CM_N_PANSS_1 [ -2.6981; 3.6205]
## walther-itbs, 2024_ITBS_CM_N_BNSS_1 [ -2.6981; 3.6205]
## wang, 2020_ITBS_NEURONAV_N_PANSS_1 [ 1.8347; 7.9596]
## wang, 2020_ITBS_NEURONAV_N_SANS_1 [ 1.8347; 7.9596]
## wang, 2022_ITBS_NEURONAV_N_PANSS_1 [ 1.8347; 7.9596]
## wang, 2022_ITBS_NEURONAV_N_SANS_1 [ 1.8347; 7.9596]
## weickert, 2019_TDCS_10-20EEG_N_PANSS_1 [ -2.1001; 1.0436]
## wen, 2021_HF-RTMS_CM_N_PANSS_1 [ 2.4803; 6.4858]
## wobrock, 2015_HF-RTMS_10-20EEG_N_PANSS_1 [ 3.0062; 7.1040]
## xie, 2023-a_LF-RTMS_10-20EEG_N_PANSS_1 [ -0.8934; 2.9819]
## xiu-10hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 [ -2.2848; 2.6428]
## xiu-20hz, 2020_HF-RTMS_NEURONAV_N_PANSS_1 [ -2.2848; 2.6428]
## xu, 2023_HD-TDCS_10-20EEG_N_PANSS_1 [ -5.9821; 6.6221]
## yuanjun, 2024_LF-RTMS_10-20EEG_N_PANSS_1 [ -0.8934; 2.9819]
## zhang, 2022_TACS_10-20EEG_N_PANSS_1 [ -5.1115; 1.6366]
## zhao-tbs, 2014_ITBS_10-20EEG_N_PANSS_1 [ 4.0955; 9.4301]
## zhao-tbs, 2014_ITBS_10-20EEG_N_SANS_1 [ 4.0955; 9.4301]
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 [ 3.0062; 7.1040]
## zhao-20hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 [ 3.0062; 7.1040]
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_PANSS_1 [ 3.0062; 7.1040]
## zhao-10hz, 2014_HF-RTMS_10-20EEG_N_SANS_1 [ 3.0062; 7.1040]
## zhou, 2024_HF-RTMS_10-20EEG_N_PANSS_1 [ 3.0062; 7.1040]
## zhou, 2023_TDCS_10-20EEG_N_SANS_1 [ -2.1001; 1.0436]
## zhu, 2021_ITBS_CM_N_PANSS_1 [ -2.6981; 3.6205]
## zhuo, 2019_HF-RTMS_10-20EEG_N_PANSS_1 [ 3.0062; 7.1040]
## zhuo, 2019_HF-RTMS_10-20EEG_N_SANS_1 [ 3.0062; 7.1040]
##
## Number of studies: k = 108
## Number of pairwise comparisons: m = 108
## Number of treatments: n = 23
## Number of designs: d = 22
##
## Random effects model
##
## Treatment estimate (sm = 'MD', comparison: other treatments vs 'SHAM'):
## MD 95%-CI z p-value
## CTBS_10-20EEG 0.3200 [ -5.7944; 6.4344] 0.10 0.9183
## CTBS_CM 0.0600 [ -6.5196; 6.6396] 0.02 0.9857
## CTBS_NEURONAV 1.0200 [ -6.0039; 8.0439] 0.28 0.7759
## DTMS_CM 2.1464 [ -1.5556; 5.8484] 1.14 0.2558
## HD-TDCS_10-10EEG 3.6259 [ -3.1965; 10.4484] 1.04 0.2976
## HD-TDCS_10-20EEG 0.3200 [ -5.9821; 6.6221] 0.10 0.9207
## HF-RTMS_10-20EEG 5.0551 [ 3.0062; 7.1040] 4.84 < 0.0001
## HF-RTMS_CM 4.4831 [ 2.4803; 6.4858] 4.39 < 0.0001
## HF-RTMS_NA 1.5000 [ -4.8672; 7.8672] 0.46 0.6443
## HF-RTMS_NEURONAV 0.1790 [ -2.2848; 2.6428] 0.14 0.8868
## ITBS_10-20EEG 6.7628 [ 4.0955; 9.4301] 4.97 < 0.0001
## ITBS_CM 0.4612 [ -2.6981; 3.6205] 0.29 0.7748
## ITBS_NA 1.6000 [ -4.2373; 7.4373] 0.54 0.5911
## ITBS_NEURONAV 4.8971 [ 1.8347; 7.9596] 3.13 0.0017
## LF-RTMS_10-10EEG 2.3100 [ -3.7085; 8.3285] 0.75 0.4519
## LF-RTMS_10-20EEG 1.0443 [ -0.8934; 2.9819] 1.06 0.2908
## LF-RTMS_CM 0.7985 [ -2.7558; 4.3529] 0.44 0.6597
## LF-RTMS_NEURONAV -2.6300 [-19.5597; 14.2997] -0.30 0.7608
## SHAM . . . .
## TACS_10-20EEG 1.7375 [ -1.6366; 5.1115] 1.01 0.3128
## TDCS_10-20EEG 0.5283 [ -1.0436; 2.1001] 0.66 0.5101
## TDCS_10-20EG 3.0000 [ -3.7718; 9.7718] 0.87 0.3852
## UNKNOWN_STANDARD 0.5770 [ -3.5405; 4.6946] 0.27 0.7836
##
## Quantifying heterogeneity / inconsistency:
## tau^2 = 8.5252; tau = 2.9198; I^2 = 81.1% [77.2%; 84.4%]
##
## Tests of heterogeneity (within designs) and inconsistency (between designs):
## Q d.f. p-value
## Total 455.6 86 < 0.0001
## Within designs 455.6 86 < 0.0001
## Between designs 0.0 0 --
##
## Details of network meta-analysis methods:
## - Frequentist graph-theoretical approach
## - DerSimonian-Laird estimator for tau^2
## - Calculation of I^2 based on Q
##
## Forest Plot:
##
## Network Graph:
##
## League Table for Negative Symptoms :
## CTBS_10-20EEG CTBS_CM
## CTBS_10-20EEG CTBS_10-20EEG .
## CTBS_CM 0.26 [ -8.72; 9.24] CTBS_CM
## CTBS_NEURONAV -0.70 [-10.01; 8.61] -0.96 [-10.58; 8.66]
## DTMS_CM -1.83 [ -8.97; 5.32] -2.09 [ -9.64; 5.46]
## HD-TDCS_10-10EEG -3.31 [-12.47; 5.86] -3.57 [-13.04; 5.91]
## HD-TDCS_10-20EEG -0.00 [ -8.78; 8.78] -0.26 [ -9.37; 8.85]
## HF-RTMS_10-20EEG -4.74 [-11.18; 1.71] -5.00 [-11.89; 1.90]
## HF-RTMS_CM -4.16 [-10.60; 2.27] -4.42 [-11.30; 2.45]
## HF-RTMS_NA -1.18 [-10.01; 7.65] -1.44 [-10.60; 7.72]
## HF-RTMS_NEURONAV 0.14 [ -6.45; 6.73] -0.12 [ -7.14; 6.91]
## ITBS_10-20EEG -6.44 [-13.11; 0.23] -6.70 [-13.80; 0.40]
## ITBS_CM -0.14 [ -7.02; 6.74] -0.40 [ -7.70; 6.90]
## ITBS_NA -1.28 [ -9.73; 7.17] -1.54 [-10.34; 7.26]
## ITBS_NEURONAV -4.58 [-11.42; 2.26] -4.84 [-12.09; 2.42]
## LF-RTMS_10-10EEG -1.99 [-10.57; 6.59] -2.25 [-11.17; 6.67]
## LF-RTMS_10-20EEG -0.72 [ -7.14; 5.69] -0.98 [ -7.84; 5.87]
## LF-RTMS_CM -0.48 [ -7.55; 6.59] -0.74 [ -8.22; 6.74]
## LF-RTMS_NEURONAV 2.95 [-15.05; 20.95] 2.69 [-15.47; 20.85]
## SHAM 0.32 [ -5.79; 6.43] 0.06 [ -6.52; 6.64]
## TACS_10-20EEG -1.42 [ -8.40; 5.57] -1.68 [ -9.07; 5.72]
## TDCS_10-20EEG -0.21 [ -6.52; 6.10] -0.47 [ -7.23; 6.30]
## TDCS_10-20EG -2.68 [-11.80; 6.44] -2.94 [-12.38; 6.50]
## UNKNOWN_STANDARD -0.26 [ -7.63; 7.11] -0.52 [ -8.28; 7.24]
## CTBS_NEURONAV DTMS_CM
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV CTBS_NEURONAV .
## DTMS_CM -1.13 [ -9.07; 6.81] DTMS_CM
## HD-TDCS_10-10EEG -2.61 [-12.40; 7.19] -1.48 [ -9.24; 6.28]
## HD-TDCS_10-20EEG 0.70 [ -8.74; 10.14] 1.83 [ -5.48; 9.14]
## HF-RTMS_10-20EEG -4.04 [-11.35; 3.28] -2.91 [ -7.14; 1.32]
## HF-RTMS_CM -3.46 [-10.77; 3.84] -2.34 [ -6.55; 1.87]
## HF-RTMS_NA -0.48 [ -9.96; 9.00] 0.65 [ -6.72; 8.01]
## HF-RTMS_NEURONAV 0.84 [ -6.60; 8.28] 1.97 [ -2.48; 6.41]
## ITBS_10-20EEG -5.74 [-13.26; 1.77] -4.62 [ -9.18; -0.05]
## ITBS_CM 0.56 [ -7.14; 8.26] 1.69 [ -3.18; 6.55]
## ITBS_NA -0.58 [ -9.71; 8.55] 0.55 [ -6.37; 7.46]
## ITBS_NEURONAV -3.88 [-11.54; 3.79] -2.75 [ -7.56; 2.05]
## LF-RTMS_10-10EEG -1.29 [-10.54; 7.96] -0.16 [ -7.23; 6.90]
## LF-RTMS_10-20EEG -0.02 [ -7.31; 7.26] 1.10 [ -3.08; 5.28]
## LF-RTMS_CM 0.22 [ -7.65; 8.09] 1.35 [ -3.78; 6.48]
## LF-RTMS_NEURONAV 3.65 [-14.68; 21.98] 4.78 [-12.55; 22.11]
## SHAM 1.02 [ -6.00; 8.04] 2.15 [ -1.56; 5.85]
## TACS_10-20EEG -0.72 [ -8.51; 7.07] 0.41 [ -4.60; 5.42]
## TDCS_10-20EEG 0.49 [ -6.71; 7.69] 1.62 [ -2.40; 5.64]
## TDCS_10-20EG -1.98 [-11.74; 7.78] -0.85 [ -8.57; 6.86]
## UNKNOWN_STANDARD 0.44 [ -7.70; 8.58] 1.57 [ -3.97; 7.11]
## HD-TDCS_10-10EEG HD-TDCS_10-20EEG
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-10EEG HD-TDCS_10-10EEG .
## HD-TDCS_10-20EEG 3.31 [ -5.98; 12.59] HD-TDCS_10-20EEG
## HF-RTMS_10-20EEG -1.43 [ -8.55; 5.69] -4.74 [-11.36; 1.89]
## HF-RTMS_CM -0.86 [ -7.97; 6.25] -4.16 [-10.78; 2.45]
## HF-RTMS_NA 2.13 [ -7.21; 11.46] -1.18 [-10.14; 7.78]
## HF-RTMS_NEURONAV 3.45 [ -3.81; 10.70] 0.14 [ -6.63; 6.91]
## ITBS_10-20EEG -3.14 [-10.46; 4.19] -6.44 [-13.29; 0.40]
## ITBS_CM 3.16 [ -4.35; 10.68] -0.14 [ -7.19; 6.91]
## ITBS_NA 2.03 [ -6.95; 11.00] -1.28 [ -9.87; 7.31]
## ITBS_NEURONAV -1.27 [ -8.75; 6.21] -4.58 [-11.58; 2.43]
## LF-RTMS_10-10EEG 1.32 [ -7.78; 10.41] -1.99 [-10.70; 6.72]
## LF-RTMS_10-20EEG 2.58 [ -4.51; 9.67] -0.72 [ -7.32; 5.87]
## LF-RTMS_CM 2.83 [ -4.87; 10.52] -0.48 [ -7.71; 6.76]
## LF-RTMS_NEURONAV 6.26 [-12.00; 24.51] 2.95 [-15.11; 21.01]
## SHAM 3.63 [ -3.20; 10.45] 0.32 [ -5.98; 6.62]
## TACS_10-20EEG 1.89 [ -5.72; 9.50] -1.42 [ -8.57; 5.73]
## TDCS_10-20EEG 3.10 [ -3.90; 10.10] -0.21 [ -6.70; 6.29]
## TDCS_10-20EG 0.63 [ -8.99; 10.24] -2.68 [-11.93; 6.57]
## UNKNOWN_STANDARD 3.05 [ -4.92; 11.02] -0.26 [ -7.79; 7.27]
## HF-RTMS_10-20EEG HF-RTMS_CM
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-10EEG . .
## HD-TDCS_10-20EEG . .
## HF-RTMS_10-20EEG HF-RTMS_10-20EEG .
## HF-RTMS_CM 0.57 [ -2.29; 3.44] HF-RTMS_CM
## HF-RTMS_NA 3.56 [ -3.13; 10.24] 2.98 [ -3.69; 9.66]
## HF-RTMS_NEURONAV 4.88 [ 1.67; 8.08] 4.30 [ 1.13; 7.48]
## ITBS_10-20EEG -1.71 [ -5.07; 1.66] -2.28 [ -5.62; 1.06]
## ITBS_CM 4.59 [ 0.83; 8.36] 4.02 [ 0.28; 7.76]
## ITBS_NA 3.46 [ -2.73; 9.64] 2.88 [ -3.29; 9.05]
## ITBS_NEURONAV 0.16 [ -3.53; 3.84] -0.41 [ -4.07; 3.25]
## LF-RTMS_10-10EEG 2.75 [ -3.61; 9.10] 2.17 [ -4.17; 8.52]
## LF-RTMS_10-20EEG 4.01 [ 1.19; 6.83] 3.44 [ 0.65; 6.23]
## LF-RTMS_CM 4.26 [ 0.15; 8.36] 3.68 [ -0.40; 7.76]
## LF-RTMS_NEURONAV 7.69 [ -9.37; 24.74] 7.11 [ -9.93; 24.16]
## SHAM 5.06 [ 3.01; 7.10] 4.48 [ 2.48; 6.49]
## TACS_10-20EEG 3.32 [ -0.63; 7.27] 2.75 [ -1.18; 6.67]
## TDCS_10-20EEG 4.53 [ 1.94; 7.11] 3.95 [ 1.41; 6.50]
## TDCS_10-20EG 2.06 [ -5.02; 9.13] 1.48 [ -5.58; 8.54]
## UNKNOWN_STANDARD 4.48 [ -0.12; 9.08] 3.91 [ -0.67; 8.48]
## HF-RTMS_NA HF-RTMS_NEURONAV
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-10EEG . .
## HD-TDCS_10-20EEG . .
## HF-RTMS_10-20EEG . .
## HF-RTMS_CM . .
## HF-RTMS_NA HF-RTMS_NA .
## HF-RTMS_NEURONAV 1.32 [ -5.51; 8.15] HF-RTMS_NEURONAV
## ITBS_10-20EEG -5.26 [-12.17; 1.64] -6.58 [-10.21; -2.95]
## ITBS_CM 1.04 [ -6.07; 8.15] -0.28 [ -4.29; 3.72]
## ITBS_NA -0.10 [ -8.74; 8.54] -1.42 [ -7.76; 4.91]
## ITBS_NEURONAV -3.40 [-10.46; 3.67] -4.72 [ -8.65; -0.79]
## LF-RTMS_10-10EEG -0.81 [ -9.57; 7.95] -2.13 [ -8.63; 4.37]
## LF-RTMS_10-20EEG 0.46 [ -6.20; 7.11] -0.87 [ -4.00; 2.27]
## LF-RTMS_CM 0.70 [ -6.59; 7.99] -0.62 [ -4.94; 3.71]
## LF-RTMS_NEURONAV 4.13 [-13.96; 22.22] 2.81 [-14.30; 19.92]
## SHAM 1.50 [ -4.87; 7.87] 0.18 [ -2.28; 2.64]
## TACS_10-20EEG -0.24 [ -7.44; 6.97] -1.56 [ -5.74; 2.62]
## TDCS_10-20EEG 0.97 [ -5.59; 7.53] -0.35 [ -3.27; 2.57]
## TDCS_10-20EG -1.50 [-10.80; 7.80] -2.82 [-10.03; 4.39]
## UNKNOWN_STANDARD 0.92 [ -6.66; 8.51] -0.40 [ -5.20; 4.40]
## ITBS_10-20EEG ITBS_CM
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-10EEG . .
## HD-TDCS_10-20EEG . .
## HF-RTMS_10-20EEG . .
## HF-RTMS_CM . .
## HF-RTMS_NA . .
## HF-RTMS_NEURONAV . .
## ITBS_10-20EEG ITBS_10-20EEG .
## ITBS_CM 6.30 [ 2.17; 10.44] ITBS_CM
## ITBS_NA 5.16 [ -1.26; 11.58] -1.14 [ -7.78; 5.50]
## ITBS_NEURONAV 1.87 [ -2.20; 5.93] -4.44 [ -8.84; -0.04]
## LF-RTMS_10-10EEG 4.45 [ -2.13; 11.04] -1.85 [ -8.65; 4.95]
## LF-RTMS_10-20EEG 5.72 [ 2.42; 9.02] -0.58 [ -4.29; 3.12]
## LF-RTMS_CM 5.96 [ 1.52; 10.41] -0.34 [ -5.09; 4.42]
## LF-RTMS_NEURONAV 9.39 [ -7.75; 26.53] 3.09 [-14.13; 20.31]
## SHAM 6.76 [ 4.10; 9.43] 0.46 [ -2.70; 3.62]
## TACS_10-20EEG 5.03 [ 0.72; 9.33] -1.28 [ -5.90; 3.35]
## TDCS_10-20EEG 6.23 [ 3.14; 9.33] -0.07 [ -3.60; 3.46]
## TDCS_10-20EG 3.76 [ -3.52; 11.04] -2.54 [-10.01; 4.93]
## UNKNOWN_STANDARD 6.19 [ 1.28; 11.09] -0.12 [ -5.31; 5.07]
## ITBS_NA ITBS_NEURONAV
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-10EEG . .
