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Dynamics and kinematics of simple neural systems
Authors:Rabinovich Mikhail  Selverston Allen  Rubchinsky Leonid  Huerta Ramon
Affiliation:Institute for Nonlinear Science, University of California, San Diego, La Jolla, California 92093-0402Institute of Applied Physics, Russian Academy of Science, Nizhniy Novgorod, 603600, RussiaDepartment of Biology, University of California, San Diego, La Jolla, California 92093-0357Institute for Nonlinear Science and Department of Physics, University of California, San Diego, La Jolla, California 92093-0402Institute for Nonlinear Science, University of California, San Diego, La Jolla, California 92093-0402.
Abstract:The dynamics of simple neural systems is of interest to both biologists and physicists. One of the possible roles of such systems is the production of rhythmic patterns, and their alterations (modification of behavior, processing of sensory information, adaptation, control). In this paper, the neural systems are considered as a subject of modeling by the dynamical systems approach. In particular, we analyze how a stable, ordinary behavior of a small neural system can be described by simple finite automata models, and how more complicated dynamical systems modeling can be used. The approach is illustrated by biological and numerical examples: experiments with and numerical simulations of the stomatogastric central pattern generators network of the California spiny lobster. (c) 1996 American Institute of Physics.
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