Resting State Cognition and Connectivity Analyses
Visualize distrubtions of brain variables:
brain_l <- brain %>%
pivot_longer(
cols = -subnum, # Specify columns to pivot (all except subnum)
names_to = "network_pair", # Name of the new column for variable names
values_to = "value" # Name of the new column for values
)
ggplot(data = brain_l, aes(x = network_pair, y=value,fill=network_pair)) +
geom_violin(alpha=.5) +
geom_point(aes(color=network_pair), fill="black",shape=19,alpha=.65,position="jitter") +
labs(y = "Connectivity", x = "Networks") +
ggtitle("Within and Between Netowrk connectivity distributions") +
theme_minimal() 
### Correlations between connectivity measures:
# Compute a correlation matrix
brain_corr <- cor(brain_sr_red[,c(2:7)])
# Compute a matrix of correlation p-values
brain_p.mat <- cor_pmat(brain_sr_red[,c(2:7)])
#Display Heatmap
ggcorrplot(brain_corr, hc.order = TRUE, type = "lower",
outline.color = "white", insig = "blank",
lab = TRUE, digits = 2)
ggplot(data = brain_sr_red, aes(x = SAL_SAL, y=SAL_DMN)) +
geom_point(fill="skyblue4",shape=19,alpha=.75) +
labs(y = "SAL - DMN connectivity", x = "SAL - SAL connectivity") +
ggtitle(".5 correlation between sal-dmn and sal-sal connecitivity") +
theme_minimal() 
Visualize the distrubtions of resting state cognition domains:
sr_l <- brain_sr_red[,c(1,44:50)] %>%
pivot_longer(
cols = -subnum, # Specify columns to pivot (all except subnum)
names_to = "thoughtdomain", # Name of the new column for variable names
values_to = "value" # Name of the new column for values
)
ggplot(data = sr_l, aes(x = thoughtdomain, y=value,fill=thoughtdomain)) +
geom_violin(alpha=.5) +
geom_point(aes(color=thoughtdomain), fill="black",shape=19,alpha=.65,position="jitter") +
labs(y = "Factor Score", x = "Thought Domains") +
ggtitle("Resting State Thought Domain distributions") +
theme_minimal()## Warning: Removed 315 rows containing non-finite outside the scale range
## (`stat_ydensity()`).## Warning: Removed 315 rows containing missing values or values outside the scale range
## (`geom_point()`).
# Compute a correlation matrix
sr_corr <- cor(brain_sr_red[,c(44:50)],use = "complete")
# Compute a matrix of correlation p-values
sr_p.mat <- cor_pmat(brain_sr_red[,c(44:50)])
#Display Heatmap
ggcorrplot(sr_corr, hc.order = TRUE, type = "lower",
outline.color = "white", insig = "blank",
lab = TRUE, digits = 2)
Models with FC as outcome:
Within Network
#Brain ~ TD1 ... TD7 + Age + SAB
dmn_win <- lm(DMN_DMN ~ sleepiness + self_other + comfort + visual_thought + self_talk + ephemeral + somatic + AgeatMRI + GeneralInformation_SexAtBirth, data=brain_sr_red)
summary(dmn_win) ##
## Call:
## lm(formula = DMN_DMN ~ sleepiness + self_other + comfort + visual_thought +
## self_talk + ephemeral + somatic + AgeatMRI + GeneralInformation_SexAtBirth,
## data = brain_sr_red)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.051170 -0.026998 -0.009671 0.025015 0.086144
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0678030 0.0636823 1.065 0.292