## HD-TDCS_10-20EEG . .
## HF-RTMS_10-20EEG . .
## HF-RTMS_CM . .
## HF-RTMS_NA . .
## HF-RTMS_NEURONAV . .
## ITBS_10-20EEG . .
## ITBS_CM . .
## ITBS_NA ITBS_NA .
## ITBS_NEURONAV -3.30 [ -9.89; 3.29] ITBS_NEURONAV
## LF-RTMS_10-10EEG -0.71 [ -9.09; 7.67] 2.59 [ -4.17; 9.34]
## LF-RTMS_10-20EEG 0.56 [ -5.59; 6.71] 3.85 [ 0.23; 7.48]
## LF-RTMS_CM 0.80 [ -6.03; 7.64] 4.10 [ -0.59; 8.79]
## LF-RTMS_NEURONAV 4.23 [-13.68; 22.14] 7.53 [ -9.68; 24.73]
## SHAM 1.60 [ -4.24; 7.44] 4.90 [ 1.83; 7.96]
## TACS_10-20EEG -0.14 [ -6.88; 6.60] 3.16 [ -1.40; 7.72]
## TDCS_10-20EEG 1.07 [ -4.97; 7.12] 4.37 [ 0.93; 7.81]
## TDCS_10-20EG -1.40 [-10.34; 7.54] 1.90 [ -5.53; 9.33]
## UNKNOWN_STANDARD 1.02 [ -6.12; 8.17] 4.32 [ -0.81; 9.45]
## LF-RTMS_10-10EEG LF-RTMS_10-20EEG
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-10EEG . .
## HD-TDCS_10-20EEG . .
## HF-RTMS_10-20EEG . .
## HF-RTMS_CM . .
## HF-RTMS_NA . .
## HF-RTMS_NEURONAV . .
## ITBS_10-20EEG . .
## ITBS_CM . .
## ITBS_NA . .
## ITBS_NEURONAV . .
## LF-RTMS_10-10EEG LF-RTMS_10-10EEG .
## LF-RTMS_10-20EEG 1.27 [ -5.06; 7.59] LF-RTMS_10-20EEG
## LF-RTMS_CM 1.51 [ -5.48; 8.50] 0.25 [ -3.80; 4.29]
## LF-RTMS_NEURONAV 4.94 [-13.03; 22.91] 3.67 [-13.37; 20.71]
## SHAM 2.31 [ -3.71; 8.33] 1.04 [ -0.89; 2.98]
## TACS_10-20EEG 0.57 [ -6.33; 7.47] -0.69 [ -4.58; 3.20]
## TDCS_10-20EEG 1.78 [ -4.44; 8.00] 0.52 [ -1.98; 3.01]
## TDCS_10-20EG -0.69 [ -9.75; 8.37] -1.96 [ -9.00; 5.09]
## UNKNOWN_STANDARD 1.73 [ -5.56; 9.03] 0.47 [ -4.08; 5.02]
## LF-RTMS_CM LF-RTMS_NEURONAV
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-10EEG . .
## HD-TDCS_10-20EEG . .
## HF-RTMS_10-20EEG . .
## HF-RTMS_CM . .
## HF-RTMS_NA . .
## HF-RTMS_NEURONAV . .
## ITBS_10-20EEG . .
## ITBS_CM . .
## ITBS_NA . .
## ITBS_NEURONAV . .
## LF-RTMS_10-10EEG . .
## LF-RTMS_10-20EEG . .
## LF-RTMS_CM LF-RTMS_CM .
## LF-RTMS_NEURONAV 3.43 [-13.87; 20.73] LF-RTMS_NEURONAV
## SHAM 0.80 [ -2.76; 4.35] -2.63 [-19.56; 14.30]
## TACS_10-20EEG -0.94 [ -5.84; 3.96] -4.37 [-21.63; 12.90]
## TDCS_10-20EEG 0.27 [ -3.62; 4.16] -3.16 [-20.16; 13.84]
## TDCS_10-20EG -2.20 [ -9.85; 5.45] -5.63 [-23.86; 12.60]
## UNKNOWN_STANDARD 0.22 [ -5.22; 5.66] -3.21 [-20.63; 14.22]
## SHAM TACS_10-20EEG
## CTBS_10-20EEG 0.32 [ -5.79; 6.43] .
## CTBS_CM 0.06 [ -6.52; 6.64] .
## CTBS_NEURONAV 1.02 [ -6.00; 8.04] .
## DTMS_CM 2.15 [ -1.56; 5.85] .
## HD-TDCS_10-10EEG 3.63 [ -3.20; 10.45] .
## HD-TDCS_10-20EEG 0.32 [ -5.98; 6.62] .
## HF-RTMS_10-20EEG 5.06 [ 3.01; 7.10] .
## HF-RTMS_CM 4.48 [ 2.48; 6.49] .
## HF-RTMS_NA 1.50 [ -4.87; 7.87] .
## HF-RTMS_NEURONAV 0.18 [ -2.28; 2.64] .
## ITBS_10-20EEG 6.76 [ 4.10; 9.43] .
## ITBS_CM 0.46 [ -2.70; 3.62] .
## ITBS_NA 1.60 [ -4.24; 7.44] .
## ITBS_NEURONAV 4.90 [ 1.83; 7.96] .
## LF-RTMS_10-10EEG 2.31 [ -3.71; 8.33] .
## LF-RTMS_10-20EEG 1.04 [ -0.89; 2.98] .
## LF-RTMS_CM 0.80 [ -2.76; 4.35] .
## LF-RTMS_NEURONAV -2.63 [-19.56; 14.30] .
## SHAM SHAM -1.74 [ -5.11; 1.64]
## TACS_10-20EEG -1.74 [ -5.11; 1.64] TACS_10-20EEG
## TDCS_10-20EEG -0.53 [ -2.10; 1.04] 1.21 [ -2.51; 4.93]
## TDCS_10-20EG -3.00 [ -9.77; 3.77] -1.26 [ -8.83; 6.30]
## UNKNOWN_STANDARD -0.58 [ -4.69; 3.54] 1.16 [ -4.16; 6.48]
## TDCS_10-20EEG TDCS_10-20EG
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-10EEG . .
## HD-TDCS_10-20EEG . .
## HF-RTMS_10-20EEG . .
## HF-RTMS_CM . .
## HF-RTMS_NA . .
## HF-RTMS_NEURONAV . .
## ITBS_10-20EEG . .
## ITBS_CM . .
## ITBS_NA . .
## ITBS_NEURONAV . .
## LF-RTMS_10-10EEG . .
## LF-RTMS_10-20EEG . .
## LF-RTMS_CM . .
## LF-RTMS_NEURONAV . .
## SHAM -0.53 [ -2.10; 1.04] -3.00 [ -9.77; 3.77]
## TACS_10-20EEG . .
## TDCS_10-20EEG TDCS_10-20EEG .
## TDCS_10-20EG -2.47 [ -9.42; 4.48] TDCS_10-20EG
## UNKNOWN_STANDARD -0.05 [ -4.46; 4.36] 2.42 [ -5.50; 10.35]
## UNKNOWN_STANDARD
## CTBS_10-20EEG .
## CTBS_CM .
## CTBS_NEURONAV .
## DTMS_CM .
## HD-TDCS_10-10EEG .
## HD-TDCS_10-20EEG .
## HF-RTMS_10-20EEG .
## HF-RTMS_CM .
## HF-RTMS_NA .
## HF-RTMS_NEURONAV .
## ITBS_10-20EEG .
## ITBS_CM .
## ITBS_NA .
## ITBS_NEURONAV .
## LF-RTMS_10-10EEG .
## LF-RTMS_10-20EEG .
## LF-RTMS_CM .
## LF-RTMS_NEURONAV .
## SHAM -0.58 [ -4.69; 3.54]
## TACS_10-20EEG .
## TDCS_10-20EEG .
## TDCS_10-20EG .
## UNKNOWN_STANDARD UNKNOWN_STANDARD
##
## Upper triangle: MD (95% CI); lower triangle: p-value
## Positive values favor the column-defining treatment
##
## Treatment Rankings (SUCRA values):
## SUCRA values not available in netrank output
##
## ==================================================
## Network Meta-Analysis for Total Psychopathology
## ==================================================
##
## Available treatments for Total Psychopathology NMA:
##
## CTBS_10-20EEG CTBS_CM CTBS_NEURONAV DTMS_CM
## 1 1 1 3
## HD-TDCS_10-20EEG HF-RTMS_10-20EEG HF-RTMS_CM HF-RTMS_NA
## 1 7 9 2
## HF-RTMS_NEURONAV ITBS_10-20EEG ITBS_CM ITBS_NA
## 6 5 2 1
## ITBS_NEURONAV LF-RTMS_10-10EEG LF-RTMS_10-20EEG LF-RTMS_CM
## 2 1 5 3
## LF-RTMS_NEURONAV PRM-RTMS_NEURONAV SHAM TACS_10-20EEG
## 1 1 73 3
## TDCS_10-20EEG UNKNOWN_STANDARD
## 17 1
##
## Running network meta-analysis for Total Psychopathology ...
##
## Summary of results:
## Original data:
##
## treat1
## battion, 2021_ITBS_CM_T_PANSS_1 ITBS_CM
## blumberger, 2012_LF-RTMS_NEURONAV_T_PANSS_1 LF-RTMS_NEURONAV
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_T_PANSS_1 PRM-RTMS_NEURONAV
## brunelin, 2012_TDCS_10-20EEG_T_PANSS_1 SHAM
## chang-a, 2021_TACS_10-20EEG_T_PANSS_1 SHAM
## chauhan, 2021_ITBS_10-20EEG_T_PANSS_1 ITBS_10-20EEG
## chauhan, 2021_ITBS_10-20EEG_T_BPRS_1 ITBS_10-20EEG
## de jesus, 2011_LF-RTMS_10-20EEG_T_BPRS_1 LF-RTMS_10-20EEG
## du, 2024_HF-RTMS_NEURONAV_T_BPRS_1 HF-RTMS_NEURONAV
## du, 2022_HF-RTMS_10-20EEG_T_PANSS_1 HF-RTMS_10-20EEG
## fitzerald, 2008_LF-RTMS_CM_T_PANSS_1 LF-RTMS_CM
## fitzerald-l, 2014_TDCS_10-20EEG_T_PANSS_1 SHAM
## fitzerald-bi, 2014_TDCS_10-20EEG_T_PANSS_1 SHAM
## frohlich, 2016_TDCS_10-20EEG_T_PANSS_1 SHAM
## gao, 2024_ITBS_10-20EEG_T_PANSS_1 ITBS_10-20EEG
## garg, 2016_DTMS_CM_T_PANSS_1 DTMS_CM
## gomes, 2018_TDCS_10-20EEG_T_PANSS-T_1 SHAM
## guan, 2020_HF-RTMS_NEURONAV_T_PANSS-T_1 HF-RTMS_NEURONAV
## holi, 2004_HF-RTMS_10-20EEG_T_PANSS_1 HF-RTMS_10-20EEG
## hu, 2024_LF-RTMS_10-20EEG_T_PANSS_1 LF-RTMS_10-20EEG
## hu, 2023_LF-RTMS_10-10EEG_T_PANSS_1 LF-RTMS_10-10EEG
## huang, 2016_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## jeon, 2018_TDCS_10-20EEG_T_PANSS_1 SHAM
## jin, 2023_ITBS_NA_T_PANSS_1 ITBS_NA
## kang, 2024_CTBS_CM_T_PANSS_1 CTBS_CM
## klein, 1999_LF-RTMS_CM_T_BPRS_1 LF-RTMS_CM
## koops, 2018_TDCS_10-20EEG_T_PANSS_1 SHAM
## liu, 2024_HF-RTMS_NA_T_PANSS_1 HF-RTMS_NA
## lyu, 2024_TDCS_10-20EEG_T_PANSS_1 SHAM
## mao, 2023_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## meiron, 2021_TDCS_10-20EEG_T_PANSS_1 SHAM
## meiron, 2024_TDCS_10-20EEG_T_PANSS_1 SHAM
## mellin-tacs, 2018_TACS_10-20EEG_T_PANSS-T_1 SHAM
## mellin-tdcs, 2018_TDCS_10-20EEG_T_PANSS_1 SHAM
## moeller, 2022_DTMS_CM_T_PANSS_1 DTMS_CM
## novak, 2006_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## palm, 2016_TDCS_10-20EEG_T_PANSS_1 SHAM
## prikryl, 2007_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## prikryl, 2012_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## prikryl, 2014_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## quan, 2015_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## rabany, 2014_DTMS_CM_T_PANSS_1 DTMS_CM
## rollnik, 2000_HF-RTMS_CM_T_BPRS_1 HF-RTMS_CM
## rosa, 2007_LF-RTMS_10-20EEG_T_PANSS_1 LF-RTMS_10-20EEG
## saba, 2006_LF-RTMS_CM_T_PANSS_1 LF-RTMS_CM
## smith, 2015_TDCS_10-20EEG_T_PANSS_1 SHAM
## smith, 2020_TDCS_10-20EEG_T_PANSS_1 SHAM
## su, 2023b_HF-RTMS_NEURONAV_T_PANSS_1 HF-RTMS_NEURONAV
## su, 2022_HF-RTMS_NEURONAV_T_PANSS_1 HF-RTMS_NEURONAV
## tikka, 2017_CTBS_NEURONAV_T_PANSS_1 CTBS_NEURONAV
## tyagi, 2022_CTBS_10-20EEG_T_PANSS_1 CTBS_10-20EEG
## valiengo, 2020_TDCS_10-20EEG_T_PANSS_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_T_PANSS_1 ITBS_10-20EEG
## walther-lft, 2024_UNKNOWN_STANDARD_T_PANSS_1 SHAM
## walther-itbs, 2024_ITBS_CM_T_PANSS_1 ITBS_CM
## wang, 2020_ITBS_NEURONAV_T_PANSS_1 ITBS_NEURONAV
## wang, 2022_ITBS_NEURONAV_T_PANSS_1 ITBS_NEURONAV
## weickert, 2019_TDCS_10-20EEG_T_PANSS_1 SHAM
## wen, 2021_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## wobrock, 2015_HF-RTMS_10-20EEG_T_PANSS_1 HF-RTMS_10-20EEG
## xie, 2023-a_LF-RTMS_10-20EEG_T_PANSS_1 LF-RTMS_10-20EEG
## xiu-10hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 HF-RTMS_NEURONAV
## xiu-20hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 HF-RTMS_NEURONAV
## xu, 2023_HD-TDCS_10-20EEG_T_PANSS_1 HD-TDCS_10-20EEG
## yuanjun, 2024_LF-RTMS_10-20EEG_T_PANSS_1 LF-RTMS_10-20EEG
## zhai-a, 2023_HF-RTMS_NA_T_PANSS_1 HF-RTMS_NA
## zhang, 2022_TACS_10-20EEG_T_PANSS_1 SHAM
## zhao-tbs, 2014_ITBS_10-20EEG_T_PANSS_1 ITBS_10-20EEG
## zhao-20hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 HF-RTMS_10-20EEG
## zhao-10hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 HF-RTMS_10-20EEG
## zhou, 2024_HF-RTMS_10-20EEG_T_PANSS_1 HF-RTMS_10-20EEG
## zhou, 2023_TDCS_10-20EEG_T_PANSS_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_T_PANSS_1 HF-RTMS_10-20EEG
## treat2 TE
## battion, 2021_ITBS_CM_T_PANSS_1 SHAM 2.2500
## blumberger, 2012_LF-RTMS_NEURONAV_T_PANSS_1 SHAM 1.8000
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_T_PANSS_1 SHAM 5.8700
## brunelin, 2012_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG -7.7000
## chang-a, 2021_TACS_10-20EEG_T_PANSS_1 TACS_10-20EEG -4.3900
## chauhan, 2021_ITBS_10-20EEG_T_PANSS_1 SHAM -0.8300
## chauhan, 2021_ITBS_10-20EEG_T_BPRS_1 SHAM -0.0700
## de jesus, 2011_LF-RTMS_10-20EEG_T_BPRS_1 SHAM 6.0100
## du, 2024_HF-RTMS_NEURONAV_T_BPRS_1 SHAM -1.0000
## du, 2022_HF-RTMS_10-20EEG_T_PANSS_1 SHAM -0.6000
## fitzerald, 2008_LF-RTMS_CM_T_PANSS_1 SHAM -0.2000
## fitzerald-l, 2014_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG -0.9000
## fitzerald-bi, 2014_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG -9.1000
## frohlich, 2016_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG 3.3000
## gao, 2024_ITBS_10-20EEG_T_PANSS_1 SHAM 3.4600
## garg, 2016_DTMS_CM_T_PANSS_1 SHAM 3.6000
## gomes, 2018_TDCS_10-20EEG_T_PANSS-T_1 TDCS_10-20EEG -9.9200
## guan, 2020_HF-RTMS_NEURONAV_T_PANSS-T_1 SHAM -0.0000
## holi, 2004_HF-RTMS_10-20EEG_T_PANSS_1 SHAM -11.8000
## hu, 2024_LF-RTMS_10-20EEG_T_PANSS_1 SHAM 9.2700
## hu, 2023_LF-RTMS_10-10EEG_T_PANSS_1 SHAM 9.9300
## huang, 2016_HF-RTMS_CM_T_PANSS_1 SHAM 3.9100
## jeon, 2018_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG -6.6000
## jin, 2023_ITBS_NA_T_PANSS_1 SHAM 1.7000
## kang, 2024_CTBS_CM_T_PANSS_1 SHAM 2.9700
## klein, 1999_LF-RTMS_CM_T_BPRS_1 SHAM 0.5000
## koops, 2018_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG -1.9500
## liu, 2024_HF-RTMS_NA_T_PANSS_1 SHAM 2.1800
## lyu, 2024_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG 3.6000
## mao, 2023_HF-RTMS_CM_T_PANSS_1 SHAM 4.8000
## meiron, 2021_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG -10.9670
## meiron, 2024_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG -10.1400
## mellin-tacs, 2018_TACS_10-20EEG_T_PANSS-T_1 TACS_10-20EEG 0.2100
## mellin-tdcs, 2018_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG -2.4400
## moeller, 