Stress-sensitive inference of task controllability

Abstract

Estimating the controllability of the environment enables agents to better predict upcoming events and decide when to engage controlled action selection. How does the human brain estimate controllability? Trial-by-trial analysis of choices, decision times, and neural activity in an explore-and-predict task demonstrate that humans solve this problem by comparing the predictions of an "actor" model with those of a reduced "spectator" model of their environment. Neural BOLD responses within striatal and medial prefrontal areas tracked the instantaneous difference in the prediction errors generated by these two statistical learning models. BOLD activity in the posterior cingulate, temporoparietal, and prefrontal cortices covaried with changes in estimated controllability. Exposure to inescapable stressors biased controllability estimates downward and increased reliance on the spectator model in an anxiety-dependent fashion. Taken together, these findings provide a mechanistic account of controllability inference and its distortion by stress exposure.