Fig. 2.

Balanced accuracy for the binary classifiers as assessed using leave-one-out cross validation for the three different subgroup comparisons – that is, CHR vs. REM (left), CHR vs. IMP (middle), and IMP vs. REM (right). Balanced accuracies are shown for the different features – namely, effective connectivity parameters (DCM; blue), functional connectivity (FC; light grey), and local BOLD activity (CI, dark grey). Asterisks above the bars indicate significant classification performance as assessed by means of permutation tests where an empirical null distribution of the balanced accuracy is computed by randomly permuting the participant labels and re-evaluating the classifier based on these new labels. Additionally, asterisks above the lines connecting two bars indicate significant differences in classification performance between different data features as assessed using the asymptotic McNemar test.