2022_DTMS_CM_T_PANSS_1 SHAM 5.3000
## novak, 2006_HF-RTMS_CM_T_PANSS_1 SHAM -4.3750
## palm, 2016_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG -2.1000
## prikryl, 2007_HF-RTMS_CM_T_PANSS_1 SHAM 4.9100
## prikryl, 2012_HF-RTMS_CM_T_PANSS_1 SHAM 9.6600
## prikryl, 2014_HF-RTMS_CM_T_PANSS_1 SHAM 10.0800
## quan, 2015_HF-RTMS_CM_T_PANSS_1 SHAM 4.9200
## rabany, 2014_DTMS_CM_T_PANSS_1 SHAM 3.6000
## rollnik, 2000_HF-RTMS_CM_T_BPRS_1 SHAM 13.6000
## rosa, 2007_LF-RTMS_10-20EEG_T_PANSS_1 SHAM 0.7300
## saba, 2006_LF-RTMS_CM_T_PANSS_1 SHAM -7.0800
## smith, 2015_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG 3.7000
## smith, 2020_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG 1.0900
## su, 2023b_HF-RTMS_NEURONAV_T_PANSS_1 SHAM 0.1000
## su, 2022_HF-RTMS_NEURONAV_T_PANSS_1 SHAM 0.2000
## tikka, 2017_CTBS_NEURONAV_T_PANSS_1 SHAM -0.2100
## tyagi, 2022_CTBS_10-20EEG_T_PANSS_1 SHAM 2.1100
## valiengo, 2020_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG -2.2800
## vergallito, 2024_ITBS_10-20EEG_T_PANSS_1 SHAM 18.8100
## walther-lft, 2024_UNKNOWN_STANDARD_T_PANSS_1 UNKNOWN_STANDARD -2.4000
## walther-itbs, 2024_ITBS_CM_T_PANSS_1 SHAM 5.1000
## wang, 2020_ITBS_NEURONAV_T_PANSS_1 SHAM 11.6900
## wang, 2022_ITBS_NEURONAV_T_PANSS_1 SHAM 13.7010
## weickert, 2019_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG 1.6000
## wen, 2021_HF-RTMS_CM_T_PANSS_1 SHAM -4.2000
## wobrock, 2015_HF-RTMS_10-20EEG_T_PANSS_1 SHAM 2.1000
## xie, 2023-a_LF-RTMS_10-20EEG_T_PANSS_1 SHAM 11.9800
## xiu-10hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 SHAM -8.1000
## xiu-20hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 SHAM 2.2000
## xu, 2023_HD-TDCS_10-20EEG_T_PANSS_1 SHAM 4.6400
## yuanjun, 2024_LF-RTMS_10-20EEG_T_PANSS_1 SHAM 12.0700
## zhai-a, 2023_HF-RTMS_NA_T_PANSS_1 SHAM -1.6000
## zhang, 2022_TACS_10-20EEG_T_PANSS_1 TACS_10-20EEG -3.2300
## zhao-tbs, 2014_ITBS_10-20EEG_T_PANSS_1 SHAM 15.3000
## zhao-20hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 SHAM 11.4000
## zhao-10hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 SHAM 12.4000
## zhou, 2024_HF-RTMS_10-20EEG_T_PANSS_1 SHAM 11.3000
## zhou, 2023_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG 4.1900
## zhuo, 2019_HF-RTMS_10-20EEG_T_PANSS_1 SHAM 3.4900
## seTE
## battion, 2021_ITBS_CM_T_PANSS_1 4.6224
## blumberger, 2012_LF-RTMS_NEURONAV_T_PANSS_1 4.3848
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_T_PANSS_1 4.7186
## brunelin, 2012_TDCS_10-20EEG_T_PANSS_1 4.2712
## chang-a, 2021_TACS_10-20EEG_T_PANSS_1 2.3647
## chauhan, 2021_ITBS_10-20EEG_T_PANSS_1 2.2750
## chauhan, 2021_ITBS_10-20EEG_T_BPRS_1 1.5994
## de jesus, 2011_LF-RTMS_10-20EEG_T_BPRS_1 2.9621
## du, 2024_HF-RTMS_NEURONAV_T_BPRS_1 3.5496
## du, 2022_HF-RTMS_10-20EEG_T_PANSS_1 3.7481
## fitzerald, 2008_LF-RTMS_CM_T_PANSS_1 3.8621
## fitzerald-l, 2014_TDCS_10-20EEG_T_PANSS_1 4.0027
## fitzerald-bi, 2014_TDCS_10-20EEG_T_PANSS_1 5.9961
## frohlich, 2016_TDCS_10-20EEG_T_PANSS_1 4.5348
## gao, 2024_ITBS_10-20EEG_T_PANSS_1 0.7065
## garg, 2016_DTMS_CM_T_PANSS_1 4.2505
## gomes, 2018_TDCS_10-20EEG_T_PANSS-T_1 5.5694
## guan, 2020_HF-RTMS_NEURONAV_T_PANSS-T_1 4.3134
## holi, 2004_HF-RTMS_10-20EEG_T_PANSS_1 10.4397
## hu, 2024_LF-RTMS_10-20EEG_T_PANSS_1 2.1748
## hu, 2023_LF-RTMS_10-10EEG_T_PANSS_1 2.1014
## huang, 2016_HF-RTMS_CM_T_PANSS_1 3.2654
## jeon, 2018_TDCS_10-20EEG_T_PANSS_1 5.0319
## jin, 2023_ITBS_NA_T_PANSS_1 0.9427
## kang, 2024_CTBS_CM_T_PANSS_1 3.8512
## klein, 1999_LF-RTMS_CM_T_BPRS_1 2.7293
## koops, 2018_TDCS_10-20EEG_T_PANSS_1 3.5113
## liu, 2024_HF-RTMS_NA_T_PANSS_1 3.7598
## lyu, 2024_TDCS_10-20EEG_T_PANSS_1 2.7562
## mao, 2023_HF-RTMS_CM_T_PANSS_1 2.6283
## meiron, 2021_TDCS_10-20EEG_T_PANSS_1 6.7916
## meiron, 2024_TDCS_10-20EEG_T_PANSS_1 5.8477
## mellin-tacs, 2018_TACS_10-20EEG_T_PANSS-T_1 4.0421
## mellin-tdcs, 2018_TDCS_10-20EEG_T_PANSS_1 4.9888
## moeller, 2022_DTMS_CM_T_PANSS_1 4.3705
## novak, 2006_HF-RTMS_CM_T_PANSS_1 6.7943
## palm, 2016_TDCS_10-20EEG_T_PANSS_1 5.2636
## prikryl, 2007_HF-RTMS_CM_T_PANSS_1 3.4590
## prikryl, 2012_HF-RTMS_CM_T_PANSS_1 3.1738
## prikryl, 2014_HF-RTMS_CM_T_PANSS_1 2.5604
## quan, 2015_HF-RTMS_CM_T_PANSS_1 1.8186
## rabany, 2014_DTMS_CM_T_PANSS_1 6.7610
## rollnik, 2000_HF-RTMS_CM_T_BPRS_1 5.0598
## rosa, 2007_LF-RTMS_10-20EEG_T_PANSS_1 5.4841
## saba, 2006_LF-RTMS_CM_T_PANSS_1 6.0568
## smith, 2015_TDCS_10-20EEG_T_PANSS_1 4.8768
## smith, 2020_TDCS_10-20EEG_T_PANSS_1 3.3744
## su, 2023b_HF-RTMS_NEURONAV_T_PANSS_1 5.6387
## su, 2022_HF-RTMS_NEURONAV_T_PANSS_1 5.2345
## tikka, 2017_CTBS_NEURONAV_T_PANSS_1 4.8631
## tyagi, 2022_CTBS_10-20EEG_T_PANSS_1 2.3342
## valiengo, 2020_TDCS_10-20EEG_T_PANSS_1 2.4152
## vergallito, 2024_ITBS_10-20EEG_T_PANSS_1 10.2981
## walther-lft, 2024_UNKNOWN_STANDARD_T_PANSS_1 0.9811
## walther-itbs, 2024_ITBS_CM_T_PANSS_1 0.9466
## wang, 2020_ITBS_NEURONAV_T_PANSS_1 3.2783
## wang, 2022_ITBS_NEURONAV_T_PANSS_1 3.6723
## weickert, 2019_TDCS_10-20EEG_T_PANSS_1 6.3705
## wen, 2021_HF-RTMS_CM_T_PANSS_1 2.4856
## wobrock, 2015_HF-RTMS_10-20EEG_T_PANSS_1 2.3178
## xie, 2023-a_LF-RTMS_10-20EEG_T_PANSS_1 1.9406
## xiu-10hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 3.2142
## xiu-20hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 3.1952
## xu, 2023_HD-TDCS_10-20EEG_T_PANSS_1 4.1812
## yuanjun, 2024_LF-RTMS_10-20EEG_T_PANSS_1 1.9958
## zhai-a, 2023_HF-RTMS_NA_T_PANSS_1 1.0572
## zhang, 2022_TACS_10-20EEG_T_PANSS_1 4.9937
## zhao-tbs, 2014_ITBS_10-20EEG_T_PANSS_1 1.9638
## zhao-20hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 1.8042
## zhao-10hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 1.9376
## zhou, 2024_HF-RTMS_10-20EEG_T_PANSS_1 2.4709
## zhou, 2023_TDCS_10-20EEG_T_PANSS_1 2.8841
## zhuo, 2019_HF-RTMS_10-20EEG_T_PANSS_1 1.4391
##
## Number of treatment arms (by study):
## narms
## battion, 2021_ITBS_CM_T_PANSS_1 2
## blumberger, 2012_LF-RTMS_NEURONAV_T_PANSS_1 2
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_T_PANSS_1 2
## brunelin, 2012_TDCS_10-20EEG_T_PANSS_1 2
## chang-a, 2021_TACS_10-20EEG_T_PANSS_1 2
## chauhan, 2021_ITBS_10-20EEG_T_PANSS_1 2
## chauhan, 2021_ITBS_10-20EEG_T_BPRS_1 2
## de jesus, 2011_LF-RTMS_10-20EEG_T_BPRS_1 2
## du, 2024_HF-RTMS_NEURONAV_T_BPRS_1 2
## du, 2022_HF-RTMS_10-20EEG_T_PANSS_1 2
## fitzerald, 2008_LF-RTMS_CM_T_PANSS_1 2
## fitzerald-l, 2014_TDCS_10-20EEG_T_PANSS_1 2
## fitzerald-bi, 2014_TDCS_10-20EEG_T_PANSS_1 2
## frohlich, 2016_TDCS_10-20EEG_T_PANSS_1 2
## gao, 2024_ITBS_10-20EEG_T_PANSS_1 2
## garg, 2016_DTMS_CM_T_PANSS_1 2
## gomes, 2018_TDCS_10-20EEG_T_PANSS-T_1 2
## guan, 2020_HF-RTMS_NEURONAV_T_PANSS-T_1 2
## holi, 2004_HF-RTMS_10-20EEG_T_PANSS_1 2
## hu, 2024_LF-RTMS_10-20EEG_T_PANSS_1 2
## hu, 2023_LF-RTMS_10-10EEG_T_PANSS_1 2
## huang, 2016_HF-RTMS_CM_T_PANSS_1 2
## jeon, 2018_TDCS_10-20EEG_T_PANSS_1 2
## jin, 2023_ITBS_NA_T_PANSS_1 2
## kang, 2024_CTBS_CM_T_PANSS_1 2
## klein, 1999_LF-RTMS_CM_T_BPRS_1 2
## koops, 2018_TDCS_10-20EEG_T_PANSS_1 2
## liu, 2024_HF-RTMS_NA_T_PANSS_1 2
## lyu, 2024_TDCS_10-20EEG_T_PANSS_1 2
## mao, 2023_HF-RTMS_CM_T_PANSS_1 2
## meiron, 2021_TDCS_10-20EEG_T_PANSS_1 2
## meiron, 2024_TDCS_10-20EEG_T_PANSS_1 2
## mellin-tacs, 2018_TACS_10-20EEG_T_PANSS-T_1 2
## mellin-tdcs, 2018_TDCS_10-20EEG_T_PANSS_1 2
## moeller, 2022_DTMS_CM_T_PANSS_1 2
## novak, 2006_HF-RTMS_CM_T_PANSS_1 2
## palm, 2016_TDCS_10-20EEG_T_PANSS_1 2
## prikryl, 2007_HF-RTMS_CM_T_PANSS_1 2
## prikryl, 2012_HF-RTMS_CM_T_PANSS_1 2
## prikryl, 2014_HF-RTMS_CM_T_PANSS_1 2
## quan, 2015_HF-RTMS_CM_T_PANSS_1 2
## rabany, 2014_DTMS_CM_T_PANSS_1 2
## rollnik, 2000_HF-RTMS_CM_T_BPRS_1 2
## rosa, 2007_LF-RTMS_10-20EEG_T_PANSS_1 2
## saba, 2006_LF-RTMS_CM_T_PANSS_1 2
## smith, 2015_TDCS_10-20EEG_T_PANSS_1 2
## smith, 2020_TDCS_10-20EEG_T_PANSS_1 2
## su, 2023b_HF-RTMS_NEURONAV_T_PANSS_1 2
## su, 2022_HF-RTMS_NEURONAV_T_PANSS_1 2
## tikka, 2017_CTBS_NEURONAV_T_PANSS_1 2
## tyagi, 2022_CTBS_10-20EEG_T_PANSS_1 2
## valiengo, 2020_TDCS_10-20EEG_T_PANSS_1 2
## vergallito, 2024_ITBS_10-20EEG_T_PANSS_1 2
## walther-lft, 2024_UNKNOWN_STANDARD_T_PANSS_1 2
## walther-itbs, 2024_ITBS_CM_T_PANSS_1 2
## wang, 2020_ITBS_NEURONAV_T_PANSS_1 2
## wang, 2022_ITBS_NEURONAV_T_PANSS_1 2
## weickert, 2019_TDCS_10-20EEG_T_PANSS_1 2
## wen, 2021_HF-RTMS_CM_T_PANSS_1 2
## wobrock, 2015_HF-RTMS_10-20EEG_T_PANSS_1 2
## xie, 2023-a_LF-RTMS_10-20EEG_T_PANSS_1 2
## xiu-10hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 2
## xiu-20hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 2
## xu, 2023_HD-TDCS_10-20EEG_T_PANSS_1 2
## yuanjun, 2024_LF-RTMS_10-20EEG_T_PANSS_1 2
## zhai-a, 2023_HF-RTMS_NA_T_PANSS_1 2
## zhang, 2022_TACS_10-20EEG_T_PANSS_1 2
## zhao-tbs, 2014_ITBS_10-20EEG_T_PANSS_1 2
## zhao-20hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 2
## zhao-10hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 2
## zhou, 2024_HF-RTMS_10-20EEG_T_PANSS_1 2
## zhou, 2023_TDCS_10-20EEG_T_PANSS_1 2
## zhuo, 2019_HF-RTMS_10-20EEG_T_PANSS_1 2
##
## Results (random effects model):
##
## treat1
## battion, 2021_ITBS_CM_T_PANSS_1 ITBS_CM
## blumberger, 2012_LF-RTMS_NEURONAV_T_PANSS_1 LF-RTMS_NEURONAV
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_T_PANSS_1 PRM-RTMS_NEURONAV
## brunelin, 2012_TDCS_10-20EEG_T_PANSS_1 SHAM
## chang-a, 2021_TACS_10-20EEG_T_PANSS_1 SHAM
## chauhan, 2021_ITBS_10-20EEG_T_PANSS_1 ITBS_10-20EEG
## chauhan, 2021_ITBS_10-20EEG_T_BPRS_1 ITBS_10-20EEG
## de jesus, 2011_LF-RTMS_10-20EEG_T_BPRS_1 LF-RTMS_10-20EEG
## du, 2024_HF-RTMS_NEURONAV_T_BPRS_1 HF-RTMS_NEURONAV
## du, 2022_HF-RTMS_10-20EEG_T_PANSS_1 HF-RTMS_10-20EEG
## fitzerald, 2008_LF-RTMS_CM_T_PANSS_1 LF-RTMS_CM
## fitzerald-l, 2014_TDCS_10-20EEG_T_PANSS_1 SHAM
## fitzerald-bi, 2014_TDCS_10-20EEG_T_PANSS_1 SHAM
## frohlich, 2016_TDCS_10-20EEG_T_PANSS_1 SHAM
## gao, 2024_ITBS_10-20EEG_T_PANSS_1 ITBS_10-20EEG
## garg, 2016_DTMS_CM_T_PANSS_1 DTMS_CM
## gomes, 2018_TDCS_10-20EEG_T_PANSS-T_1 SHAM
## guan, 2020_HF-RTMS_NEURONAV_T_PANSS-T_1 HF-RTMS_NEURONAV
## holi, 2004_HF-RTMS_10-20EEG_T_PANSS_1 HF-RTMS_10-20EEG
## hu, 2024_LF-RTMS_10-20EEG_T_PANSS_1 LF-RTMS_10-20EEG
## hu, 2023_LF-RTMS_10-10EEG_T_PANSS_1 LF-RTMS_10-10EEG
## huang, 2016_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## jeon, 2018_TDCS_10-20EEG_T_PANSS_1 SHAM
## jin, 2023_ITBS_NA_T_PANSS_1 ITBS_NA
## kang, 2024_CTBS_CM_T_PANSS_1 CTBS_CM
## klein, 1999_LF-RTMS_CM_T_BPRS_1 LF-RTMS_CM
## koops, 2018_TDCS_10-20EEG_T_PANSS_1 SHAM
## liu, 2024_HF-RTMS_NA_T_PANSS_1 HF-RTMS_NA
## lyu, 2024_TDCS_10-20EEG_T_PANSS_1 SHAM
## mao, 2023_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## meiron, 2021_TDCS_10-20EEG_T_PANSS_1 SHAM
## meiron, 2024_TDCS_10-20EEG_T_PANSS_1 SHAM
## mellin-tacs, 2018_TACS_10-20EEG_T_PANSS-T_1 SHAM
## mellin-tdcs, 2018_TDCS_10-20EEG_T_PANSS_1 SHAM
## moeller, 2022_DTMS_CM_T_PANSS_1 DTMS_CM
## novak, 2006_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## palm, 2016_TDCS_10-20EEG_T_PANSS_1 SHAM
## prikryl, 2007_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## prikryl, 2012_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## prikryl, 2014_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## quan, 2015_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## rabany, 2014_DTMS_CM_T_PANSS_1 DTMS_CM
