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Flexible control of mutual inhibition: a neural model of two-interval discrimination.

Networks adapt to environmental demands by switching between distinct dynamical behaviors. The activity of frontal-lobe neurons during two-interval discrimination tasks is an example of these adaptable dynamics. Subjects first perceive a stimulus, then hold it in working memory, and finally make a decision by comparing it with a second stimulus. We present a simple mutual-inhibition network model that captures all three task phases within a single framework. The model integrates both working memory and decision making because its dynamical properties are easily controlled without changing its connectivity. Mutual inhibition between nonlinear units is a useful design motif for networks that must display multiple behaviors.

Pubmed ID: 15718474

Authors

  • Machens CK
  • Romo R
  • Brody CD

Journal

Science (New York, N.Y.)

Publication Data

February 18, 2005

Associated Grants

  • Agency: NIMH NIH HHS, Id: 1R01MH067991-01

Mesh Terms

  • Algorithms
  • Animals
  • Cognition
  • Computer Simulation
  • Decision Making
  • Discrimination (Psychology)
  • Frontal Lobe
  • Macaca
  • Mathematics
  • Memory
  • Models, Neurological
  • Nerve Net
  • Neural Inhibition
  • Neural Networks (Computer)
  • Neurons
  • Neurons, Afferent
  • Nonlinear Dynamics
  • Prefrontal Cortex
  • Psychomotor Performance
  • Somatosensory Cortex