Medial prefrontal cortex as an action-outcome predictor

The medial prefrontal cortex (mPFC) and especially anterior cingulate cortex (ACC) is central to higher cognitive function and numerous clinical disorders, yet its basic function remains in dispute. Various competing theories of mPFC have treated effects of errors, conflict, error likelihood, volatility, and reward, based on findings from neuroimaging and neurophysiology in humans and monkeys. To date, no single theory has been able to reconcile and account for the variety of findings. Here we show that a simple model based on standard learning rules can simulate and unify an unprecedented range of known effects in mPFC. The model reinterprets many known effects and suggests a new view of mPFC, as a region concerned with learning and predicting the likely outcomes of actions, whether good or bad. Cognitive control at the neural level is then seen as a result of evaluating the probable and actual outcomes of one's actions.