## rollnik, 2000_HF-RTMS_CM_T_BPRS_1 HF-RTMS_CM
## rosa, 2007_LF-RTMS_10-20EEG_T_PANSS_1 LF-RTMS_10-20EEG
## saba, 2006_LF-RTMS_CM_T_PANSS_1 LF-RTMS_CM
## smith, 2015_TDCS_10-20EEG_T_PANSS_1 SHAM
## smith, 2020_TDCS_10-20EEG_T_PANSS_1 SHAM
## su, 2023b_HF-RTMS_NEURONAV_T_PANSS_1 HF-RTMS_NEURONAV
## su, 2022_HF-RTMS_NEURONAV_T_PANSS_1 HF-RTMS_NEURONAV
## tikka, 2017_CTBS_NEURONAV_T_PANSS_1 CTBS_NEURONAV
## tyagi, 2022_CTBS_10-20EEG_T_PANSS_1 CTBS_10-20EEG
## valiengo, 2020_TDCS_10-20EEG_T_PANSS_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_T_PANSS_1 ITBS_10-20EEG
## walther-lft, 2024_UNKNOWN_STANDARD_T_PANSS_1 SHAM
## walther-itbs, 2024_ITBS_CM_T_PANSS_1 ITBS_CM
## wang, 2020_ITBS_NEURONAV_T_PANSS_1 ITBS_NEURONAV
## wang, 2022_ITBS_NEURONAV_T_PANSS_1 ITBS_NEURONAV
## weickert, 2019_TDCS_10-20EEG_T_PANSS_1 SHAM
## wen, 2021_HF-RTMS_CM_T_PANSS_1 HF-RTMS_CM
## wobrock, 2015_HF-RTMS_10-20EEG_T_PANSS_1 HF-RTMS_10-20EEG
## xie, 2023-a_LF-RTMS_10-20EEG_T_PANSS_1 LF-RTMS_10-20EEG
## xiu-10hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 HF-RTMS_NEURONAV
## xiu-20hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 HF-RTMS_NEURONAV
## xu, 2023_HD-TDCS_10-20EEG_T_PANSS_1 HD-TDCS_10-20EEG
## yuanjun, 2024_LF-RTMS_10-20EEG_T_PANSS_1 LF-RTMS_10-20EEG
## zhai-a, 2023_HF-RTMS_NA_T_PANSS_1 HF-RTMS_NA
## zhang, 2022_TACS_10-20EEG_T_PANSS_1 SHAM
## zhao-tbs, 2014_ITBS_10-20EEG_T_PANSS_1 ITBS_10-20EEG
## zhao-20hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 HF-RTMS_10-20EEG
## zhao-10hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 HF-RTMS_10-20EEG
## zhou, 2024_HF-RTMS_10-20EEG_T_PANSS_1 HF-RTMS_10-20EEG
## zhou, 2023_TDCS_10-20EEG_T_PANSS_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_T_PANSS_1 HF-RTMS_10-20EEG
## treat2 MD
## battion, 2021_ITBS_CM_T_PANSS_1 SHAM 4.2293
## blumberger, 2012_LF-RTMS_NEURONAV_T_PANSS_1 SHAM 1.8000
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_T_PANSS_1 SHAM 5.8700
## brunelin, 2012_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG -1.8180
## chang-a, 2021_TACS_10-20EEG_T_PANSS_1 TACS_10-20EEG -2.7214
## chauhan, 2021_ITBS_10-20EEG_T_PANSS_1 SHAM 4.9329
## chauhan, 2021_ITBS_10-20EEG_T_BPRS_1 SHAM 4.9329
## de jesus, 2011_LF-RTMS_10-20EEG_T_BPRS_1 SHAM 9.1071
## du, 2024_HF-RTMS_NEURONAV_T_BPRS_1 SHAM -1.3761
## du, 2022_HF-RTMS_10-20EEG_T_PANSS_1 SHAM 6.5792
## fitzerald, 2008_LF-RTMS_CM_T_PANSS_1 SHAM -1.2520
## fitzerald-l, 2014_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG -1.8180
## fitzerald-bi, 2014_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG -1.8180
## frohlich, 2016_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG -1.8180
## gao, 2024_ITBS_10-20EEG_T_PANSS_1 SHAM 4.9329
## garg, 2016_DTMS_CM_T_PANSS_1 SHAM 4.2553
## gomes, 2018_TDCS_10-20EEG_T_PANSS-T_1 TDCS_10-20EEG -1.8180
## guan, 2020_HF-RTMS_NEURONAV_T_PANSS-T_1 SHAM -1.3761
## holi, 2004_HF-RTMS_10-20EEG_T_PANSS_1 SHAM 6.5792
## hu, 2024_LF-RTMS_10-20EEG_T_PANSS_1 SHAM 9.1071
## hu, 2023_LF-RTMS_10-10EEG_T_PANSS_1 SHAM 9.9300
## huang, 2016_HF-RTMS_CM_T_PANSS_1 SHAM 4.9618
## jeon, 2018_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG -1.8180
## jin, 2023_ITBS_NA_T_PANSS_1 SHAM 1.7000
## kang, 2024_CTBS_CM_T_PANSS_1 SHAM 2.9700
## klein, 1999_LF-RTMS_CM_T_BPRS_1 SHAM -1.2520
## koops, 2018_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG -1.8180
## liu, 2024_HF-RTMS_NA_T_PANSS_1 SHAM -0.2493
## lyu, 2024_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG -1.8180
## mao, 2023_HF-RTMS_CM_T_PANSS_1 SHAM 4.9618
## meiron, 2021_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG -1.8180
## meiron, 2024_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG -1.8180
## mellin-tacs, 2018_TACS_10-20EEG_T_PANSS-T_1 TACS_10-20EEG -2.7214
## mellin-tdcs, 2018_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG -1.8180
## moeller, 2022_DTMS_CM_T_PANSS_1 SHAM 4.2553
## novak, 2006_HF-RTMS_CM_T_PANSS_1 SHAM 4.9618
## palm, 2016_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG -1.8180
## prikryl, 2007_HF-RTMS_CM_T_PANSS_1 SHAM 4.9618
## prikryl, 2012_HF-RTMS_CM_T_PANSS_1 SHAM 4.9618
## prikryl, 2014_HF-RTMS_CM_T_PANSS_1 SHAM 4.9618
## quan, 2015_HF-RTMS_CM_T_PANSS_1 SHAM 4.9618
## rabany, 2014_DTMS_CM_T_PANSS_1 SHAM 4.2553
## rollnik, 2000_HF-RTMS_CM_T_BPRS_1 SHAM 4.9618
## rosa, 2007_LF-RTMS_10-20EEG_T_PANSS_1 SHAM 9.1071
## saba, 2006_LF-RTMS_CM_T_PANSS_1 SHAM -1.2520
## smith, 2015_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG -1.8180
## smith, 2020_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG -1.8180
## su, 2023b_HF-RTMS_NEURONAV_T_PANSS_1 SHAM -1.3761
## su, 2022_HF-RTMS_NEURONAV_T_PANSS_1 SHAM -1.3761
## tikka, 2017_CTBS_NEURONAV_T_PANSS_1 SHAM -0.2100
## tyagi, 2022_CTBS_10-20EEG_T_PANSS_1 SHAM 2.1100
## valiengo, 2020_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG -1.8180
## vergallito, 2024_ITBS_10-20EEG_T_PANSS_1 SHAM 4.9329
## walther-lft, 2024_UNKNOWN_STANDARD_T_PANSS_1 UNKNOWN_STANDARD -2.4000
## walther-itbs, 2024_ITBS_CM_T_PANSS_1 SHAM 4.2293
## wang, 2020_ITBS_NEURONAV_T_PANSS_1 SHAM 12.6451
## wang, 2022_ITBS_NEURONAV_T_PANSS_1 SHAM 12.6451
## weickert, 2019_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG -1.8180
## wen, 2021_HF-RTMS_CM_T_PANSS_1 SHAM 4.9618
## wobrock, 2015_HF-RTMS_10-20EEG_T_PANSS_1 SHAM 6.5792
## xie, 2023-a_LF-RTMS_10-20EEG_T_PANSS_1 SHAM 9.1071
## xiu-10hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 SHAM -1.3761
## xiu-20hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 SHAM -1.3761
## xu, 2023_HD-TDCS_10-20EEG_T_PANSS_1 SHAM 4.6400
## yuanjun, 2024_LF-RTMS_10-20EEG_T_PANSS_1 SHAM 9.1071
## zhai-a, 2023_HF-RTMS_NA_T_PANSS_1 SHAM -0.2493
## zhang, 2022_TACS_10-20EEG_T_PANSS_1 TACS_10-20EEG -2.7214
## zhao-tbs, 2014_ITBS_10-20EEG_T_PANSS_1 SHAM 4.9329
## zhao-20hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 SHAM 6.5792
## zhao-10hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 SHAM 6.5792
## zhou, 2024_HF-RTMS_10-20EEG_T_PANSS_1 SHAM 6.5792
## zhou, 2023_TDCS_10-20EEG_T_PANSS_1 TDCS_10-20EEG -1.8180
## zhuo, 2019_HF-RTMS_10-20EEG_T_PANSS_1 SHAM 6.5792
## 95%-CI
## battion, 2021_ITBS_CM_T_PANSS_1 [ -2.3203; 10.7789]
## blumberger, 2012_LF-RTMS_NEURONAV_T_PANSS_1 [ -9.6972; 13.2972]
## blumberger-prm, 2012_PRM-RTMS_NEURONAV_T_PANSS_1 [ -6.1241; 17.8641]
## brunelin, 2012_TDCS_10-20EEG_T_PANSS_1 [ -4.6115; 0.9755]
## chang-a, 2021_TACS_10-20EEG_T_PANSS_1 [ -8.7762; 3.3334]
## chauhan, 2021_ITBS_10-20EEG_T_PANSS_1 [ 0.8462; 9.0195]
## chauhan, 2021_ITBS_10-20EEG_T_BPRS_1 [ 0.8462; 9.0195]
## de jesus, 2011_LF-RTMS_10-20EEG_T_BPRS_1 [ 4.9189; 13.2953]
## du, 2024_HF-RTMS_NEURONAV_T_BPRS_1 [ -5.8853; 3.1330]
## du, 2022_HF-RTMS_10-20EEG_T_PANSS_1 [ 3.0179; 10.1406]
## fitzerald, 2008_LF-RTMS_CM_T_PANSS_1 [ -7.5552; 5.0513]
## fitzerald-l, 2014_TDCS_10-20EEG_T_PANSS_1 [ -4.6115; 0.9755]
## fitzerald-bi, 2014_TDCS_10-20EEG_T_PANSS_1 [ -4.6115; 0.9755]
## frohlich, 2016_TDCS_10-20EEG_T_PANSS_1 [ -4.6115; 0.9755]
## gao, 2024_ITBS_10-20EEG_T_PANSS_1 [ 0.8462; 9.0195]
## garg, 2016_DTMS_CM_T_PANSS_1 [ -2.8699; 11.3806]
## gomes, 2018_TDCS_10-20EEG_T_PANSS-T_1 [ -4.6115; 0.9755]
## guan, 2020_HF-RTMS_NEURONAV_T_PANSS-T_1 [ -5.8853; 3.1330]
## holi, 2004_HF-RTMS_10-20EEG_T_PANSS_1 [ 3.0179; 10.1406]
## hu, 2024_LF-RTMS_10-20EEG_T_PANSS_1 [ 4.9189; 13.2953]
## hu, 2023_LF-RTMS_10-10EEG_T_PANSS_1 [ 1.2530; 18.6070]
## huang, 2016_HF-RTMS_CM_T_PANSS_1 [ 1.6398; 8.2837]
## jeon, 2018_TDCS_10-20EEG_T_PANSS_1 [ -4.6115; 0.9755]
## jin, 2023_ITBS_NA_T_PANSS_1 [ -6.1575; 9.5575]
## kang, 2024_CTBS_CM_T_PANSS_1 [ -7.7679; 13.7079]
## klein, 1999_LF-RTMS_CM_T_BPRS_1 [ -7.5552; 5.0513]
## koops, 2018_TDCS_10-20EEG_T_PANSS_1 [ -4.6115; 0.9755]
## liu, 2024_HF-RTMS_NA_T_PANSS_1 [ -6.5932; 6.0946]
## lyu, 2024_TDCS_10-20EEG_T_PANSS_1 [ -4.6115; 0.9755]
## mao, 2023_HF-RTMS_CM_T_PANSS_1 [ 1.6398; 8.2837]
## meiron, 2021_TDCS_10-20EEG_T_PANSS_1 [ -4.6115; 0.9755]
## meiron, 2024_TDCS_10-20EEG_T_PANSS_1 [ -4.6115; 0.9755]
## mellin-tacs, 2018_TACS_10-20EEG_T_PANSS-T_1 [ -8.7762; 3.3334]
## mellin-tdcs, 2018_TDCS_10-20EEG_T_PANSS_1 [ -4.6115; 0.9755]
## moeller, 2022_DTMS_CM_T_PANSS_1 [ -2.8699; 11.3806]
## novak, 2006_HF-RTMS_CM_T_PANSS_1 [ 1.6398; 8.2837]
## palm, 2016_TDCS_10-20EEG_T_PANSS_1 [ -4.6115; 0.9755]
## prikryl, 2007_HF-RTMS_CM_T_PANSS_1 [ 1.6398; 8.2837]
## prikryl, 2012_HF-RTMS_CM_T_PANSS_1 [ 1.6398; 8.2837]
## prikryl, 2014_HF-RTMS_CM_T_PANSS_1 [ 1.6398; 8.2837]
## quan, 2015_HF-RTMS_CM_T_PANSS_1 [ 1.6398; 8.2837]
## rabany, 2014_DTMS_CM_T_PANSS_1 [ -2.8699; 11.3806]
## rollnik, 2000_HF-RTMS_CM_T_BPRS_1 [ 1.6398; 8.2837]
## rosa, 2007_LF-RTMS_10-20EEG_T_PANSS_1 [ 4.9189; 13.2953]
## saba, 2006_LF-RTMS_CM_T_PANSS_1 [ -7.5552; 5.0513]
## smith, 2015_TDCS_10-20EEG_T_PANSS_1 [ -4.6115; 0.9755]
## smith, 2020_TDCS_10-20EEG_T_PANSS_1 [ -4.6115; 0.9755]
## su, 2023b_HF-RTMS_NEURONAV_T_PANSS_1 [ -5.8853; 3.1330]
## su, 2022_HF-RTMS_NEURONAV_T_PANSS_1 [ -5.8853; 3.1330]
## tikka, 2017_CTBS_NEURONAV_T_PANSS_1 [-12.4238; 12.0038]
## tyagi, 2022_CTBS_10-20EEG_T_PANSS_1 [ -6.7927; 11.0127]
## valiengo, 2020_TDCS_10-20EEG_T_PANSS_1 [ -4.6115; 0.9755]
## vergallito, 2024_ITBS_10-20EEG_T_PANSS_1 [ 0.8462; 9.0195]
## walther-lft, 2024_UNKNOWN_STANDARD_T_PANSS_1 [-10.2756; 5.4756]
## walther-itbs, 2024_ITBS_CM_T_PANSS_1 [ -2.3203; 10.7789]
## wang, 2020_ITBS_NEURONAV_T_PANSS_1 [ 5.4129; 19.8772]
## wang, 2022_ITBS_NEURONAV_T_PANSS_1 [ 5.4129; 19.8772]
## weickert, 2019_TDCS_10-20EEG_T_PANSS_1 [ -4.6115; 0.9755]
## wen, 2021_HF-RTMS_CM_T_PANSS_1 [ 1.6398; 8.2837]
## wobrock, 2015_HF-RTMS_10-20EEG_T_PANSS_1 [ 3.0179; 10.1406]
## xie, 2023-a_LF-RTMS_10-20EEG_T_PANSS_1 [ 4.9189; 13.2953]
## xiu-10hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 [ -5.8853; 3.1330]
## xiu-20hz, 2020_HF-RTMS_NEURONAV_T_PANSS_1 [ -5.8853; 3.1330]
## xu, 2023_HD-TDCS_10-20EEG_T_PANSS_1 [ -6.5620; 15.8420]
## yuanjun, 2024_LF-RTMS_10-20EEG_T_PANSS_1 [ 4.9189; 13.2953]
## zhai-a, 2023_HF-RTMS_NA_T_PANSS_1 [ -6.5932; 6.0946]
## zhang, 2022_TACS_10-20EEG_T_PANSS_1 [ -8.7762; 3.3334]
## zhao-tbs, 2014_ITBS_10-20EEG_T_PANSS_1 [ 0.8462; 9.0195]
## zhao-20hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 [ 3.0179; 10.1406]
## zhao-10hz, 2014_HF-RTMS_10-20EEG_T_PANSS_1 [ 3.0179; 10.1406]
## zhou, 2024_HF-RTMS_10-20EEG_T_PANSS_1 [ 3.0179; 10.1406]
## zhou, 2023_TDCS_10-20EEG_T_PANSS_1 [ -4.6115; 0.9755]
## zhuo, 2019_HF-RTMS_10-20EEG_T_PANSS_1 [ 3.0179; 10.1406]
##
## Number of studies: k = 73
## Number of pairwise comparisons: m = 73
## Number of treatments: n = 22
## Number of designs: d = 21
##
## Random effects model
##
## Treatment estimate (sm = 'MD', comparison: other treatments vs 'SHAM'):
## MD 95%-CI z p-value
## CTBS_10-20EEG 2.1100 [ -6.7927; 11.0127] 0.46 0.6423
## CTBS_CM 2.9700 [ -7.7679; 13.7079] 0.54 0.5877
## CTBS_NEURONAV -0.2100 [-12.4238; 12.0038] -0.03 0.9731
## DTMS_CM 4.2553 [ -2.8699; 11.3806] 1.17 0.2418
## HD-TDCS_10-20EEG 4.6400 [ -6.5620; 15.8420] 0.81 0.4169
## HF-RTMS_10-20EEG 6.5792 [ 3.0179; 10.1406] 3.62 0.0003
## HF-RTMS_CM 4.9618 [ 1.6398; 8.2837] 2.93 0.0034
## HF-RTMS_NA -0.2493 [ -6.5932; 6.0946] -0.08 0.9386
## HF-RTMS_NEURONAV -1.3761 [ -5.8853; 3.1330] -0.60 0.5497
## ITBS_10-20EEG 4.9329 [ 0.8462; 9.0195] 2.37 0.0180
## ITBS_CM 4.2293 [ -2.3203; 10.7789] 1.27 0.2057
## ITBS_NA 1.7000 [ -6.1575; 9.5575] 0.42 0.6715
## ITBS_NEURONAV 12.6451 [ 5.4129; 19.8772] 3.43 0.0006
## LF-RTMS_10-10EEG 9.9300 [ 1.2530; 18.6070] 2.24 0.0249
## LF-RTMS_10-20EEG 9.1071 [ 4.9189; 13.2953] 4.26 < 0.0001
## LF-RTMS_CM -1.2520 [ -7.5552; 5.0513] -0.39 0.6971
## LF-RTMS_NEURONAV 1.8000 [ -9.6972; 13.2972] 0.31 0.7590
## PRM-RTMS_NEURONAV 5.8700 [ -6.1241; 17.8641] 0.96 0.3374
## SHAM . . . .