## sleepiness 0.0047825 0.0068717 0.696 0.490
## self_other 0.0032847 0.0077885 0.422 0.675
## comfort 0.0001450 0.0070278 0.021 0.984
## visual_thought -0.0066841 0.0067264 -0.994 0.325
## self_talk 0.0004631 0.0066859 0.069 0.945
## ephemeral 0.0001330 0.0074788 0.018 0.986
## somatic 0.0047066 0.0078302 0.601 0.551
## AgeatMRI -0.0004415 0.0028990 -0.152 0.880
## GeneralInformation_SexAtBirth 0.0175467 0.0136667 1.284 0.205
##
## Residual standard error: 0.03981 on 48 degrees of freedom
## (155 observations deleted due to missingness)
## Multiple R-squared: 0.09165, Adjusted R-squared: -0.07867
## F-statistic: 0.5381 on 9 and 48 DF, p-value: 0.8394fp_win <- lm(FP_FP ~ sleepiness + self_other + comfort + visual_thought + self_talk + ephemeral + somatic + AgeatMRI + GeneralInformation_SexAtBirth, data=brain_sr_red)
summary(fp_win) ##
## Call:
## lm(formula = FP_FP ~ sleepiness + self_other + comfort + visual_thought +
## self_talk + ephemeral + somatic + AgeatMRI + GeneralInformation_SexAtBirth,
## data = brain_sr_red)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.101057 -0.045278 -0.009729 0.034283 0.144649
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 8.359e-02 1.041e-01 0.803 0.426
## sleepiness -2.218e-03 1.123e-02 -0.197 0.844
## self_other 8.716e-03 1.273e-02 0.685 0.497
## comfort 8.440e-03 1.149e-02 0.735 0.466
## visual_thought -2.060e-03 1.100e-02 -0.187 0.852
## self_talk -1.064e-03 1.093e-02 -0.097 0.923
## ephemeral -2.612e-03 1.223e-02 -0.214 0.832
## somatic 8.105e-03 1.280e-02 0.633 0.530
## AgeatMRI 2.332e-05 4.740e-03 0.005 0.996
## GeneralInformation_SexAtBirth 2.655e-02 2.234e-02 1.188 0.241
##
## Residual standard error: 0.06508 on 48 degrees of freedom
## (155 observations deleted due to missingness)
## Multiple R-squared: 0.03962, Adjusted R-squared: -0.1405
## F-statistic: 0.22 on 9 and 48 DF, p-value: 0.9902sal_win <- lm(SAL_SAL ~ sleepiness + self_other + comfort + visual_thought + self_talk + ephemeral + somatic + AgeatMRI + GeneralInformation_SexAtBirth, data=brain_sr_red)
summary(sal_win) ##
## Call:
## lm(formula = SAL_SAL ~ sleepiness + self_other + comfort + visual_thought +
## self_talk + ephemeral + somatic + AgeatMRI + GeneralInformation_SexAtBirth,
## data = brain_sr_red)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.095748 -0.027877 -0.002153 0.025918 0.159472
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.1780249 0.0826567 2.154 0.0363 *
## sleepiness 0.0042285 0.0089191 0.474 0.6376
## self_other 0.0142181 0.0101091 1.406 0.1660
## comfort 0.0009873 0.0091218 0.108 0.9143
## visual_thought -0.0046916 0.0087305 -0.537 0.5935
## self_talk -0.0110343 0.0086780 -1.272 0.2097
## ephemeral -0.0017381 0.0097072 -0.179 0.8587
## somatic 0.0055976 0.0101632 0.551 0.5843
## AgeatMRI -0.0035276 0.0037628 -0.937 0.3532
## GeneralInformation_SexAtBirth 0.0042394 0.0177388 0.239 0.8121
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.05167 on 48 degrees of freedom
## (155 observations deleted due to missingness)
## Multiple R-squared: 0.1051, Adjusted R-squared: -0.06267
## F-statistic: 0.6265 on 9 and 48 DF, p-value: 0.7686Between Network
dmn_fp <- lm(FP_DMN ~ sleepiness + self_other + comfort + visual_thought + self_talk + ephemeral + somatic + AgeatMRI + GeneralInformation_SexAtBirth, data=brain_sr_red)
summary(dmn_fp) ##
## Call:
## lm(formula = FP_DMN ~ sleepiness + self_other + comfort + visual_thought +
## self_talk + ephemeral + somatic + AgeatMRI + GeneralInformation_SexAtBirth,
## data = brain_sr_red)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.101602 -0.014112 0.002437 0.016969 0.048497
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.0033728 0.0479833 -0.070 0.9443
