Inferring synaptic connections from spike data of multiple neurons

Ryota Kobayashi, Principles of Informatics Research Division, National Institute of Informatics, Tokyo, Japan
Vendredi 6 novembre 2015 à 11h, salle 26-00/332
Abstract
Correlations in neuronal activity are defined as "functional connections" between pairs of neurons. It is still unclear how the functional connectivity is related to underlying (physiological) synaptic connectivity. Here, we develop a coupled escape rate model (CERM) to infer synaptic connections from spike data of multiple neurons. Estimation performance of the proposed method was compared to that of the previous methods by using a simulated data generated by a realistic cortical network model, which consists of thousands of detailed model neurons (Kitano & Fukai, 2007). We conclude that CERM method is a promising method to infer synaptic connections from multiple neural spike data. This is joint work with Katsunori Kitano.
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