Presentation 2009-10-23
Statistical mechanics of a Mexican-hat-type network with Depressing Synapses
Yasuhiko IGARASHI, Masafumi OIZUMI, Masato OKADA,
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Abstract(in English) We analyze a stochastic binary neural network model with depressing synapses by the mean-field theory to explore the effects of synaptic depression on macroscopic behavior of the system. Taking advantage of independence at equal time between a depression variable and a firing state variable, we derive microscopic dynamical mean field equations for a stochastic binary neural network model with depressing synapses. We consider a network with homogeneous connectivity and that with Mexican-hat type connectivity. Based on the microscopic equations, we derive macroscopic steady state equations for these networks. We analyze the stabilities of the steady states in Fourier space and investigate how synaptic depression affects macroscopic properties of these networks.
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Keyword(in English) Synaptic depression / Mexican-hat type interaction / Mean-field analysis / Rotating state
Paper # NC2009-40
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Committee NC
Conference Date 2009/10/16(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Statistical mechanics of a Mexican-hat-type network with Depressing Synapses
Sub Title (in English)
Keyword(1) Synaptic depression
Keyword(2) Mexican-hat type interaction
Keyword(3) Mean-field analysis
Keyword(4) Rotating state
1st Author's Name Yasuhiko IGARASHI
1st Author's Affiliation Graduate School of Frontier Sciences, The University of Tokyo()
2nd Author's Name Masafumi OIZUMI
2nd Author's Affiliation Graduate School of Frontier Sciences, The University of Tokyo
3rd Author's Name Masato OKADA
3rd Author's Affiliation Graduate School of Frontier Sciences, The University of Tokyo:RIKEN Brain Science Institute
Date 2009-10-23
Paper # NC2009-40
Volume (vol) vol.109
Number (no) 252
Page pp.pp.-
#Pages 6
Date of Issue