Flexible control of mutual inhibition: a neural model of two-interval discrimination.
Publication Year
2005
Type
Journal Article
Abstract
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.
Keywords
Animals,
Decision Making,
Models, Neurological,
Neurons, Afferent,
Prefrontal Cortex,
Neurons,
Algorithms,
Memory,
Psychomotor Performance,
Nerve Net,
Nonlinear Dynamics,
Somatosensory Cortex,
Cognition,
Computer Simulation,
Frontal Lobe,
Macaca,
Mathematics,
Neural Inhibition,
Discrimination, Psychological,
Neural Networks, Computer
Journal
Science
Volume
307
Issue
5712
Pages
1121-4
Date Published
2005 Feb 18
ISSN Number
1095-9203
Alternate Journal
Science
PMID
15718474