How Tasks Change Whole-Brain Functional Organization to Reveal Brain-Phenotype Relationships

Abstract

Functional connectivity (FC) calculated from task fMRI data better reveals brain-phenotype relationships than rest-based FC, but why is unknown. Here, in over 700 individuals performing 7 different tasks, we use psychophysiological interaction (PPI) and predictive modeling analyses to demonstrate that FC and overall degree of task-induced signal change, but not task-evoked activation alone, drive phenotypic prediction, and the combination of these components further improves prediction. Inter-subject PPI analyses demonstrate that predictive utility is highest in distributed FC patterns that are dissimilar across individuals, except in regions of group-level task activation, suggesting that task FC better predicts phenotype than rest FC for two, regionally specific reasons: (1) utilization of activated regions synchronizes them and amplifies components of their signals that meaningfully vary across individuals; and (2) elsewhere in the brain, prediction is driven by nodal interactions that set individuals apart. These findings unite two, historically separate lines of human neuroscience research — task activation and FC — and offer a framework to leverage insights from both to reveal the neural bases of complex human traits, symptoms, and behaviors.