Fig. 3.

(a) Manhattan plot with univariate t tests of all variables along the x-axis [cognition (Cog), electrophysiology (EEG), structural magnetic resonance imaging (sMRI), and diffusion tensor imaging (DTI)] and log-transformed p values along the y-axis. Lower dashed horizontal line indicates significance level of p = 0.05. Upper dashed lines indicate the Bonferroni-corrected p value for each modality. (b) In colored horizontal lines, the fraction of data splits (see Fig. 1), where individual variables were included in the final machine learning model, which determined the diagnostic accuracy (presented in Fig. 2). Specification of variables is provided in online Supplementary Material. Only configurations of the six machine learning algorithms, which included feature selection, are shown. nB, naïve Bayes; LR, logistic regression without regularization; LR_r, logistic regression with regularization; SVM_l, support vector machine with linear kernel; DT, decision tree; RF, random forest.