Presentation 2015-11-01
Estimation of connectivity between neurons using SPIKE-distance
Kaori Kuroda, Mikio Hasegawa, Tohru Ikeguchi,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) To understand information processing in the brain, it is important to clarify the connectivity between neurons. We have already proposed the method of estimating connectivities between neurons only from observed multiple spike sequences by quantifying distance between spike sequences. To quantify distance between spike sequences, the spike time metric is used. However, the spike time metric involves a parameter. Then, we have to set an optimal parameter in the spike time metric. In this report, we used the SPIKE-distance instead of the spike time metric. The SPIKE-distance is a parameter-free measure which can quantify the distance between spike sequences. Using the SPIKE-distance, we estimate the network structure. As a result, the proposed method exhibits higher performance than the previous method.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) spike sequence / SPIKE-distance / partialization analysis
Paper # NLP2015-125
Date of Issue 2015-10-24 (NLP)

Conference Information
Committee NLP
Conference Date 2015/10/31(2days)
Place (in Japanese) (See Japanese page)
Place (in English) Nobumoto Ohama Memorial Hall
Topics (in Japanese) (See Japanese page)
Topics (in English) Nonlinear Problems, etc.
Chair Kenya Jinno(Nippon Inst. of Tech.)
Vice Chair Naoto Fujisaka(Hiroshima City Univ.)
Secretary Naoto Fujisaka(Tokyo Univ. of Science)
Assistant Hidehiro Nakano(Tokyo City Univ.) / Hiroyuki Asahara(Okayama Univ. of Science)

Paper Information
Registration To Technical Committee on Nonlinear Problems
Language ENG-JTITLE
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Estimation of connectivity between neurons using SPIKE-distance
Sub Title (in English)
Keyword(1) spike sequence
Keyword(2) SPIKE-distance
Keyword(3) partialization analysis
1st Author's Name Kaori Kuroda
1st Author's Affiliation Tokyo University of Science(Tokyo Univ. of Science)
2nd Author's Name Mikio Hasegawa
2nd Author's Affiliation Tokyo University of Science(Tokyo Univ. of Science)
3rd Author's Name Tohru Ikeguchi
3rd Author's Affiliation Tokyo University of Science(Tokyo Univ. of Science)
Date 2015-11-01
Paper # NLP2015-125
Volume (vol) vol.115
Number (no) NLP-284
Page pp.pp.105-109(NLP),
#Pages 5
Date of Issue 2015-10-24 (NLP)