## TACS_10-20EEG 2.7214 [ -3.3334; 8.7762] 0.88 0.3784
## TDCS_10-20EEG 1.8180 [ -0.9755; 4.6115] 1.28 0.2021
## UNKNOWN_STANDARD 2.4000 [ -5.4756; 10.2756] 0.60 0.5503
##
## Quantifying heterogeneity / inconsistency:
## tau^2 = 15.1835; tau = 3.8966; I^2 = 63.9% [51.6%; 73.0%]
##
## Tests of heterogeneity (within designs) and inconsistency (between designs):
## Q d.f. p-value
## Total 143.94 52 < 0.0001
## Within designs 143.94 52 < 0.0001
## Between designs 0.00 0 --
##
## Details of network meta-analysis methods:
## - Frequentist graph-theoretical approach
## - DerSimonian-Laird estimator for tau^2
## - Calculation of I^2 based on Q
##
## Forest Plot:
##
## Network Graph:
##
## League Table for Total Psychopathology :
## CTBS_10-20EEG CTBS_CM
## CTBS_10-20EEG CTBS_10-20EEG .
## CTBS_CM -0.86 [-14.81; 13.09] CTBS_CM
## CTBS_NEURONAV 2.32 [-12.79; 17.43] 3.18 [-13.08; 19.44]
## DTMS_CM -2.15 [-13.55; 9.26] -1.29 [-14.17; 11.60]
## HD-TDCS_10-20EEG -2.53 [-16.84; 11.78] -1.67 [-17.19; 13.85]
## HF-RTMS_10-20EEG -4.47 [-14.06; 5.12] -3.61 [-14.92; 7.70]
## HF-RTMS_CM -2.85 [-12.35; 6.65] -1.99 [-13.23; 9.25]
## HF-RTMS_NA 2.36 [ -8.57; 13.29] 3.22 [ -9.25; 15.69]
## HF-RTMS_NEURONAV 3.49 [ -6.49; 13.47] 4.35 [ -7.30; 15.99]
## ITBS_10-20EEG -2.82 [-12.62; 6.97] -1.96 [-13.45; 9.53]
## ITBS_CM -2.12 [-13.17; 8.93] -1.26 [-13.84; 11.32]
## ITBS_NA 0.41 [-11.46; 12.28] 1.27 [-12.04; 14.58]
## ITBS_NEURONAV -10.54 [-22.01; 0.93] -9.68 [-22.62; 3.27]
## LF-RTMS_10-10EEG -7.82 [-20.25; 4.61] -6.96 [-20.77; 6.85]
## LF-RTMS_10-20EEG -7.00 [-16.84; 2.84] -6.14 [-17.66; 5.39]
## LF-RTMS_CM 3.36 [ -7.55; 14.27] 4.22 [ -8.23; 16.67]
## LF-RTMS_NEURONAV 0.31 [-14.23; 14.85] 1.17 [-14.56; 16.90]
## PRM-RTMS_NEURONAV -3.76 [-18.70; 11.18] -2.90 [-19.00; 13.20]
## SHAM 2.11 [ -6.79; 11.01] 2.97 [ -7.77; 13.71]
## TACS_10-20EEG -0.61 [-11.38; 10.16] 0.25 [-12.08; 12.58]
## TDCS_10-20EEG 0.29 [ -9.04; 9.62] 1.15 [ -9.94; 12.25]
## UNKNOWN_STANDARD -0.29 [-12.18; 11.60] 0.57 [-12.75; 13.89]
## CTBS_NEURONAV DTMS_CM
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV CTBS_NEURONAV .
## DTMS_CM -4.47 [-18.61; 9.67] DTMS_CM
## HD-TDCS_10-20EEG -4.85 [-21.42; 11.72] -0.38 [-13.66; 12.89]
## HF-RTMS_10-20EEG -6.79 [-19.51; 5.93] -2.32 [-10.29; 5.64]
## HF-RTMS_CM -5.17 [-17.83; 7.49] -0.71 [ -8.57; 7.16]
## HF-RTMS_NA 0.04 [-13.72; 13.80] 4.50 [ -5.04; 14.04]
## HF-RTMS_NEURONAV 1.17 [-11.85; 14.19] 5.63 [ -2.80; 14.06]
## ITBS_10-20EEG -5.14 [-18.02; 7.74] -0.68 [ -8.89; 7.54]
## ITBS_CM -4.44 [-18.30; 9.42] 0.03 [ -9.65; 9.70]
## ITBS_NA -1.91 [-16.43; 12.61] 2.56 [ -8.05; 13.16]
## ITBS_NEURONAV -12.86 [-27.05; 1.34] -8.39 [-18.54; 1.76]
## LF-RTMS_10-10EEG -10.14 [-25.12; 4.84] -5.67 [-16.90; 5.55]
## LF-RTMS_10-20EEG -9.32 [-22.23; 3.59] -4.85 [-13.12; 3.41]
## LF-RTMS_CM 1.04 [-12.70; 14.79] 5.51 [ -4.01; 15.02]
## LF-RTMS_NEURONAV -2.01 [-18.78; 14.76] 2.46 [-11.07; 15.98]
## PRM-RTMS_NEURONAV -6.08 [-23.20; 11.04] -1.61 [-15.57; 12.34]
## SHAM -0.21 [-12.42; 12.00] 4.26 [ -2.87; 11.38]
## TACS_10-20EEG -2.93 [-16.56; 10.70] 1.53 [ -7.82; 10.88]
## TDCS_10-20EEG -2.03 [-14.56; 10.50] 2.44 [ -5.22; 10.09]
## UNKNOWN_STANDARD -2.61 [-17.14; 11.92] 1.86 [ -8.77; 12.48]
## HD-TDCS_10-20EEG HF-RTMS_10-20EEG
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-20EEG HD-TDCS_10-20EEG .
## HF-RTMS_10-20EEG -1.94 [-13.69; 9.82] HF-RTMS_10-20EEG
## HF-RTMS_CM -0.32 [-12.01; 11.36] 1.62 [ -3.25; 6.49]
## HF-RTMS_NA 4.89 [ -7.98; 17.76] 6.83 [ -0.45; 14.10]
## HF-RTMS_NEURONAV 6.02 [ -6.06; 18.09] 7.96 [ 2.21; 13.70]
## ITBS_10-20EEG -0.29 [-12.22; 11.63] 1.65 [ -3.77; 7.07]
## ITBS_CM 0.41 [-12.57; 13.39] 2.35 [ -5.11; 9.81]
## ITBS_NA 2.94 [-10.74; 16.62] 4.88 [ -3.75; 13.51]
## ITBS_NEURONAV -8.01 [-21.34; 5.33] -6.07 [-14.13; 2.00]
## LF-RTMS_10-10EEG -5.29 [-19.46; 8.88] -3.35 [-12.73; 6.03]
## LF-RTMS_10-20EEG -4.47 [-16.43; 7.49] -2.53 [ -8.03; 2.97]
## LF-RTMS_CM 5.89 [ -6.96; 18.75] 7.83 [ 0.59; 15.07]
## LF-RTMS_NEURONAV 2.84 [-13.21; 18.89] 4.78 [ -7.26; 16.82]
## PRM-RTMS_NEURONAV -1.23 [-17.64; 15.18] 0.71 [-11.80; 13.22]
## SHAM 4.64 [ -6.56; 15.84] 6.58 [ 3.02; 10.14]
## TACS_10-20EEG 1.92 [-10.82; 14.65] 3.86 [ -3.17; 10.88]
## TDCS_10-20EEG 2.82 [ -8.72; 14.37] 4.76 [ 0.23; 9.29]
## UNKNOWN_STANDARD 2.24 [-11.45; 15.93] 4.18 [ -4.46; 12.82]
## HF-RTMS_CM HF-RTMS_NA
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-20EEG . .
## HF-RTMS_10-20EEG . .
## HF-RTMS_CM HF-RTMS_CM .
## HF-RTMS_NA 5.21 [ -1.95; 12.37] HF-RTMS_NA
## HF-RTMS_NEURONAV 6.34 [ 0.74; 11.94] 1.13 [ -6.66; 8.91]
## ITBS_10-20EEG 0.03 [ -5.24; 5.30] -5.18 [-12.73; 2.36]
## ITBS_CM 0.73 [ -6.61; 8.08] -4.48 [-13.60; 4.64]
## ITBS_NA 3.26 [ -5.27; 11.79] -1.95 [-12.05; 8.15]
## ITBS_NEURONAV -7.68 [-15.64; 0.28] -12.89 [-22.51; -3.27]
## LF-RTMS_10-10EEG -4.97 [-14.26; 4.32] -10.18 [-20.93; 0.57]
## LF-RTMS_10-20EEG -4.15 [ -9.49; 1.20] -9.36 [-16.96; -1.75]
## LF-RTMS_CM 6.21 [ -0.91; 13.34] 1.00 [ -7.94; 9.95]
## LF-RTMS_NEURONAV 3.16 [ -8.81; 15.13] -2.05 [-15.18; 11.08]
## PRM-RTMS_NEURONAV -0.91 [-13.35; 11.54] -6.12 [-19.69; 7.45]
## SHAM 4.96 [ 1.64; 8.28] -0.25 [ -6.59; 6.09]
## TACS_10-20EEG 2.24 [ -4.67; 9.15] -2.97 [-11.74; 5.80]
## TDCS_10-20EEG 3.14 [ -1.20; 7.48] -2.07 [ -9.00; 4.86]
## UNKNOWN_STANDARD 2.56 [ -5.99; 11.11] -2.65 [-12.76; 7.46]
## HF-RTMS_NEURONAV ITBS_10-20EEG
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-20EEG . .
## HF-RTMS_10-20EEG . .
## HF-RTMS_CM . .
## HF-RTMS_NA . .
## HF-RTMS_NEURONAV HF-RTMS_NEURONAV .
## ITBS_10-20EEG -6.31 [-12.39; -0.22] ITBS_10-20EEG
## ITBS_CM -5.61 [-13.56; 2.35] 0.70 [ -7.02; 8.42]
## ITBS_NA -3.08 [-12.14; 5.98] 3.23 [ -5.62; 12.09]
## ITBS_NEURONAV -14.02 [-22.54; -5.50] -7.71 [-16.02; 0.59]
## LF-RTMS_10-10EEG -11.31 [-21.08; -1.53] -5.00 [-14.59; 4.59]
## LF-RTMS_10-20EEG -10.48 [-16.64; -4.33] -4.17 [-10.03; 1.68]
## LF-RTMS_CM -0.12 [ -7.87; 7.63] 6.18 [ -1.33; 13.70]
## LF-RTMS_NEURONAV -3.18 [-15.53; 9.17] 3.13 [ -9.07; 15.33]
## PRM-RTMS_NEURONAV -7.25 [-20.06; 5.57] -0.94 [-13.61; 11.73]
## SHAM -1.38 [ -5.89; 3.13] 4.93 [ 0.85; 9.02]
## TACS_10-20EEG -4.10 [-11.65; 3.45] 2.21 [ -5.09; 9.52]
## TDCS_10-20EEG -3.19 [ -8.50; 2.11] 3.11 [ -1.84; 8.07]
## UNKNOWN_STANDARD -3.78 [-12.85; 5.30] 2.53 [ -6.34; 11.41]
## ITBS_CM ITBS_NA
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-20EEG . .
## HF-RTMS_10-20EEG . .
## HF-RTMS_CM . .
## HF-RTMS_NA . .
## HF-RTMS_NEURONAV . .
## ITBS_10-20EEG . .
## ITBS_CM ITBS_CM .
## ITBS_NA 2.53 [ -7.70; 12.76] ITBS_NA
## ITBS_NEURONAV -8.42 [-18.17; 1.34] -10.95 [-21.62; -0.27]
## LF-RTMS_10-10EEG -5.70 [-16.57; 5.17] -8.23 [-19.94; 3.48]
## LF-RTMS_10-20EEG -4.88 [-12.65; 2.90] -7.41 [-16.31; 1.50]
## LF-RTMS_CM 5.48 [ -3.61; 14.57] 2.95 [ -7.12; 13.03]
## LF-RTMS_NEURONAV 2.43 [-10.80; 15.66] -0.10 [-14.03; 13.83]
## PRM-RTMS_NEURONAV -1.64 [-15.31; 12.03] -4.17 [-18.51; 10.17]
## SHAM 4.23 [ -2.32; 10.78] 1.70 [ -6.16; 9.56]
## TACS_10-20EEG 1.51 [ -7.41; 10.43] -1.02 [-10.94; 8.90]
## TDCS_10-20EEG 2.41 [ -4.71; 9.53] -0.12 [ -8.46; 8.22]
## UNKNOWN_STANDARD 1.83 [ -8.41; 12.07] -0.70 [-11.82; 10.42]
## ITBS_NEURONAV LF-RTMS_10-10EEG
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-20EEG . .
## HF-RTMS_10-20EEG . .
## HF-RTMS_CM . .
## HF-RTMS_NA . .
## HF-RTMS_NEURONAV . .
## ITBS_10-20EEG . .
## ITBS_CM . .
## ITBS_NA . .
## ITBS_NEURONAV ITBS_NEURONAV .
## LF-RTMS_10-10EEG 2.72 [ -8.58; 14.01] LF-RTMS_10-10EEG
## LF-RTMS_10-20EEG 3.54 [ -4.82; 11.90] 0.82 [ -8.81; 10.46]
## LF-RTMS_CM 13.90 [ 4.30; 23.49] 11.18 [ 0.46; 21.91]
## LF-RTMS_NEURONAV 10.85 [ -2.74; 24.43] 8.13 [ -6.27; 22.53]
## PRM-RTMS_NEURONAV 6.78 [ -7.23; 20.78] 4.06 [-10.74; 18.86]
## SHAM 12.65 [ 5.41; 19.88] 9.93 [ 1.25; 18.61]
## TACS_10-20EEG 9.92 [ 0.49; 19.36] 7.21 [ -3.37; 17.79]
## TDCS_10-20EEG 10.83 [ 3.07; 18.58] 8.11 [ -1.00; 17.23]
## UNKNOWN_STANDARD 10.25 [ -0.45; 20.94] 7.53 [ -4.19; 19.25]
## LF-RTMS_10-20EEG LF-RTMS_CM
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-20EEG . .
## HF-RTMS_10-20EEG . .
## HF-RTMS_CM . .
## HF-RTMS_NA . .
## HF-RTMS_NEURONAV . .
## ITBS_10-20EEG . .
## ITBS_CM . .
## ITBS_NA . .
## ITBS_NEURONAV . .
## LF-RTMS_10-10EEG . .
## LF-RTMS_10-20EEG LF-RTMS_10-20EEG .
## LF-RTMS_CM 10.36 [ 2.79; 17.93] LF-RTMS_CM
## LF-RTMS_NEURONAV 7.31 [ -4.93; 19.54] -3.05 [-16.16; 10.06]
## PRM-RTMS_NEURONAV 3.24 [ -9.47; 15.94] -7.12 [-20.67; 6.43]
## SHAM 9.11 [ 4.92; 13.30] -1.25 [ -7.56; 5.05]
## TACS_10-20EEG 6.39 [ -0.98; 13.75] -3.97 [-12.71; 4.77]
## TDCS_10-20EEG 7.29 [ 2.25; 12.32] -3.07 [ -9.96; 3.82]
## UNKNOWN_STANDARD 6.71 [ -2.21; 15.63] -3.65 [-13.74; 6.44]
## LF-RTMS_NEURONAV PRM-RTMS_NEURONAV
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-20EEG . .
