Presentation 2006-07-14
Higher Order Effects on Rate Reduction for Network of Hodgkin-Huxley Neurons
Masafumi OIZUMI, Yoichi MIYAWAKI, Masato OKADA,
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Abstract(in English) We propose a systematic method of rate reduction for a Hodgkin-Huxley type neural network model. In this context, Shriki et al. assumed that the threshold of f-I cureve for the reduced rate model linearly depends on the leak conductance of the Hodgkin-Huxley equation, while its gain remains constant. First, we will show that they have second order dependence. Second, we show that we can naturally reduce the Hodgkin-Huxley type network with second order interaction to an analog type neural network model with higher order interaction based on this finding. Finally, we construct statistical mechanics for the Hodgkin-Huxley type network with the Mexican-hat type interaction through our rate reduction technique.
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Keyword(in English) Hodgkin-Huxley equations / Rate reduction / Statistical mechanics / Mexican-hat type interaction
Paper # NC2006-40
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Committee NC
Conference Date 2006/7/7(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Higher Order Effects on Rate Reduction for Network of Hodgkin-Huxley Neurons
Sub Title (in English)
Keyword(1) Hodgkin-Huxley equations
Keyword(2) Rate reduction
Keyword(3) Statistical mechanics
Keyword(4) Mexican-hat type interaction
1st Author's Name Masafumi OIZUMI
1st Author's Affiliation Graduate School of Frontier Sciences, The University of Tokyo()
2nd Author's Name Yoichi MIYAWAKI
2nd Author's Affiliation NICT:ATR Computational Neuroscience Laboratories:RIKEN Brain Science Institute
3rd Author's Name Masato OKADA
3rd Author's Affiliation Graduate School of Frontier Sciences, The University of Tokyo:RIKEN Brain Science Institute
Date 2006-07-14
Paper # NC2006-40
Volume (vol) vol.106
Number (no) 163
Page pp.pp.-
#Pages 6
Date of Issue