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.
|Journal||Journal of Physics: Conference Series|
|Publication status||Published - 2016 Apr 6|
|Event||International Meeting on High-Dimensional Data-Driven Science, HD3 2015 - Kyoto, Japan|
Duration: 2015 Dec 14 → 2015 Dec 17
ASJC Scopus subject areas
- Physics and Astronomy(all)