A computational model of inhibitory control in frontal cortex and basal ganglia

Psychol Rev. 2013 Apr;120(2):329-55. doi: 10.1037/a0031542.

Abstract

Planning and executing volitional actions in the face of conflicting habitual responses is a critical aspect of human behavior. At the core of the interplay between these 2 control systems lies an override mechanism that can suppress the habitual action selection process and allow executive control to take over. Here, we construct a neural circuit model informed by behavioral and electrophysiological data collected on various response inhibition paradigms. This model extends a well-established model of action selection in the basal ganglia by including a frontal executive control network that integrates information about sensory input and task rules to facilitate well-informed decision making via the oculomotor system. Our simulations of the anti-saccade, Simon, and saccade-override tasks ensue in conflict between a prepotent and controlled response that causes the network to pause action selection via projections to the subthalamic nucleus. Our model reproduces key behavioral and electrophysiological patterns and their sensitivity to lesions and pharmacological manipulations. Finally, we show how this network can be extended to include the inferior frontal cortex to simulate key qualitative patterns of global response inhibition demands as required in the stop-signal task.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Animals
  • Basal Ganglia / physiology*
  • Computer Simulation
  • Decision Making / physiology
  • Electrophysiological Phenomena
  • Executive Function / physiology*
  • Humans
  • Inhibition, Psychological*
  • Models, Neurological*
  • Neural Networks, Computer*
  • Neuropsychological Tests
  • Neurotransmitter Agents / physiology
  • Prefrontal Cortex / physiology*
  • Reaction Time / physiology
  • Saccades / physiology
  • Time Factors

Substances

  • Neurotransmitter Agents