[Seminar] Estimation of neural connections from partially observed neural spikes by Professor Noboru Murata

Abstract:

Estimating neural connections from multiple spike trains is an important task for analyzing mechanisms of information processing in the brain. There are many proposals for estimating connections between observed neurons, but most of them pay little attention on influence from unobserved neurons.  By introducing a probabilistic firing model of observed and unobserved neurons, we propose a method of infer the effects of unobserved neurons and estimating the connections of partially observed neurons.  Our proposed method is verified an validated with synthetic and real data.

This talk is based on: [https://doi.org/10.1016/j.neunet.2018.07.019]

Taishi Iwasaki, Hideitsu Hino, Masami Tatsuno, Shotaro Akaho, Noboru Murata, Estimation of neural connections from partially observed neural spikes, Neural Networks, 108, pp.172-191, 2018

Bigraphy:

Noboru Murata received the B.Eng., M.Eng., and Dr.Eng. degrees in mathematical engineering and information physics from the University of Tokyo, in 1987, 1989, and 1992, respectively. He was with GMD FIRST, Germany, and RIKEN, Japan. Since 2000, he joined Waseda University, Japan, where he is currently a Professor. His research interest includes the theoretical aspects of learning machines such as neural networks, focusing on the dynamics, and statistical properties of learning.