Graph structure modeling for multi-neuronal spike data

Shotaro Akaho, Sho Higuchi, Taishi Iwasaki, Hideitsu Hino, Masami Tatsuno, Noboru Murata

Research output: Contribution to journalConference articlepeer-review


We propose a method to extract connectivity between neurons for extracellularly recorded multiple spike trains. The method removes pseudo-correlation caused by propagation of information along an indirect pathway, and is also robust against the influence from unobserved neurons. The estimation algorithm consists of iterations of a simple matrix inversion, which is scalable to large data sets. The performance is examined by synthetic spike data.

Original languageEnglish
Article number012012
JournalJournal of Physics: Conference Series
Issue number1
Publication statusPublished - 2016 Apr 6
EventInternational Meeting on High-Dimensional Data-Driven Science, HD3 2015 - Kyoto, Japan
Duration: 2015 Dec 142015 Dec 17

ASJC Scopus subject areas

  • Physics and Astronomy(all)


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