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.
|ジャーナル||Journal of Physics: Conference Series|
|出版ステータス||Published - 2016 4月 6|
|イベント||International Meeting on High-Dimensional Data-Driven Science, HD3 2015 - Kyoto, Japan|
継続期間: 2015 12月 14 → 2015 12月 17
ASJC Scopus subject areas