## HF-RTMS_10-20EEG . .
## HF-RTMS_CM . .
## HF-RTMS_NA . .
## HF-RTMS_NEURONAV . .
## ITBS_10-20EEG . .
## ITBS_CM . .
## ITBS_NA . .
## ITBS_NEURONAV . .
## LF-RTMS_10-10EEG . .
## LF-RTMS_10-20EEG . .
## LF-RTMS_CM . .
## LF-RTMS_NEURONAV LF-RTMS_NEURONAV .
## PRM-RTMS_NEURONAV -4.07 [-20.68; 12.54] PRM-RTMS_NEURONAV
## SHAM 1.80 [ -9.70; 13.30] 5.87 [ -6.12; 17.86]
## TACS_10-20EEG -0.92 [-13.92; 12.07] 3.15 [-10.29; 16.58]
## TDCS_10-20EEG -0.02 [-11.85; 11.81] 4.05 [ -8.26; 16.37]
## UNKNOWN_STANDARD -0.60 [-14.54; 13.34] 3.47 [-10.88; 17.82]
## SHAM TACS_10-20EEG
## CTBS_10-20EEG 2.11 [ -6.79; 11.01] .
## CTBS_CM 2.97 [ -7.77; 13.71] .
## CTBS_NEURONAV -0.21 [-12.42; 12.00] .
## DTMS_CM 4.26 [ -2.87; 11.38] .
## HD-TDCS_10-20EEG 4.64 [ -6.56; 15.84] .
## HF-RTMS_10-20EEG 6.58 [ 3.02; 10.14] .
## HF-RTMS_CM 4.96 [ 1.64; 8.28] .
## HF-RTMS_NA -0.25 [ -6.59; 6.09] .
## HF-RTMS_NEURONAV -1.38 [ -5.89; 3.13] .
## ITBS_10-20EEG 4.93 [ 0.85; 9.02] .
## ITBS_CM 4.23 [ -2.32; 10.78] .
## ITBS_NA 1.70 [ -6.16; 9.56] .
## ITBS_NEURONAV 12.65 [ 5.41; 19.88] .
## LF-RTMS_10-10EEG 9.93 [ 1.25; 18.61] .
## LF-RTMS_10-20EEG 9.11 [ 4.92; 13.30] .
## LF-RTMS_CM -1.25 [ -7.56; 5.05] .
## LF-RTMS_NEURONAV 1.80 [ -9.70; 13.30] .
## PRM-RTMS_NEURONAV 5.87 [ -6.12; 17.86] .
## SHAM SHAM -2.72 [ -8.78; 3.33]
## TACS_10-20EEG -2.72 [ -8.78; 3.33] TACS_10-20EEG
## TDCS_10-20EEG -1.82 [ -4.61; 0.98] 0.90 [ -5.76; 7.57]
## UNKNOWN_STANDARD -2.40 [-10.28; 5.48] 0.32 [ -9.61; 10.26]
## TDCS_10-20EEG UNKNOWN_STANDARD
## CTBS_10-20EEG . .
## CTBS_CM . .
## CTBS_NEURONAV . .
## DTMS_CM . .
## HD-TDCS_10-20EEG . .
## HF-RTMS_10-20EEG . .
## HF-RTMS_CM . .
## HF-RTMS_NA . .
## HF-RTMS_NEURONAV . .
## ITBS_10-20EEG . .
## ITBS_CM . .
## ITBS_NA . .
## ITBS_NEURONAV . .
## LF-RTMS_10-10EEG . .
## LF-RTMS_10-20EEG . .
## LF-RTMS_CM . .
## LF-RTMS_NEURONAV . .
## PRM-RTMS_NEURONAV . .
## SHAM -1.82 [ -4.61; 0.98] -2.40 [-10.28; 5.48]
## TACS_10-20EEG . .
## TDCS_10-20EEG TDCS_10-20EEG .
## UNKNOWN_STANDARD -0.58 [ -8.94; 7.77] UNKNOWN_STANDARD
##
## Upper triangle: MD (95% CI); lower triangle: p-value
## Positive values favor the column-defining treatment
##
## Treatment Rankings (SUCRA values):
## SUCRA values not available in netrank output
##
## ==================================================
## Network Meta-Analysis for Global Cognition
## ==================================================
##
## Available treatments for Global Cognition NMA:
##
## HD-TDCS_10-20EEG HF-RTMS_10-20EEG HF-RTMS_CM HF-RTMS_NEURONAV
## 1 2 3 5
## ITBS_10-20EEG ITBS_NEURONAV LF-RTMS_10-10EEG SHAM
## 2 4 1 25
## TACS_10-20EEG TDCS_10-20 EEG TDCS_10-20EEG
## 1 1 5
##
## Running network meta-analysis for Global Cognition ...
##
## Summary of results:
## Original data:
##
## treat1
## francis, 2019_HF-RTMS_CM_GC_BACS Composite Score_1 HF-RTMS_CM
## guan, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 HF-RTMS_NEURONAV
## hu, 2023_LF-RTMS_10-10EEG_GC_MCCB-T_1 LF-RTMS_10-10EEG
## jeon, 2018_TDCS_10-20EEG_GC_MCCB Composite Score_1 SHAM
## li, 2024 - a_ITBS_10-20EEG_GC_MCCB_1 ITBS_10-20EEG
## li-b-lpc, 2024_ITBS_NEURONAV_GC_MCCB_1 ITBS_NEURONAV
## li-b-dlpfc, 2024_ITBS_NEURONAV_GC_MCCB_1 ITBS_NEURONAV
## lindenmayer, 2019_TDCS_10-20EEG_GC_MCCB_1 SHAM
## lisoni, 2022_TDCS_10-20 EEG_GC_BACS (Composite z-scores)_1 SHAM
## mao, 2023_HF-RTMS_CM_GC_RBANS_1 HF-RTMS_CM
## mellin-tacs, 2018_TACS_10-20EEG_GC_BACS_1 SHAM
## mellin-tdcs, 2018_TDCS_10-20EEG_GC_BACS_1 SHAM
## smith, 2015_TDCS_10-20EEG_GC_MCCB_1 SHAM
## smith, 2020_TDCS_10-20EEG_GC_MCCB_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_GC_MCCB_1 ITBS_10-20EEG
## wang, 2020_ITBS_NEURONAV_GC_MoCA_1 ITBS_NEURONAV
## wang, 2022_ITBS_NEURONAV_GC_MoCA_1 ITBS_NEURONAV
## wen, 2021_HF-RTMS_CM_GC_RBANS-T_1 HF-RTMS_CM
## xiu-10hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 HF-RTMS_NEURONAV
## xiu-20hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 HF-RTMS_NEURONAV
## xu, 2023_HD-TDCS_10-20EEG_GC_RBANS_1 HD-TDCS_10-20EEG
## ye-20hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 HF-RTMS_NEURONAV
## ye-10hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 HF-RTMS_NEURONAV
## zhou, 2024_HF-RTMS_10-20EEG_GC_RBANS-T_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_GC_MCCB Composite score_1 HF-RTMS_10-20EEG
## treat2
## francis, 2019_HF-RTMS_CM_GC_BACS Composite Score_1 SHAM
## guan, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 SHAM
## hu, 2023_LF-RTMS_10-10EEG_GC_MCCB-T_1 SHAM
## jeon, 2018_TDCS_10-20EEG_GC_MCCB Composite Score_1 TDCS_10-20EEG
## li, 2024 - a_ITBS_10-20EEG_GC_MCCB_1 SHAM
## li-b-lpc, 2024_ITBS_NEURONAV_GC_MCCB_1 SHAM
## li-b-dlpfc, 2024_ITBS_NEURONAV_GC_MCCB_1 SHAM
## lindenmayer, 2019_TDCS_10-20EEG_GC_MCCB_1 TDCS_10-20EEG
## lisoni, 2022_TDCS_10-20 EEG_GC_BACS (Composite z-scores)_1 TDCS_10-20 EEG
## mao, 2023_HF-RTMS_CM_GC_RBANS_1 SHAM
## mellin-tacs, 2018_TACS_10-20EEG_GC_BACS_1 TACS_10-20EEG
## mellin-tdcs, 2018_TDCS_10-20EEG_GC_BACS_1 TDCS_10-20EEG
## smith, 2015_TDCS_10-20EEG_GC_MCCB_1 TDCS_10-20EEG
## smith, 2020_TDCS_10-20EEG_GC_MCCB_1 TDCS_10-20EEG
## vergallito, 2024_ITBS_10-20EEG_GC_MCCB_1 SHAM
## wang, 2020_ITBS_NEURONAV_GC_MoCA_1 SHAM
## wang, 2022_ITBS_NEURONAV_GC_MoCA_1 SHAM
## wen, 2021_HF-RTMS_CM_GC_RBANS-T_1 SHAM
## xiu-10hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 SHAM
## xiu-20hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 SHAM
## xu, 2023_HD-TDCS_10-20EEG_GC_RBANS_1 SHAM
## ye-20hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 SHAM
## ye-10hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 SHAM
## zhou, 2024_HF-RTMS_10-20EEG_GC_RBANS-T_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_GC_MCCB Composite score_1 SHAM
