Presentation 2019-05-10
A Study on Reconstructing Common Inputs to Neurons using Superposed Recurrence Plots
Ryota Nomura, Tohru Ikeguchi,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) In this paper, we proposed a method for reconstructing common input data to single neurons only from observed spike sequences. First, we prepare a set of neurons which have different parameter values, or bifurcate, and we observe output spike sequences from the bifurcating neurons. Next, the observed spike sequences are transformed to a time series of firing rates, and a recurrence plot of the transformed firing rate time series is constructed. Finally, we applied the method of recovering a source input from which a recurrence plot is constructed. The results show that the proposed scheme works well to reconstruct the common input applied to single neurons.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) superposed recurrence plot / point process / bifurcation
Paper # NLP2019-6
Date of Issue 2019-05-03 (NLP)

Conference Information
Committee NLP
Conference Date 2019/5/10(2days)
Place (in Japanese) (See Japanese page)
Place (in English) J:COM HoltoHALL OITA
Topics (in Japanese) (See Japanese page)
Topics (in English) etc.
Chair Norikazu Takahashi(Okayama Univ.)
Vice Chair Hiroaki Kurokawa(Tokyo Univ. of Tech.)
Secretary Hiroaki Kurokawa(Hiroshima Inst. of Tech.)
Assistant Masayuki Kimura(Kyoto Univ.) / Yutaka Shimada(Saitama Univ.)

Paper Information
Registration To Technical Committee on Nonlinear Problems
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Study on Reconstructing Common Inputs to Neurons using Superposed Recurrence Plots
Sub Title (in English)
Keyword(1) superposed recurrence plot
Keyword(2) point process
Keyword(3) bifurcation
1st Author's Name Ryota Nomura
1st Author's Affiliation Tokyo University of Science(Tokyo Univ. Science)
2nd Author's Name Tohru Ikeguchi
2nd Author's Affiliation Tokyo University of Science(Tokyo Univ. Science)
Date 2019-05-10
Paper # NLP2019-6
Volume (vol) vol.119
Number (no) NLP-19
Page pp.pp.29-34(NLP),
#Pages 6
Date of Issue 2019-05-03 (NLP)