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Topological and Dynamical Aspects of a Neural Network Model for Generation of Pursuit Motor Programs

Abstract

A computational model of a motor program generator (MPG) forhorizontal pursuit eye movements (PEM) is proposed. The MPG modelconsists of two neural networks (velocity maps). Neurons arearranged in a single circular layer with lattice structure andconnected only to their immediate neighbors. During PEM one ofthe two maps always features an activity peak (AP) which travelswith constant velocity from one neuron to the next. A memory traceof the most recent portion of the trajectory is created by meansof a temporary increase of the interneuronal connectivity strengthbetween previously activated neurons. This novel MPG model may beuseful for designing parallel processors for motor control ofrobots.

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