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

Science (New York, N.Y.) | Feb 18, 2005

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 RIS Download

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