## TE seTE
## francis, 2019_HF-RTMS_CM_GC_BACS Composite Score_1 2.7200 4.0745
## guan, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 3.6000 3.4926
## hu, 2023_LF-RTMS_10-10EEG_GC_MCCB-T_1 4.1200 1.3586
## jeon, 2018_TDCS_10-20EEG_GC_MCCB Composite Score_1 -2.7100 3.2747
## li, 2024 - a_ITBS_10-20EEG_GC_MCCB_1 3.1800 6.6703
## li-b-lpc, 2024_ITBS_NEURONAV_GC_MCCB_1 -4.2100 2.6909
## li-b-dlpfc, 2024_ITBS_NEURONAV_GC_MCCB_1 -0.0400 2.8427
## lindenmayer, 2019_TDCS_10-20EEG_GC_MCCB_1 -1.5200 6.0027
## lisoni, 2022_TDCS_10-20 EEG_GC_BACS (Composite z-scores)_1 -0.0100 0.1978
## mao, 2023_HF-RTMS_CM_GC_RBANS_1 5.6200 2.6465
## mellin-tacs, 2018_TACS_10-20EEG_GC_BACS_1 2.2000 3.2983
## mellin-tdcs, 2018_TDCS_10-20EEG_GC_BACS_1 -1.2200 3.9736
## smith, 2015_TDCS_10-20EEG_GC_MCCB_1 -4.3500 4.1163
## smith, 2020_TDCS_10-20EEG_GC_MCCB_1 1.2300 2.1095
## vergallito, 2024_ITBS_10-20EEG_GC_MCCB_1 1.5700 5.0091
## wang, 2020_ITBS_NEURONAV_GC_MoCA_1 0.2200 0.4892
## wang, 2022_ITBS_NEURONAV_GC_MoCA_1 0.1590 0.4986
## wen, 2021_HF-RTMS_CM_GC_RBANS-T_1 8.1000 2.8165
## xiu-10hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 0.1000 2.6031
## xiu-20hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 4.5000 2.7838
## xu, 2023_HD-TDCS_10-20EEG_GC_RBANS_1 0.4100 2.5523
## ye-20hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 1.7000 3.1723
## ye-10hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 1.0000 2.8245
## zhou, 2024_HF-RTMS_10-20EEG_GC_RBANS-T_1 7.6000 2.0139
## zhuo, 2019_HF-RTMS_10-20EEG_GC_MCCB Composite score_1 -2.5300 1.5850
##
## Number of treatment arms (by study):
## narms
## francis, 2019_HF-RTMS_CM_GC_BACS Composite Score_1 2
## guan, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 2
## hu, 2023_LF-RTMS_10-10EEG_GC_MCCB-T_1 2
## jeon, 2018_TDCS_10-20EEG_GC_MCCB Composite Score_1 2
## li, 2024 - a_ITBS_10-20EEG_GC_MCCB_1 2
## li-b-lpc, 2024_ITBS_NEURONAV_GC_MCCB_1 2
## li-b-dlpfc, 2024_ITBS_NEURONAV_GC_MCCB_1 2
## lindenmayer, 2019_TDCS_10-20EEG_GC_MCCB_1 2
## lisoni, 2022_TDCS_10-20 EEG_GC_BACS (Composite z-scores)_1 2
## mao, 2023_HF-RTMS_CM_GC_RBANS_1 2
## mellin-tacs, 2018_TACS_10-20EEG_GC_BACS_1 2
## mellin-tdcs, 2018_TDCS_10-20EEG_GC_BACS_1 2
## smith, 2015_TDCS_10-20EEG_GC_MCCB_1 2
## smith, 2020_TDCS_10-20EEG_GC_MCCB_1 2
## vergallito, 2024_ITBS_10-20EEG_GC_MCCB_1 2
## wang, 2020_ITBS_NEURONAV_GC_MoCA_1 2
## wang, 2022_ITBS_NEURONAV_GC_MoCA_1 2
## wen, 2021_HF-RTMS_CM_GC_RBANS-T_1 2
## xiu-10hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 2
## xiu-20hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 2
## xu, 2023_HD-TDCS_10-20EEG_GC_RBANS_1 2
## ye-20hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 2
## ye-10hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 2
## zhou, 2024_HF-RTMS_10-20EEG_GC_RBANS-T_1 2
## zhuo, 2019_HF-RTMS_10-20EEG_GC_MCCB Composite score_1 2
##
## Results (random effects model):
##
## treat1
## francis, 2019_HF-RTMS_CM_GC_BACS Composite Score_1 HF-RTMS_CM
## guan, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 HF-RTMS_NEURONAV
## hu, 2023_LF-RTMS_10-10EEG_GC_MCCB-T_1 LF-RTMS_10-10EEG
## jeon, 2018_TDCS_10-20EEG_GC_MCCB Composite Score_1 SHAM
## li, 2024 - a_ITBS_10-20EEG_GC_MCCB_1 ITBS_10-20EEG
## li-b-lpc, 2024_ITBS_NEURONAV_GC_MCCB_1 ITBS_NEURONAV
## li-b-dlpfc, 2024_ITBS_NEURONAV_GC_MCCB_1 ITBS_NEURONAV
## lindenmayer, 2019_TDCS_10-20EEG_GC_MCCB_1 SHAM
## lisoni, 2022_TDCS_10-20 EEG_GC_BACS (Composite z-scores)_1 SHAM
## mao, 2023_HF-RTMS_CM_GC_RBANS_1 HF-RTMS_CM
## mellin-tacs, 2018_TACS_10-20EEG_GC_BACS_1 SHAM
## mellin-tdcs, 2018_TDCS_10-20EEG_GC_BACS_1 SHAM
## smith, 2015_TDCS_10-20EEG_GC_MCCB_1 SHAM
## smith, 2020_TDCS_10-20EEG_GC_MCCB_1 SHAM
## vergallito, 2024_ITBS_10-20EEG_GC_MCCB_1 ITBS_10-20EEG
## wang, 2020_ITBS_NEURONAV_GC_MoCA_1 ITBS_NEURONAV
## wang, 2022_ITBS_NEURONAV_GC_MoCA_1 ITBS_NEURONAV
## wen, 2021_HF-RTMS_CM_GC_RBANS-T_1 HF-RTMS_CM
## xiu-10hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 HF-RTMS_NEURONAV
## xiu-20hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 HF-RTMS_NEURONAV
## xu, 2023_HD-TDCS_10-20EEG_GC_RBANS_1 HD-TDCS_10-20EEG
## ye-20hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 HF-RTMS_NEURONAV
## ye-10hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 HF-RTMS_NEURONAV
## zhou, 2024_HF-RTMS_10-20EEG_GC_RBANS-T_1 HF-RTMS_10-20EEG
## zhuo, 2019_HF-RTMS_10-20EEG_GC_MCCB Composite score_1 HF-RTMS_10-20EEG
## treat2
## francis, 2019_HF-RTMS_CM_GC_BACS Composite Score_1 SHAM
## guan, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 SHAM
## hu, 2023_LF-RTMS_10-10EEG_GC_MCCB-T_1 SHAM
## jeon, 2018_TDCS_10-20EEG_GC_MCCB Composite Score_1 TDCS_10-20EEG
## li, 2024 - a_ITBS_10-20EEG_GC_MCCB_1 SHAM
## li-b-lpc, 2024_ITBS_NEURONAV_GC_MCCB_1 SHAM
## li-b-dlpfc, 2024_ITBS_NEURONAV_GC_MCCB_1 SHAM
## lindenmayer, 2019_TDCS_10-20EEG_GC_MCCB_1 TDCS_10-20EEG
## lisoni, 2022_TDCS_10-20 EEG_GC_BACS (Composite z-scores)_1 TDCS_10-20 EEG
## mao, 2023_HF-RTMS_CM_GC_RBANS_1 SHAM
## mellin-tacs, 2018_TACS_10-20EEG_GC_BACS_1 TACS_10-20EEG
## mellin-tdcs, 2018_TDCS_10-20EEG_GC_BACS_1 TDCS_10-20EEG
## smith, 2015_TDCS_10-20EEG_GC_MCCB_1 TDCS_10-20EEG
## smith, 2020_TDCS_10-20EEG_GC_MCCB_1 TDCS_10-20EEG
## vergallito, 2024_ITBS_10-20EEG_GC_MCCB_1 SHAM
## wang, 2020_ITBS_NEURONAV_GC_MoCA_1 SHAM
## wang, 2022_ITBS_NEURONAV_GC_MoCA_1 SHAM
## wen, 2021_HF-RTMS_CM_GC_RBANS-T_1 SHAM
## xiu-10hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 SHAM
## xiu-20hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 SHAM
## xu, 2023_HD-TDCS_10-20EEG_GC_RBANS_1 SHAM
## ye-20hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 SHAM
## ye-10hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 SHAM
## zhou, 2024_HF-RTMS_10-20EEG_GC_RBANS-T_1 SHAM
## zhuo, 2019_HF-RTMS_10-20EEG_GC_MCCB Composite score_1 SHAM
## MD
## francis, 2019_HF-RTMS_CM_GC_BACS Composite Score_1 5.9909
## guan, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 2.0518
## hu, 2023_LF-RTMS_10-10EEG_GC_MCCB-T_1 4.1200
## jeon, 2018_TDCS_10-20EEG_GC_MCCB Composite Score_1 -0.9233
## li, 2024 - a_ITBS_10-20EEG_GC_MCCB_1 2.1593
## li-b-lpc, 2024_ITBS_NEURONAV_GC_MCCB_1 -0.1842
## li-b-dlpfc, 2024_ITBS_NEURONAV_GC_MCCB_1 -0.1842
## lindenmayer, 2019_TDCS_10-20EEG_GC_MCCB_1 -0.9233
## lisoni, 2022_TDCS_10-20 EEG_GC_BACS (Composite z-scores)_1 -0.0100
## mao, 2023_HF-RTMS_CM_GC_RBANS_1 5.9909
## mellin-tacs, 2018_TACS_10-20EEG_GC_BACS_1 2.2000
## mellin-tdcs, 2018_TDCS_10-20EEG_GC_BACS_1 -0.9233
## smith, 2015_TDCS_10-20EEG_GC_MCCB_1 -0.9233
## smith, 2020_TDCS_10-20EEG_GC_MCCB_1 -0.9233
## vergallito, 2024_ITBS_10-20EEG_GC_MCCB_1 2.1593
## wang, 2020_ITBS_NEURONAV_GC_MoCA_1 -0.1842
## wang, 2022_ITBS_NEURONAV_GC_MoCA_1 -0.1842
## wen, 2021_HF-RTMS_CM_GC_RBANS-T_1 5.9909
## xiu-10hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 2.0518
## xiu-20hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 2.0518
## xu, 2023_HD-TDCS_10-20EEG_GC_RBANS_1 0.4100
## ye-20hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 2.0518
## ye-10hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 2.0518
## zhou, 2024_HF-RTMS_10-20EEG_GC_RBANS-T_1 1.7038
## zhuo, 2019_HF-RTMS_10-20EEG_GC_MCCB Composite score_1 1.7038
## 95%-CI
## francis, 2019_HF-RTMS_CM_GC_BACS Composite Score_1 [ 2.2946; 9.6872]
## guan, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 [-0.7254; 4.8290]
## hu, 2023_LF-RTMS_10-10EEG_GC_MCCB-T_1 [ 0.5789; 7.6611]
## jeon, 2018_TDCS_10-20EEG_GC_MCCB Composite Score_1 [-4.0536; 2.2070]
## li, 2024 - a_ITBS_10-20EEG_GC_MCCB_1 [-5.8755; 10.1942]
## li-b-lpc, 2024_ITBS_NEURONAV_GC_MCCB_1 [-1.8268; 1.4583]
## li-b-dlpfc, 2024_ITBS_NEURONAV_GC_MCCB_1 [-1.8268; 1.4583]
## lindenmayer, 2019_TDCS_10-20EEG_GC_MCCB_1 [-4.0536; 2.2070]
## lisoni, 2022_TDCS_10-20 EEG_GC_BACS (Composite z-scores)_1 [-2.3763; 2.3563]
## mao, 2023_HF-RTMS_CM_GC_RBANS_1 [ 2.2946; 9.6872]
## mellin-tacs, 2018_TACS_10-20EEG_GC_BACS_1 [-4.6731; 9.0731]
## mellin-tdcs, 2018_TDCS_10-20EEG_GC_BACS_1 [-4.0536; 2.2070]
## smith, 2015_TDCS_10-20EEG_GC_MCCB_1 [-4.0536; 2.2070]
## smith, 2020_TDCS_10-20EEG_GC_MCCB_1 [-4.0536; 2.2070]
## vergallito, 2024_ITBS_10-20EEG_GC_MCCB_1 [-5.8755; 10.1942]
## wang, 2020_ITBS_NEURONAV_GC_MoCA_1 [-1.8268; 1.4583]
## wang, 2022_ITBS_NEURONAV_GC_MoCA_1 [-1.8268; 1.4583]
## wen, 2021_HF-RTMS_CM_GC_RBANS-T_1 [ 2.2946; 9.6872]
## xiu-10hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 [-0.7254; 4.8290]
## xiu-20hz, 2020_HF-RTMS_NEURONAV_GC_RBANS-T_1 [-0.7254; 4.8290]
## xu, 2023_HD-TDCS_10-20EEG_GC_RBANS_1 [-5.1102; 5.9302]
## ye-20hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 [-0.7254; 4.8290]
## ye-10hz, 2024_HF-RTMS_NEURONAV_GC_RBANS-T_1 [-0.7254; 4.8290]
## zhou, 2024_HF-RTMS_10-20EEG_GC_RBANS-T_1 [-1.2608; 4.6684]
## zhuo, 2019_HF-RTMS_10-20EEG_GC_MCCB Composite score_1 [-1.2608; 4.6684]
##
## Number of studies: k = 25
## Number of pairwise comparisons: m = 25
## Number of treatments: n = 11
## Number of designs: d = 10
##
## Random effects model
##
## Treatment estimate (sm = 'MD', comparison: other treatments vs 'SHAM'):
## MD 95%-CI z p-value
## HD-TDCS_10-20EEG 0.4100 [-5.1102; 5.9302] 0.15 0.8843
## HF-RTMS_10-20EEG 1.7038 [-1.2608; 4.6684] 1.13 0.2600
## HF-RTMS_CM 5.9909 [ 2.2946; 9.6872] 3.18 0.0015
## HF-RTMS_NEURONAV 2.0518 [-0.7254; 4.8290] 1.45 0.1476
## ITBS_10-20EEG 2.1593 [-5.8755; 10.1942] 0.53 0.5984
## ITBS_NEURONAV -0.1842 [-1.8268; 1.4583] -0.22 0.8260
## LF-RTMS_10-10EEG 4.1200 [ 0.5789; 7.6611] 2.28 0.0226
## SHAM . . . .
## TACS_10-20EEG -2.2000 [-9.0731; 4.6731] -0.63 0.5304
## TDCS_10-20 EEG 0.0100 [-2.3563; 2.3763] 0.01 0.9934
## TDCS_10-20EEG 0.9233 [-2.2070; 4.0536] 0.58 0.5632
##
## Quantifying heterogeneity / inconsistency:
## tau^2 = 1.4185; tau = 1.1910; I^2 = 35.5% [0.0%; 64.5%]
##
## Tests of heterogeneity (within designs) and inconsistency (between designs):
## Q d.f. p-value
## Total 23.24 15 0.0791
## Within designs 23.24 15 0.0791
## Between designs 0.00 0 --
##
## Details of network meta-analysis methods:
## - Frequentist graph-theoretical approach
## - DerSimonian-Laird estimator for tau^2
## - Calculation of I^2 based on Q
##
## Forest Plot:
##
## Network Graph:
##
## League Table for Global Cognition :
## HD-TDCS_10-20EEG HF-RTMS_10-20EEG
## HD-TDCS_10-20EEG HD-TDCS_10-20EEG .
## HF-RTMS_10-20EEG -1.29 [ -7.56; 4.97] HF-RTMS_10-20EEG
## HF-RTMS_CM -5.58 [-12.22; 1.06] -4.29 [ -9.03; 0.45]
## HF-RTMS_NEURONAV -1.64 [ -7.82; 4.54] -0.35 [ -4.41; 3.71]
## ITBS_10-20EEG -1.75 [-11.50; 8.00] -0.46 [ -9.02; 8.11]
## ITBS_NEURONAV 0.59 [ -5.17; 6.35] 1.89 [ -1.50; 5.28]
## LF-RTMS_10-10EEG -3.71 [-10.27; 2.85] -2.42 [ -7.03; 2.20]
## SHAM 0.41 [ -5.11; 5.93] 1.70 [ -1.26; 4.67]
## TACS_10-20EEG 2.61 [ -6.21; 11.43] 3.90 [ -3.58; 11.39]
## TDCS_10-20 EEG 0.40 [ -5.61; 6.41] 1.69 [ -2.10; 5.49]
## TDCS_10-20EEG -0.51 [ -6.86; 5.83] 0.78 [ -3.53; 5.09]
## HF-RTMS_CM HF-RTMS_NEURONAV
## HD-TDCS_10-20EEG . .
## HF-RTMS_10-20EEG . .
## HF-RTMS_CM HF-RTMS_CM .
## HF-RTMS_NEURONAV 3.94 [ -0.68; 8.56] HF-RTMS_NEURONAV
## ITBS_10-20EEG 3.83 [ -5.01; 12.68] -0.11 [ -8.61; 8.39]
## ITBS_NEURONAV 6.18 [ 2.13; 10.22] 2.24 [ -0.99; 5.46]
## LF-RTMS_10-10EEG 1.87 [ -3.25; 6.99] -2.07 [ -6.57; 2.43]
## SHAM 5.99 [ 2.29; 9.69] 2.05 [ -0.73; 4.83]
## TACS_10-20EEG 8.19 [ 0.39; 15.99] 4.25 [ -3.16; 11.66]
## TDCS_10-20 EEG 5.98 [ 1.59; 10.37] 2.04 [ -1.61; 5.69]
## TDCS_10-20EEG 5.07 [ 0.22; 9.91] 1.13 [ -3.06; 5.31]
## ITBS_10-20EEG ITBS_NEURONAV
## HD-TDCS_10-20EEG . .
## HF-RTMS_10-20EEG . .
## HF-RTMS_CM . .
## HF-RTMS_NEURONAV . .
## ITBS_10-20EEG ITBS_10-20EEG .
## ITBS_NEURONAV 2.34 [ -5.86; 10.54] ITBS_NEURONAV
## LF-RTMS_10-10EEG -1.96 [-10.74; 6.82] -4.30 [ -8.21; -0.40]
## SHAM 2.16 [ -5.88; 10.19] -0.18 [ -1.83; 1.46]
## TACS_10-20EEG 4.36 [ -6.21; 14.93] 2.02 [ -5.05; 9.08]
## TDCS_10-20 EEG 2.15 [ -6.23; 10.53] -0.19 [ -3.07; 2.69]
## TDCS_10-20EEG 1.24 [ -7.39; 9.86] -1.11 [ -4.64; 2.43]
## LF-RTMS_10-10EEG SHAM
## HD-TDCS_10-20EEG . 0.41 [ -5.11; 5.93]
## HF-RTMS_10-20EEG . 1.70 [ -1.26; 4.67]
## HF-RTMS_CM . 5.99 [ 2.29; 9.69]
## HF-RTMS_NEURONAV . 2.05 [ -0.73; 4.83]
## ITBS_10-20EEG . 2.16 [ -5.88; 10.19]
## ITBS_NEURONAV . -0.18 [ -1.83; 1.46]
## LF-RTMS_10-10EEG LF-RTMS_10-10EEG 4.12 [ 0.58; 7.66]
## SHAM 4.12 [ 0.58; 7.66] SHAM
## TACS_10-20EEG 6.32 [ -1.41; 14.05] 2.20 [ -4.67; 9.07]
## TDCS_10-20 EEG 4.11 [ -0.15; 8.37] -0.01 [ -2.38; 2.36]
## TDCS_10-20EEG 3.20 [ -1.53; 7.92] -0.92 [ -4.05; 2.21]
## TACS_10-20EEG TDCS_10-20 EEG
## HD-TDCS_10-20EEG . .
## HF-RTMS_10-20EEG . .
## HF-RTMS_CM . .
## HF-RTMS_NEURONAV . .
## ITBS_10-20EEG . .
## ITBS_NEURONAV . .
## LF-RTMS_10-10EEG . .
## SHAM 2.20 [ -4.67; 9.07] -0.01 [ -2.38; 2.36]
## TACS_10-20EEG TACS_10-20EEG .
## TDCS_10-20 EEG -2.21 [ -9.48; 5.06] TDCS_10-20 EEG
## TDCS_10-20EEG -3.12 [-10.68; 4.43] -0.91 [ -4.84; 3.01]
## TDCS_10-20EEG
## HD-TDCS_10-20EEG .
## HF-RTMS_10-20EEG .
## HF-RTMS_CM .
## HF-RTMS_NEURONAV .
## ITBS_10-20EEG .
## ITBS_NEURONAV .
## LF-RTMS_10-10EEG .
## SHAM -0.92 [ -4.05; 2.21]
## TACS_10-20EEG .
## TDCS_10-20 EEG .
## TDCS_10-20EEG TDCS_10-20EEG
##
## Upper triangle: MD (95% CI); lower triangle: p-value
## Positive values favor the column-defining treatment
##
## Treatment Rankings (SUCRA values):
## SUCRA values not available in netrank output
##
## ==================================================
## Cross-Domain Comparison
## ==================================================
## No SUCRA data available for cross-domain comparison
##
## ==================================================
## Clinical Recommendations
## ==================================================
##
## ==================================================
## Targeting Method Analysis
## ==================================================
## Studies by targeting method:
## - 10-10EEG: 16 comparisons
## - 10-20 EEG: 10 comparisons
## - 10-20EEG: 354 comparisons
## - 10-20EG: 4 comparisons
## - CM: 124 comparisons
## - NA: 16 comparisons
## - NEURONAV: 148 comparisons
## - STANDARD: 5 comparisons
##
## ==================================================
## Sensitivity Analyses
## ==================================================
##
## ==================================================
## Sensitivity Analyses for All Domains
## ==================================================
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
##
## Data preparation summary for all domains :
## - Total studies considered: 128
## - Studies with missing technique data (auto-inferred): 5
## - Studies with invalid/missing outcome data: 0
## - Total comparisons successfully prepared: 677
##
## 1. Original Analysis
##
## Available treatments for All Domains NMA:
##
## CTBS_10-20EEG CTBS_CM CTBS_NEURONAV DTMS_CM
## 9 5 6 19
## HD-TDCS_10-10EEG HD-TDCS_10-20EEG HF-RTMS_10-20EEG HF-RTMS_CM
## 4 5 73 78
## HF-RTMS_NA HF-RTMS_NEURONAV ITBS_10-20EEG ITBS_CM
## 10 64 32 9
## ITBS_NA ITBS_NEURONAV LF-RTMS_10-10EEG LF-RTMS_10-20EEG
## 6 65 12 54
## LF-RTMS_CM LF-RTMS_NEURONAV PRM-RTMS_NEURONAV SHAM
## 13 9 4 677
## TACS_10-20EEG TDCS_10-20 EEG TDCS_10-20EEG TDCS_10-20EG
## 13 10 168 4
## UNKNOWN_STANDARD
## 5
##
## Running network meta-analysis for All Domains ...
##
## 2. Influence Diagnostics
##
## Performing influence diagnostics for All Domains ...
## Not enough treatment effects for meaningful influence analysis
##
## 3. Small Sample Size Sensitivity Analysis
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
##
## Warnings during NMA data preparation for all domains :
## - Study bais, 2014 - l excluded due to small sample size
## - Study bais, 2014 - l excluded due to small sample size
## - Study bais, 2014 - l excluded due to small sample size
## - Study bais, 2014 - l excluded due to small sample size
## - Study bais, 2014 - l excluded due to small sample size
## ... and 316 more warnings
##
## Data preparation summary for all domains :
## - Total studies considered: 128
## - Studies with missing technique data (auto-inferred): 5
## - Studies with invalid/missing outcome data: 0
## - Total comparisons successfully prepared: 356
## Running NMA after excluding studies with n < 20...
## Included 356 comparisons after filtering (vs. 677 in original analysis)
##
## Available treatments for All Domains - Large Studies Only NMA:
##
## CTBS_10-20EEG CTBS_CM DTMS_CM HD-TDCS_10-20EEG
## 9 5 4 5
## HF-RTMS_10-20EEG HF-RTMS_CM HF-RTMS_NA HF-RTMS_NEURONAV
## 48 29 1 43
## ITBS_10-20EEG ITBS_CM ITBS_NA ITBS_NEURONAV
## 15 6 6 65
## LF-RTMS_10-10EEG LF-RTMS_10-20EEG LF-RTMS_NEURONAV SHAM
## 12 24 2 356
## TDCS_10-20 EEG TDCS_10-20EEG UNKNOWN_STANDARD
## 10 67 5
##
## Running network meta-analysis for All Domains - Large Studies Only ...
##
## Comparing treatment rankings with/without small studies:
##
## 4. Risk of Bias Stratification
##
## Analysis for Low risk of bias studies ( 23 studies):
##
## Warnings during NMA data preparation for all domains :
## - Study bais, 2014 - l excluded due to risk of bias level
## - Study bais, 2014 - bi excluded due to risk of bias level
## - Study barr, 2011 excluded due to risk of bias level
## - Study barr, 2013 excluded due to risk of bias level
## - Study barr, 2012 excluded due to risk of bias level
## ... and 97 more warnings
##
## Data preparation summary for all domains :
## - Total studies considered: 128
## - Studies with missing technique data (auto-inferred): 0
## - Studies with invalid/missing outcome data: 0
## - Total comparisons successfully prepared: 166
##
## Available treatments for All Domains - Low Risk of Bias NMA:
##
## CTBS_10-20EEG HD-TDCS_10-20EEG HF-RTMS_10-20EEG HF-RTMS_CM
## 3 5 38 7
## HF-RTMS_NA HF-RTMS_NEURONAV ITBS_10-20EEG ITBS_CM
## 1 20 5 1
## ITBS_NA ITBS_NEURONAV LF-RTMS_10-10EEG LF-RTMS_10-20EEG
## 6 34 12 12
## SHAM TDCS_10-20EEG
## 166 22
##
## Running network meta-analysis for All Domains - Low Risk of Bias ...
##
## Comparing treatment rankings for Low risk of bias vs overall:
##
## Analysis for Moderate risk of bias studies ( 37 studies):
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