## sleepiness 0.0055323 0.0051777 1.068 0.2906
## self_other -0.0034000 0.0058685 -0.579 0.5650
## comfort 0.0014496 0.0052953 0.274 0.7854
## visual_thought 0.0003465 0.0050682 0.068 0.9458
## self_talk 0.0093473 0.0050377 1.855 0.0697 .
## ephemeral -0.0038896 0.0056352 -0.690 0.4934
## somatic -0.0057243 0.0058999 -0.970 0.3368
## AgeatMRI -0.0006764 0.0021843 -0.310 0.7581
## GeneralInformation_SexAtBirth -0.0053639 0.0102976 -0.521 0.6048
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02999 on 48 degrees of freedom
## (155 observations deleted due to missingness)
## Multiple R-squared: 0.1329, Adjusted R-squared: -0.02967
## F-statistic: 0.8175 on 9 and 48 DF, p-value: 0.6028fp_sal <- lm(SAL_FP ~ sleepiness + self_other + comfort + visual_thought + self_talk + ephemeral + somatic + AgeatMRI + GeneralInformation_SexAtBirth, data=brain_sr_red)
summary(fp_sal) ##
## Call:
## lm(formula = SAL_FP ~ sleepiness + self_other + comfort + visual_thought +
## self_talk + ephemeral + somatic + AgeatMRI + GeneralInformation_SexAtBirth,
## data = brain_sr_red)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.075193 -0.015626 -0.001681 0.015252 0.068077
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0464472 0.0494308 0.940 0.352
## sleepiness 0.0037822 0.0053339 0.709 0.482
## self_other -0.0010928 0.0060455 -0.181 0.857
## comfort 0.0002129 0.0054551 0.039 0.969
## visual_thought -0.0065655 0.0052211 -1.257 0.215
## self_talk -0.0002003 0.0051896 -0.039 0.969
## ephemeral 0.0004673 0.0058052 0.080 0.936
## somatic 0.0048086 0.0060778 0.791 0.433
## AgeatMRI -0.0014194 0.0022502 -0.631 0.531
## GeneralInformation_SexAtBirth -0.0039365 0.0106083 -0.371 0.712
##
## Residual standard error: 0.0309 on 48 degrees of freedom
## (155 observations deleted due to missingness)
## Multiple R-squared: 0.09784, Adjusted R-squared: -0.07132
## F-statistic: 0.5784 on 9 and 48 DF, p-value: 0.8081sal_dmn <- lm(SAL_DMN ~ sleepiness + self_other + comfort + visual_thought + self_talk + ephemeral + somatic + AgeatMRI + GeneralInformation_SexAtBirth, data=brain_sr_red)
summary(sal_dmn) ##
## Call:
## lm(formula = SAL_DMN ~ sleepiness + self_other + comfort + visual_thought +
## self_talk + ephemeral + somatic + AgeatMRI + GeneralInformation_SexAtBirth,
## data = brain_sr_red)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.081294 -0.011442 0.004415 0.014590 0.055840
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.0287258 0.0493698 -0.582 0.563
## sleepiness -0.0036234 0.0053273 -0.680 0.500
## self_other -0.0025579 0.0060381 -0.424 0.674
## comfort -0.0023398 0.0054483 -0.429 0.670
## visual_thought 0.0043569 0.0052146 0.836 0.408
## self_talk 0.0078546 0.0051832 1.515 0.136
## ephemeral -0.0042605 0.0057980 -0.735 0.466
## somatic 0.0013662 0.0060703 0.225 0.823
## AgeatMRI 0.0007032 0.0022475 0.313 0.756
## GeneralInformation_SexAtBirth -0.0065801 0.0105952 -0.621 0.538
##
## Residual standard error: 0.03086 on 48 degrees of freedom
## (155 observations deleted due to missingness)
## Multiple R-squared: 0.08551, Adjusted R-squared: -0.08596
## F-statistic: 0.4987 on 9 and 48 DF, p-value: 0.868Alternative mdoel with thought domain as DV:
# sleepiness <- lm(sleepiness ~ DMN_DMN + FP_FP + SAL_SAL + FP_DMN + SAL_FP + SAL_DMN + AgeatMRI + GeneralInformation_SexAtBirth, data=brain_sr_red)
# summary(sleepiness)
#
# selfother <- lm(self_other ~ DMN_DMN + FP_FP + SAL_SAL + FP_DMN + SAL_FP + SAL_DMN + AgeatMRI + GeneralInformation_SexAtBirth, data=brain_sr_red)
# summary(selfother)
#
# comfort <- lm(comfort ~ DMN_DMN + FP_FP + SAL_SAL + FP_DMN + SAL_FP + SAL_DMN + AgeatMRI + GeneralInformation_SexAtBirth, data=brain_sr_red)
# summary(comfort)
#
# visual_thought <- lm(visual_thought ~ DMN_DMN + FP_FP + SAL_SAL + FP_DMN + SAL_FP + SAL_DMN + AgeatMRI + GeneralInformation_SexAtBirth, data=brain_sr_red)
# summary(visual_thought)
#
# selftalk <- lm(self_talk ~ DMN_DMN + FP_FP + SAL_SAL + FP_DMN + SAL_FP + SAL_DMN + AgeatMRI + GeneralInformation_SexAtBirth, data=brain_sr_red)
# summary(selftalk)
#
# ephemeral <- lm(ephemeral ~ DMN_DMN + FP_FP + SAL_SAL + FP_DMN + SAL_FP + SAL_DMN + AgeatMRI + GeneralInformation_SexAtBirth, data=brain_sr_red)
# summary(ephemeral)
#
# somatic <- lm(somatic ~ DMN_DMN + FP_FP + SAL_SAL + FP_DMN + SAL_FP + SAL_DMN + AgeatMRI + GeneralInformation_SexAtBirth, data=brain_sr_red)
# summary(somatic)