Quantifying the Synchrony Between Two Event Strings by Performing Inference in a Probabilistic Model

スポンサーリンク

概要

• 論文の詳細を見る

• We propose a novel measure to quantify the synchrony between two event strings, referred to as "stochastic event synchrony" (SES); it is computed by performing inference in a probabilistic model. Two approaches to infer the SES parameters are proposed; one is based on iterative conditional modes (a.k.a. "cyclic maximization"), the other on expectation maximization. SES can a.o. be used to (i) detect synchrony in pairs of spike trains; (ii) to quantify the firing reliability of a single neuron. As an illustration, the firing reliability of an in vitro rat neocortical pyramidal cell is computed.

• 社団法人電子情報通信学会の論文
• 2006-10-04

著者

• Dauwels Justin

  Riken Brain Science Institute

• Vialatte Francois

  RIKEN Brain Science Institute

関連論文

• Quantifying the Synchrony Between Two Event Strings by Performing Inference in a Probabilistic Model
• On Variational Message Passing and Its Relation to Other Message Passing Inference Algorithms

スポンサーリンク