Presentation 2014-07-26
Evaluation of Chaotic Dynamics in Izhikevich Neuron Model using Lyapunov Exponent with Saltation Matrix
Sou NOBUKAWA, Haruhiko NISHIMURA, Teruya YAMANISHI, Jian-Qin LIU,
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Abstract(in English) Izhikevich neuron model, which combines continuous spike-generation mechanisms and discontinuous resetting process after spikes as a hybrid system, can reproduce major spike patterns observed in the cerebral cortex by only tuning a few parameters of it and also exhibit chaotic states in specific conditions. However, there are a few studies concerning the chaotic states over a large range of parameters due to the difficulty of dealing with the state dependent jump on the resetting process in this model. In this study, we examine the dependence of the system behavior on the resetting parameters by using Lyapunov exponent with saltation matrix and Poincare section methods, and classify the routes to chaos.
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Keyword(in English) Izhikevich neuron model / chaos / saltation matrix / Lyapunov exponent
Paper # NC2014-18
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Committee NC
Conference Date 2014/7/19(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) Evaluation of Chaotic Dynamics in Izhikevich Neuron Model using Lyapunov Exponent with Saltation Matrix
Sub Title (in English)
Keyword(1) Izhikevich neuron model
Keyword(2) chaos
Keyword(3) saltation matrix
Keyword(4) Lyapunov exponent
1st Author's Name Sou NOBUKAWA
1st Author's Affiliation Graduate School for Nursing, University of Hyogo()
2nd Author's Name Haruhiko NISHIMURA
2nd Author's Affiliation Graduate School of Applied Informatics, University of Hyogo
3rd Author's Name Teruya YAMANISHI
3rd Author's Affiliation Department of Management Information Science, Fukui University of Technology
4th Author's Name Jian-Qin LIU
4th Author's Affiliation Center for Information and Neural Networks, National Institute of Information and Communications Technology
Date 2014-07-26
Paper # NC2014-18
Volume (vol) vol.114
Number (no) 154
Page pp.pp.-
#Pages 7
Date of Issue