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Master-equation approach to stochastic neurodynamics

Toru Ohira

Jack D. Cowan

  • Department of Physics, The University of Chicago, Chicago, Illinois 60637

  • Department of Mathematics, The University of Chicago, Chicago, Illinois 60637

Phys. Rev. E 48, 2259 – Published 1 September, 1993

DOI: https://doi.org/10.1103/PhysRevE.48.2259

Abstract

A master-equation approach to the stochastic neurodynamics proposed by Cowan [in Advances in Neural Information Processing Systems 3, edited by R. P. Lippman, J. E. Moody, and D. S. Touretzky (Morgan Kaufmann, San Mateo, 1991), p. 62] is investigated in this paper. We deal with a model neural network that is composed of two-state neurons obeying elementary stochastic transition rates. We show that such an approach yields concise expressions for multipoint moments and an equation of motion. We apply the formalism to a (1+1)-dimensional system. Exact and approximate expressions for various statistical parameters are obtained and compared with Monte Carlo simulations.

References (20)

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