Article ID Journal Published Year Pages File Type
1139675 Mathematics and Computers in Simulation 2012 15 Pages PDF
Abstract
The paper studies the dynamical model of motor cognition of neural networks through the theory of stochastic phase resetting dynamics, presents the interaction, phase coding, and the evolution of the time-varying averaged number density in terms of populations of perceptive neurons, inter-neurons, and motor neurons subject to coupling, and probes into the dynamical reaction of neural networks under the condition of spontaneous movement and stimulation, respectively. With numerical simulations, we prove (1) Walter J. Freeman's conjecture that the response of cortex dynamics cannot code external stimulation information; (2) the possession of rhythm coding in the neural coding of serial neural networks; (3) the importance of neural inhibition in the regulation of the central nervous system.
Related Topics
Physical Sciences and Engineering Engineering Control and Systems Engineering
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