查看文章

Predicting individual behavior from brain functional connectivity (FC) patterns can contribute to our understanding of human brain functioning. This may apply in particular if predictions are based on features derived from circumscribed, a priori defined functional networks, which improves interpretability. Furthermore, some evidence suggests that task‐based FC data may yield more successful predictions of behavior than resting‐state FC data. Here, we comprehensively examined to what extent the correspondence of functional network priors and task states with behavioral target domains influences the predictability of individual performance in cognitive, social, and affective tasks. To this end, we used data from the Human Connectome Project for large‐scale out‐of‐sample predictions of individual abilities in working memory (WM), theory‐of‐mind cognition (SOCIAL), and emotion processing (EMO) from FC of …