An Application of Directed Information to Infer Synaptic Connectivity

Juliana M. de Assis, Francisco M. de Assis

DOI: 10.14209/sbrt.2016.53

Evento: XXXIV Simpósio Brasileiro de Telecomunicações (SBrT2016)

Keywords:

Abstract

This paper introduces a review on directed in-formation and its application as a causality measure among two stochastic processes. Jiao’s method for estimating directed information from data, using the context tree weighting algorithm is described and then used to infer synaptic connectivity from simulated neurons, from their neural spike trains only. It is observed that positive values of directed information estimates correctly predicted synaptic connections.

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