Presentation 2000/11/23
Dynamics of a spiking neural network model driven by noise
Kazuhisa SAKAMOTO, Norihiro KATAYAMA, Mitsuyuki NAKAO, Mitsuaki YAMAMOTO,
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Abstract(in English) We constructed a symmetry neural network model driven by while noise, which consists of Hodgkin-Huxley-type model neurons with a global inhibition. Dynamics of the network model were studies by the computer simulation. In the network model, many neurons showed oscillatory activities approximately at 40Hz. The single neuronal dynamics in the low frequency range changed from a white noise-like spectral profile to an 1/f noise-like one as the global inhibition decreased. The network models involving the 1/f noise-like neuronal dynamics showed intermittent state transitions between metastable firing patterns, which were emerged under the random perturbations.
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Keyword(in English) Hodgkin-Huxley equations / noise / 1/f noise / symmetry connection / state transition
Paper # MBE2000-91
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Committee MBE
Conference Date 2000/11/23(1days)
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Registration To ME and Bio Cybernetics (MBE)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Dynamics of a spiking neural network model driven by noise
Sub Title (in English)
Keyword(1) Hodgkin-Huxley equations
Keyword(2) noise
Keyword(3) 1/f noise
Keyword(4) symmetry connection
Keyword(5) state transition
1st Author's Name Kazuhisa SAKAMOTO
1st Author's Affiliation Graduate School of Information Sciences, Tohoku University()
2nd Author's Name Norihiro KATAYAMA
2nd Author's Affiliation Graduate School of Information Sciences, Tohoku University
3rd Author's Name Mitsuyuki NAKAO
3rd Author's Affiliation Graduate School of Information Sciences, Tohoku University
4th Author's Name Mitsuaki YAMAMOTO
4th Author's Affiliation Graduate School of Information Sciences, Tohoku University
Date 2000/11/23
Paper # MBE2000-91
Volume (vol) vol.100
Number (no) 478
Page pp.pp.-
#Pages 8
Date of Issue