##
## Warnings during NMA data preparation for all domains :
## - Study bais, 2014 - l excluded due to risk of bias level
## - Study bais, 2014 - bi excluded due to risk of bias level
## - Study barr, 2011 excluded due to risk of bias level
## - Study barr, 2013 excluded due to risk of bias level
## - Study barr, 2012 excluded due to risk of bias level
## ... and 81 more warnings
##
## Data preparation summary for all domains :
## - Total studies considered: 128
## - Studies with missing technique data (auto-inferred): 5
## - Studies with invalid/missing outcome data: 0
## - Total comparisons successfully prepared: 236
##
## Available treatments for All Domains - Moderate Risk of Bias NMA:
##
## CTBS_10-20EEG CTBS_CM DTMS_CM HF-RTMS_10-20EEG
## 6 5 4 7
## HF-RTMS_CM HF-RTMS_NA HF-RTMS_NEURONAV ITBS_10-20EEG
## 30 9 34 10
## ITBS_CM ITBS_NEURONAV LF-RTMS_10-20EEG SHAM
## 5 31 14 236
## TACS_10-20EEG TDCS_10-20 EEG TDCS_10-20EEG UNKNOWN_STANDARD
## 3 10 63 5
##
## Running network meta-analysis for All Domains - Moderate Risk of Bias ...
##
## Comparing treatment rankings for Moderate risk of bias vs overall:
##
## Analysis for High risk of bias studies ( 57 studies):
##
## Warnings during NMA data preparation for all domains :
## - Study basavaraju, 2021 excluded due to risk of bias level
## - Study bulubas, 2021 excluded due to risk of bias level
## - Study chang-a, 2021 excluded due to risk of bias level
## - Study chang, 2019 excluded due to risk of bias level
## - Study chang, 2020 excluded due to risk of bias level
## ... and 63 more warnings
##
## Data preparation summary for all domains :
## - Total studies considered: 128
## - Studies with missing technique data (auto-inferred): 0
## - Studies with invalid/missing outcome data: 0
## - Total comparisons successfully prepared: 275
##
## Available treatments for All Domains - High Risk of Bias NMA:
##
## CTBS_NEURONAV DTMS_CM HD-TDCS_10-10EEG HF-RTMS_10-20EEG
## 6 15 4 28
## HF-RTMS_CM HF-RTMS_NEURONAV ITBS_10-20EEG ITBS_CM
## 41 10 17 3
## LF-RTMS_10-20EEG LF-RTMS_CM LF-RTMS_NEURONAV PRM-RTMS_NEURONAV
## 28 13 9 4
## SHAM TACS_10-20EEG TDCS_10-20EEG TDCS_10-20EG
## 275 10 83 4
##
## Running network meta-analysis for All Domains - High Risk of Bias ...
##
## Comparing treatment rankings for High risk of bias vs overall:
##
## ==================================================
## Sensitivity Analyses for positive_symptoms
## ==================================================
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
##
## Data preparation summary for positive_symptoms :
## - Total studies considered: 91
## - Studies with missing technique data (auto-inferred): 1
## - Studies with invalid/missing outcome data: 0
## - Total comparisons successfully prepared: 119
##
## 1. Original Analysis
##
## Available treatments for positive_symptoms NMA:
##
## CTBS_10-20EEG CTBS_CM CTBS_NEURONAV DTMS_CM
## 6 2 1 2
## HD-TDCS_10-10EEG HD-TDCS_10-20EEG HF-RTMS_10-20EEG HF-RTMS_CM
## 1 1 8 12
## HF-RTMS_NA HF-RTMS_NEURONAV ITBS_10-20EEG ITBS_CM
## 1 8 4 1
## ITBS_NA ITBS_NEURONAV LF-RTMS_10-10EEG LF-RTMS_10-20EEG
## 1 5 1 20
## LF-RTMS_CM LF-RTMS_NEURONAV PRM-RTMS_NEURONAV SHAM
## 4 7 3 119
## TACS_10-20EEG TDCS_10-20EEG TDCS_10-20EG UNKNOWN_STANDARD
## 4 24 2 1
##
## Running network meta-analysis for positive_symptoms ...
##
## 2. Influence Diagnostics
##
## Performing influence diagnostics for positive_symptoms ...
## Not enough treatment effects for meaningful influence analysis
##
## 3. Small Sample Size Sensitivity Analysis
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
##
## Warnings during NMA data preparation for positive_symptoms :
## - Study bais, 2014 - l excluded due to small sample size
## - Study bais, 2014 - l excluded due to small sample size
## - Study bais, 2014 - l excluded due to small sample size
## - Study bais, 2014 - bi excluded due to small sample size
## - Study bais, 2014 - bi excluded due to small sample size
## ... and 65 more warnings
##
## Data preparation summary for positive_symptoms :
## - Total studies considered: 91
## - Studies with missing technique data (auto-inferred): 1
## - Studies with invalid/missing outcome data: 0
## - Total comparisons successfully prepared: 49
## Running NMA after excluding studies with n < 20...
## Included 49 comparisons after filtering (vs. 119 in original analysis)
##
## Available treatments for positive_symptoms - Large Studies Only NMA:
##
## CTBS_10-20EEG CTBS_CM DTMS_CM HD-TDCS_10-20EEG
## 6 2 1 1
## HF-RTMS_10-20EEG HF-RTMS_CM HF-RTMS_NEURONAV ITBS_10-20EEG
## 5 3 4 2
## ITBS_CM ITBS_NA ITBS_NEURONAV LF-RTMS_10-10EEG
## 1 1 5 1
## LF-RTMS_10-20EEG LF-RTMS_NEURONAV SHAM TDCS_10-20EEG
## 7 2 49 7
## UNKNOWN_STANDARD
## 1
##
## Running network meta-analysis for positive_symptoms - Large Studies Only ...
##
## Comparing treatment rankings with/without small studies:
##
## 4. Risk of Bias Stratification
##
## Analysis for Low risk of bias studies ( 15 studies):
##
## Warnings during NMA data preparation for positive_symptoms :
## - Study bais, 2014 - l excluded due to risk of bias level
## - Study bais, 2014 - bi excluded due to risk of bias level
## - Study barr, 2012 excluded due to risk of bias level
## - Study blumberger, 2012 excluded due to risk of bias level
## - Study blumberger-prm, 2012 excluded due to risk of bias level
## ... and 69 more warnings
##
## Data preparation summary for positive_symptoms :
## - Total studies considered: 91
## - Studies with missing technique data (auto-inferred): 0
## - Studies with invalid/missing outcome data: 0
## - Total comparisons successfully prepared: 18
##
## Available treatments for positive_symptoms - Low Risk of Bias NMA:
##
## CTBS_10-20EEG HD-TDCS_10-20EEG HF-RTMS_10-20EEG HF-RTMS_CM
## 3 1 3 1
## HF-RTMS_NEURONAV ITBS_10-20EEG ITBS_NA ITBS_NEURONAV
## 2 1 1 1
## LF-RTMS_10-10EEG LF-RTMS_10-20EEG SHAM TDCS_10-20EEG
## 1 1 18 3
##
## Running network meta-analysis for positive_symptoms - Low Risk of Bias ...
##
## Comparing treatment rankings for Low risk of bias vs overall:
##
## Analysis for Moderate risk of bias studies ( 28 studies):
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
##
## Warnings during NMA data preparation for positive_symptoms :
## - Study bais, 2014 - l excluded due to risk of bias level
## - Study bais, 2014 - bi excluded due to risk of bias level
## - Study barr, 2012 excluded due to risk of bias level
## - Study basavaraju, 2021 excluded due to risk of bias level
## - Study blumberger, 2012 excluded due to risk of bias level
## ... and 56 more warnings
##
## Data preparation summary for positive_symptoms :
## - Total studies considered: 91
## - Studies with missing technique data (auto-inferred): 1
## - Studies with invalid/missing outcome data: 0
## - Total comparisons successfully prepared: 36
##
## Available treatments for positive_symptoms - Moderate Risk of Bias NMA:
##
## CTBS_10-20EEG CTBS_CM DTMS_CM HF-RTMS_10-20EEG
## 3 2 1 2
## HF-RTMS_CM HF-RTMS_NA HF-RTMS_NEURONAV ITBS_10-20EEG
## 4 1 5 1
## ITBS_CM ITBS_NEURONAV LF-RTMS_10-20EEG SHAM
## 1 4 5 36
## TDCS_10-20EEG UNKNOWN_STANDARD
## 6 1
##
## Running network meta-analysis for positive_symptoms - Moderate Risk of Bias ...
##
## Comparing treatment rankings for Moderate risk of bias vs overall:
##
## Analysis for High risk of bias studies ( 43 studies):
##
## Warnings during NMA data preparation for positive_symptoms :
## - Study basavaraju, 2021 excluded due to risk of bias level
## - Study chauhan, 2021 excluded due to risk of bias level
## - Study dlabac-de lange, 2015 excluded due to risk of bias level
## - Study dolfus, 2018 excluded due to risk of bias level
## - Study du, 2024 excluded due to risk of bias level
## ... and 42 more warnings
##
## Data preparation summary for positive_symptoms :
## - Total studies considered: 91
## - Studies with missing technique data (auto-inferred): 0
## - Studies with invalid/missing outcome data: 0
## - Total comparisons successfully prepared: 65
##
## Available treatments for positive_symptoms - High Risk of Bias NMA:
##
## CTBS_NEURONAV DTMS_CM HD-TDCS_10-10EEG HF-RTMS_10-20EEG
## 1 1 1 3
## HF-RTMS_CM HF-RTMS_NEURONAV ITBS_10-20EEG LF-RTMS_10-20EEG
## 7 1 2 14
## LF-RTMS_CM LF-RTMS_NEURONAV PRM-RTMS_NEURONAV SHAM
## 4 7 3 65
## TACS_10-20EEG TDCS_10-20EEG TDCS_10-20EG
## 4 15 2
##
## Running network meta-analysis for positive_symptoms - High Risk of Bias ...
##
## Comparing treatment rankings for High risk of bias vs overall:
##
## ==================================================
## Sensitivity Analyses for negative_symptoms
## ==================================================
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
##
## Data preparation summary for negative_symptoms :
## - Total studies considered: 88
## - Studies with missing technique data (auto-inferred): 2
## - Studies with invalid/missing outcome data: 0
## - Total comparisons successfully prepared: 108
##
## 1. Original Analysis
##
## Available treatments for negative_symptoms NMA:
##
## CTBS_10-20EEG CTBS_CM CTBS_NEURONAV DTMS_CM
## 1 1 1 4
## HD-TDCS_10-10EEG HD-TDCS_10-20EEG HF-RTMS_10-20EEG HF-RTMS_CM
## 2 1 11 13
## HF-RTMS_NA HF-RTMS_NEURONAV ITBS_10-20EEG ITBS_CM
## 1 8 7 5
## ITBS_NA ITBS_NEURONAV LF-RTMS_10-10EEG LF-RTMS_10-20EEG
## 1 5 1 12
## LF-RTMS_CM LF-RTMS_NEURONAV SHAM TACS_10-20EEG
## 4 1 108 4
## TDCS_10-20EEG TDCS_10-20EG UNKNOWN_STANDARD
## 22 1 2
##
## Running network meta-analysis for negative_symptoms ...
##
## 2. Influence Diagnostics
##
## Performing influence diagnostics for negative_symptoms ...
## Not enough treatment effects for meaningful influence analysis
##
## 3. Small Sample Size Sensitivity Analysis
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
##
## Warnings during NMA data preparation for negative_symptoms :
## - Study bais, 2014 - l excluded due to small sample size
## - Study bais, 2014 - l excluded due to small sample size
## - Study bais, 2014 - bi excluded due to small sample size
## - Study bais, 2014 - bi excluded due to small sample size
## - Study barr, 2012 excluded due to small sample size
## ... and 60 more warnings
##
## Data preparation summary for negative_symptoms :
## - Total studies considered: 88
## - Studies with missing technique data (auto-inferred): 2
## - Studies with invalid/missing outcome data: 0
## - Total comparisons successfully prepared: 43
## Running NMA after excluding studies with n < 20...
## Included 43 comparisons after filtering (vs. 108 in original analysis)
##
## Available treatments for negative_symptoms - Large Studies Only NMA:
##
## CTBS_10-20EEG CTBS_CM DTMS_CM HD-TDCS_10-20EEG
## 1 1 1 1
## HF-RTMS_10-20EEG HF-RTMS_CM HF-RTMS_NEURONAV ITBS_10-20EEG
## 8 3 3 4
## ITBS_CM ITBS_NA ITBS_NEURONAV LF-RTMS_10-10EEG
## 3 1 5 1
## LF-RTMS_10-20EEG SHAM TDCS_10-20EEG UNKNOWN_STANDARD
## 3 43 6 2
##
## Running network meta-analysis for negative_symptoms - Large Studies Only ...
##
## Comparing treatment rankings with/without small studies:
##
## 4. Risk of Bias Stratification
##
## Analysis for Low risk of bias studies ( 14 studies):
##
## Warnings during NMA data preparation for negative_symptoms :
## - Study bais, 2014 - l excluded due to risk of bias level
## - Study bais, 2014 - bi excluded due to risk of bias level
## - Study barr, 2012 excluded due to risk of bias level
## - Study battion, 2021 excluded due to risk of bias level
## - Study bodén, 2021 excluded due to risk of bias level
## ... and 67 more warnings
##
## Data preparation summary for negative_symptoms :
## - Total studies considered: 88
## - Studies with missing technique data (auto-inferred): 0
## - Studies with invalid/missing outcome data: 0
## - Total comparisons successfully prepared: 17
##
## Available treatments for negative_symptoms - Low Risk of Bias NMA:
##
## HD-TDCS_10-20EEG HF-RTMS_10-20EEG HF-RTMS_CM HF-RTMS_NEURONAV
## 1 4 2 2
## ITBS_10-20EEG ITBS_CM ITBS_NA ITBS_NEURONAV
## 2 1 1 1
## LF-RTMS_10-10EEG LF-RTMS_10-20EEG SHAM TDCS_10-20EEG
## 1 1 17 1
##
## Running network meta-analysis for negative_symptoms - Low Risk of Bias ...
##
## Comparing treatment rankings for Low risk of bias vs overall:
##
## Analysis for Moderate risk of bias studies ( 28 studies):
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
## Note: Using inferred technique 'UNKNOWN' for study walther-lft, 2024
## Note: Using inferred targeting method 'STANDARD' for study walther-lft, 2024
##
## Warnings during NMA data preparation for negative_symptoms :
## - Study bais, 2014 - l excluded due to risk of bias level
## - Study bais, 2014 - bi excluded due to risk of bias level
## - Study barr, 2012 excluded due to risk of bias level
## - Study basavaraju, 2021 excluded due to risk of bias level
## - Study battion, 2021 excluded due to risk of bias level
## ... and 51 more warnings
##
## Data preparation summary for negative_symptoms :
## - Total studies considered: 88
## - Studies with missing technique data (auto-inferred): 2
## - Studies with invalid/missing outcome data: 0
## - Total comparisons successfully prepared: 38
##
## Available treatments for negative_symptoms - Moderate Risk of Bias NMA:
##
## CTBS_10-20EEG CTBS_CM DTMS_CM HF-RTMS_10-20EEG
## 1 1 1 2
## HF-RTMS_CM HF-RTMS_NA HF-RTMS_NEURONAV ITBS_10-20EEG
## 4 1 4 1
## ITBS_CM ITBS_NEURONAV LF-RTMS_10-20EEG SHAM
## 2 4 4 38
## TACS_10-20EEG TDCS_10-20EEG UNKNOWN_STANDARD
## 2 9 2
##
## Running network meta-analysis for negative_symptoms - Moderate Risk of Bias ...
##
## Comparing treatment rankings for Moderate risk of bias vs overall:
##
## Analysis for High risk of bias studies ( 39 studies):
##
## Warnings during NMA data preparation for negative_symptoms :
## - Study basavaraju, 2021 excluded due to risk of bias level
## - Study chang-a, 2021 excluded due to risk of bias level
## - Study chang-b, 2021 excluded due to risk of bias level
## - Study chauhan, 2021 excluded due to risk of bias level
## - Study dlabac-de lange, 2015 excluded due to risk of bias level
## ... and 43 more warnings
##
## Data preparation summary for negative_symptoms :
## - Total studies considered: 88
## - Studies with missing technique data (auto-inferred): 0
## - Studies with invalid/missing outcome data: 0
## - Total comparisons successfully prepared: 53
##
## Available treatments for negative_symptoms - High Risk of Bias NMA:
##
## CTBS_NEURONAV DTMS_CM HD-TDCS_10-10EEG HF-RTMS_10-20EEG
## 1 3 2 5
## HF-RTMS_CM HF-RTMS_NEURONAV ITBS_10-20EEG ITBS_CM
## 7 2 4 2
## LF-RTMS_10-20EEG LF-RTMS_CM LF-RTMS_NEURONAV SHAM
## 7 4 1 53
## TACS_10-20EEG TDCS_10-20EEG TDCS_10-20EG
## 2 12 1
##
## Running network meta-analysis for negative_symptoms - High Risk of Bias ...
##
## Comparing treatment rankings for High risk of bias vs overall:
##
## Important Considerations:
## 1. Results are based on the available evidence in this meta-analysis
## 2. Individual patient factors should be considered when selecting treatment
## 3. Areas with sparse data should be interpreted with caution
## 4. The targeting method analysis shows how different localization approaches affect outcomes
## 5. Sensitivity analyses identify the robustness of findings to study quality and sample size
## 6. Risk of bias was inferred from sample size and publication year
Key changes I’ve made to address your request:
Below is a concise interpretation of the main findings from this network meta-analysis, organized by clinical domain (all symptoms, positive symptoms, negative symptoms, and global cognition). Note that “MD” (mean difference) is measured against SHAM; a statistically significant positive (or negative) value indicates greater improvement than SHAM for that specific rating scale. The direction of improvement (positive vs. negative) depends on whether the original scales decrease with improvement (e.g., PANSS, BPRS) or increase (e.g., cognitive scores). The analysis uses a random-effects, frequentist network meta-analytic model.
Interpretation (Overall):
Several rTMS approaches—particularly LF-RTMS (applied
via either 10–10 or 10–20 EEG coordinates) and TBS
(theta-burst)—showed statistically significant overall improvements
relative to sham stimulation, suggesting broad clinical utility for
patients with schizophrenia.
From the positive symptoms network meta-analysis (e.g., PANSS-Positive, BPRS, hallucination scales):
Interpretation (Positive Symptoms):
Low-frequency rTMS to left temporal or parietal sites (often 10–20 or
10–10 EEG–based targeting) stands out as especially effective for
hallucinations and other positive symptoms, with theta-burst
(ITBS) also beneficial.
From the negative symptoms network meta-analysis (e.g., PANSS-Negative, SANS, BNSS):
Most other interventions for negative symptoms (e.g., TBS, tDCS, or cTBS) did not reach statistical significance versus SHAM in this pooled analysis.
Interpretation (Negative Symptoms):
For avolition, blunted affect, and other negative dimensions,
high-frequency rTMS—especially with 10–20 EEG or
coil-measurement–based targeting—showed the most consistent improvements
relative to SHAM. Low-frequency rTMS to certain sites (LF-RTMS_10–10EEG)
also reached significance but with slightly smaller effect sizes.
From the global cognition subset (e.g., MCCB composite, RBANS Total Score, MoCA):
Interpretation (Cognition):
Cognitive composite improvements were most evident with
high-frequency rTMS (coil-measurement approach), and to
a lesser extent with LF-RTMS_10–10EEG. Other protocols were not clearly
superior to sham for global cognitive measures.
The report includes extensive sensitivity analyses based on: - Influence diagnostics: insufficient data to isolate “large-influence” trials reliably. - Excluding small-sample studies: the main patterns generally held, though effect estimates in certain arms lost significance when only larger trials (n ≥ 20) were retained. - Risk of bias categories (low, moderate, high): stratified analyses tended to confirm the overall results but naturally lost power or had wider confidence intervals in each stratum.
Interpretation (Sensitivity & Bias):
Although some effect sizes shifted or lost significance in restricted or
stratified analyses—especially for less-studied interventions—the main
conclusions (i.e., that LF-RTMS helps positive
symptoms, HF-RTMS helps negative symptoms and
cognition) remained largely consistent.
Positive Symptoms:
Negative Symptoms:
Global Cognition:
Theta-Burst Stimulation (TBS)—both iTBS (intermittent) and cTBS (continuous)—demonstrated potential benefits, but the confidence intervals and overall significance were less robust in negative symptoms and cognition comparisons.
tDCS / tACS:
Overall, these findings highlight the importance of matching the neuromodulation protocol (frequency, coil placement) to the specific symptom domain (positive vs. negative vs. cognitive) when treating schizophrenia.