title: Computational models of performance monitoring and cognitive control.
abstract: The medial prefrontal cortex (mPFC) has been the subject of intense interest as a locus of cognitive control. Several computational models have been proposed to account for a range of effects, including error detection, conflict monitoring, error likelihood prediction, and numerous other effects observed with single-unit neurophysiology, fMRI, and lesion studies. Here, we review the state of computational models of cognitive control and offer a new theoretical synthesis of the mPFC as signaling response–outcome predictions. This new synthesis has two interacting components. The first component learns to predict the various possible outcomes of a planned action, and the second component detects discrepancies between the actual and intended responses; the detected discrepancies in turn update the outcome predictions. This single construct is consistent with a wide array of performance monitoring effects in mPFC and suggests a unifying account of the cognitive role of medial PFC in performance monitoring.
authors.forename: William H
authors.initials: WH
authors.lastname: Alexander
authors.forename: Joshua W
authors.initials: JW
authors.lastname: Brown
mesh_terms: D001288:Attention / Q000502:physiology*; D056344:Executive Function / Q000502:physiology*; D006040:Goals; D006801:Humans; D008960:Models, Psychological; D017397:Prefrontal Cortex / Q000502:physiology*; D011597:Psychomotor Performance / Q000502:physiology*