Presentation 1998/11/17
Neural Information Processing by Post-Inhibitory Rebound Firing
Ryoko Futami, Shin-ichiro Kanoh, Nozomu Hoshimiya,
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Abstract(in English) A neural network model that can hold the pattern of input spike time is proposed. The model is composed of weakly coupled neural oscillators, each of which contains paired inhibitory spiking neurons and mutual connections to elicit posit-inhibitory rebound firings. It is shown that this mechanism can detect the small time-differences between input spikes and can hold the information on the order of them. The use of post-inhibitory rebound firing makes the free-running frequency of oscillators not so sensitive to the strength of mutual connection. For the computer simulations, Hodgkin-Huxley equations are utilized. It is confirmed that an appropriate CMOS-type hardware neuron model can also generate post-inhibitory rebound firing.
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Keyword(in English) Temporal sequence / Neural oscillator / Short-term memory
Paper # NC98-57
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Committee NC
Conference Date 1998/11/17(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) Neural Information Processing by Post-Inhibitory Rebound Firing
Sub Title (in English)
Keyword(1) Temporal sequence
Keyword(2) Neural oscillator
Keyword(3) Short-term memory
1st Author's Name Ryoko Futami
1st Author's Affiliation Department of Electronics, Graduate School of Engineering, Tohoku University()
2nd Author's Name Shin-ichiro Kanoh
2nd Author's Affiliation Department of Electronics, Graduate School of Engineering, Tohoku University
3rd Author's Name Nozomu Hoshimiya
3rd Author's Affiliation Department of Electronics, Graduate School of Engineering, Tohoku University
Date 1998/11/17
Paper # NC98-57
Volume (vol) vol.98
Number (no) 401
Page pp.pp.-
#Pages 8
Date of Issue