Computational models of motivated frontal function

Handb Clin Neurol. 2019:163:317-332. doi: 10.1016/B978-0-12-804281-6.00017-3.

Abstract

Computational models of frontal function have made important contributions to understanding how the frontal lobes support a wide range of important functions, in their interactions with other brain areas including, critically, the basal ganglia (BG). We focus here on the specific case of how different frontal areas support goal-directed, motivated decision-making, by representing three essential types of information: possible plans of action (in more dorsal and lateral frontal areas), affectively significant outcomes of those action plans (in ventral, medial frontal areas including the orbital frontal cortex), and the overall utility of a given plan compared to other possible courses of action (in anterior cingulate cortex). Computational models of goal-directed action selection at multiple different levels of analysis provide insight into the nature of learning and processing in these areas and the relative contributions of the frontal cortex versus the BG. The most common neurologic disorders implicate these areas, and understanding their precise function and modes of dysfunction can contribute to the new field of computational psychiatry, within the broader field of computational neuroscience.

Keywords: Basal ganglia; Computational models; Frontal cortex; Goal-directed; Motivation; Reinforcement learning; Working memory.

Publication types

  • Review

MeSH terms

  • Computer Simulation*
  • Frontal Lobe / physiology*
  • Humans
  • Models, Neurological*
  • Motivation / physiology*