Interoception 2022-2023

heart and stuff…

cat("\014")     # clean terminal



rm(list = ls()) # clean workspace
try(dev.off(), silent = TRUE) # close all plots
library(ggplot2)
library(GGally)

# theme_set(
#   theme_minimal()
# )

df <- read.csv('rhos_and_mean_rts.csv')
# df <- df[df$Subject != 'S28_F_A', ]
df[sapply(df, is.character)] <- lapply(df[sapply(df, is.character)], as.factor)
df_intero <- read.csv('rhos_and_answers.csv')
# df_intero <- df_intero[df_intero$Subject != 'S28_F_A', ]
df_intero[sapply(df_intero, is.character)] <- lapply(df_intero[sapply(df_intero, is.character)], as.factor)
# angle_data <- read.csv('angle_and_rt_data.csv')
# angle_data <- angle_data[angle_data$Subject != 'S28_F_A', ]
# angle_data[sapply(angle_data, is.character)] <- lapply(angle_data[sapply(angle_data, is.character)], as.factor)

1 General description

options(width = 100)
summary(df)

    Subject                       Block      keystrokes       mean_angle           rho         
 S21_M_A: 6   Interoception 1        :10   Min.   : 98.00   Min.   :-3.0376   Min.   :0.01381  
 S22_M_A: 6   Interoception 2        :10   1st Qu.: 99.00   1st Qu.:-0.7406   1st Qu.:0.05038  
 S23_F_A: 6   Irregular Beat         :10   Median :100.00   Median : 1.4487   Median :0.13765  
 S26_M_A: 6   Irregular keys to heart:10   Mean   : 99.67   Mean   : 0.7136   Mean   :0.34448  
 S27_M_A: 6   Regular Beat           :10   3rd Qu.:100.00   3rd Qu.: 2.1735   3rd Qu.:0.71368  
 S29_F_A: 6   Regular keys to heart  :10   Max.   :101.00   Max.   : 2.9649   Max.   :0.93620  
 (Other):24                                                                                    
 rayleigh_p_value mean_rt_from_R   cv_rt_from_R   mean_rt_until_R  cv_rt_until_R   
 Min.   :0.0000   Min.   :217.3   Min.   :10.64   Min.   : 331.4   Min.   : 9.085  
 1st Qu.:0.0000   1st Qu.:375.9   1st Qu.:40.90   1st Qu.: 380.7   1st Qu.:34.748  
 Median :0.1520   Median :404.6   Median :54.87   Median : 423.1   Median :55.602  
 Mean   :0.3523   Mean   :411.8   Mean   :48.59   Mean   : 534.1   Mean   :46.953  
 3rd Qu.:0.7759   3rd Qu.:436.6   3rd Qu.:59.94   3rd Qu.: 655.9   3rd Qu.:58.020  
 Max.   :0.9811   Max.   :623.0   Max.   :65.91   Max.   :1092.8   Max.   :72.135  
                                                                                   

1.1 Rho v/s CV

ggplot(df[!grepl('keys to heart', df$Block), ], aes(x = rho, y = cv_rt_from_R, color = Block)) +
  geom_point(size = 5)

1.2 Rho v/s CV, just sound beat blocks

ggplot(df[grepl('Beat', df$Block), ], aes(x = rho, y = cv_rt_from_R, color = Block)) +
  geom_point(size = 5)

1.3 Rho v/s CV, just interoception blocks

ggplot(df[grepl('Interoception', df$Block), ], aes(x = rho, y = cv_rt_from_R, color = Block)) +
  geom_point(size = 5)

ggplot(df[grepl('Interoception', df$Block), ], aes(x = rho, y = cv_rt_from_R, color = Subject)) +
  geom_point(size = 5)

1.4 Angle v/s Rho

ggplot(df[grepl('Interoception', df$Block), ], aes(x = mean_angle, y = rho, color = Block)) +
  geom_point(size = 5)

1.5 Correlations

options(width = 100)
summary(df_intero)

    Subject      rho_1             pval_1            rho_2             pval_2          belief_pre 
 S21_M_A:1   Min.   :0.03661   Min.   :0.00000   Min.   :0.01456   Min.   :0.00000   Min.   :2.0  
 S22_M_A:1   1st Qu.:0.08566   1st Qu.:0.05123   1st Qu.:0.04402   1st Qu.:0.01086   1st Qu.:5.5  
 S23_F_A:1   Median :0.14967   Median :0.10771   Median :0.06803   Median :0.62701   Median :7.0  
 S26_M_A:1   Mean   :0.18853   Mean   :0.30129   Mean   :0.16907   Mean   :0.48793   Mean   :6.5  
 S27_M_A:1   3rd Qu.:0.17376   3rd Qu.:0.48015   3rd Qu.:0.26487   3rd Qu.:0.82387   3rd Qu.:8.0  
 S29_F_A:1   Max.   :0.63952   Max.   :0.87457   Max.   :0.65236   Max.   :0.97902   Max.   :8.0  
 (Other):4                                                                                        
 confidence_pre  belief_post   confidence_post  intero1_span    intero2_span       beats_1      
 Min.   :3.00   Min.   :1.00   Min.   :2.0     Min.   :115.2   Min.   : 93.62   Min.   : 130.0  
 1st Qu.:4.50   1st Qu.:3.25   1st Qu.:6.0     1st Qu.:167.3   1st Qu.:141.79   1st Qu.: 197.5  
 Median :7.00   Median :6.00   Median :6.5     Median :253.7   Median :181.50   Median : 316.0  
 Mean   :6.20   Mean   :4.90   Mean   :6.0     Mean   :321.9   Mean   :249.99   Mean   : 409.0  
 3rd Qu.:7.75   3rd Qu.:6.00   3rd Qu.:7.0     3rd Qu.:388.7   3rd Qu.:340.64   3rd Qu.: 519.2  
 Max.   :8.00   Max.   :8.00   Max.   :8.0     Max.   :772.7   Max.   :578.18   Max.   :1060.0  
                                                                                                
    beats_2       occupancy_1       occupancy_2        pulse_1         pulse_2     
 Min.   :101.0   Min.   :0.09434   Min.   :0.1256   Min.   :67.36   Min.   :64.73  
 1st Qu.:172.5   1st Qu.:0.19361   1st Qu.:0.2488   1st Qu.:70.77   1st Qu.:72.95  
 Median :229.0   Median :0.31960   Median :0.4260   Median :74.78   Median :74.89  
 Mean   :318.2   Mean   :0.35650   Mean   :0.4459   Mean   :74.86   Mean   :75.14  
 3rd Qu.:409.2   3rd Qu.:0.51357   3rd Qu.:0.5759   3rd Qu.:79.15   3rd Qu.:77.53  
 Max.   :796.0   Max.   :0.76923   Max.   :0.9901   Max.   :82.31   Max.   :82.64  
                                                                                   

variables1 <- c('rho_1', 'rho_2', 'intero1_span', 'intero2_span', 'occupancy_1', 'occupancy_2')
variables_pairs1 <- ggpairs(df_intero,
                           columns = variables1,
                           aes(alpha = .25),
                           progress = FALSE,
                           lower = list(continuous = wrap("points")))
suppressWarnings(print(variables_pairs1))

variables2 <- c('belief_pre', 'confidence_pre', 'belief_post', 'confidence_post')
variables_pairs2 <- ggpairs(df_intero,
                           columns = variables2,
                           aes(alpha = .25),
                           progress = FALSE,
                           lower = list(continuous = wrap("points")))
suppressWarnings(print(variables_pairs2))