Numerical Analysis of FitzHugh-Nagumo Neurons on Random Networks

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概要

• 論文の詳細を見る

• We investigate a model of randomly copuled neurons. The elements are FitzHgh-Nagumo excitable neurons. The interactions between them are the mixture of excitatory and inhibitory. When all interactions are excitatory, a rest state is globally stable due to the excitability of neurons. Increasing the number of inhibitory connections, we observe the phase transition from the rest state to an oscillatory state. An analytical description for the critical point of the transition is obtained by means of random matrix theories for an infinite number of neurons, and the result is in good agreement with numerical simulation.

• 2006-04-20

著者

• Yanagita Tatsuo

  Laboratory Of Nonlinear Studies And Computation Research Institute For Electronic Science Hokkaido U

• Oyama Yoshihito

  Laboratory of Cryptography and Information Security Graduate School of Systems and Information Engin

• Ichinomiya Takashi

  Laboratory Of Nonlinear Studies And Computation Research Institute For Electronic Science Hokkaido U

• YANAGITA Tatsuo

  Laboratory of Nonlinear Studies and Computation, Research Institute for Electronic Science, Hokkaido University

• Oyama Yoshihito

  Laboratory of Nonlinear Studies and Computation, Research Institute for Electronic Science, Hokkaido University

関連論文

• Numerical Analysis of FitzHugh-Nagumo Neurons on Random Networks
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