Presentation 2004-11-27
STDP network Transforms Spatiotemporal Pattern to Synchrony
Ryosuke HOSAKA, Osamu ARAKI, Tohru IKEGUCHI,
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Abstract(in English) Recent experimental results show the sensitivity of synaptic plasticity to the timing of synaptic events and postsynaptic firings (spike timing dependent plasticity: STDP). Although many of studies have been made on STDP, little is known about the effect of STDP on the relation between external input patterns to the recurrent neural network and its output spikes. In this study, we examine this relation by computer simulations of a spiking neural network with STDP. We find that STDP organized the neural network to transform an external spatiotemporal input pattern into a synchronous firing. The transformation could be achieved on the multiple inputs.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Spike-Timing-Dependent Plasticity / Spatiotemporal pattern / Synchrony / Nagumo-Sato neuron
Paper # NLP2004-85
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Committee NLP
Conference Date 2004/11/20(1days)
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Registration To Nonlinear Problems (NLP)
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) STDP network Transforms Spatiotemporal Pattern to Synchrony
Sub Title (in English)
Keyword(1) Spike-Timing-Dependent Plasticity
Keyword(2) Spatiotemporal pattern
Keyword(3) Synchrony
Keyword(4) Nagumo-Sato neuron
1st Author's Name Ryosuke HOSAKA
1st Author's Affiliation Graduate school of Science and Engineering, Saitama University()
2nd Author's Name Osamu ARAKI
2nd Author's Affiliation Department of Applied Physics, Tokyo University of Science
3rd Author's Name Tohru IKEGUCHI
3rd Author's Affiliation Graduate school of Science and Engineering, Saitama University
Date 2004-11-27
Paper # NLP2004-85
Volume (vol) vol.104
Number (no) 472
Page pp.pp.-
#Pages 6
Date of Issue