A new method for multiple spike train analysis based on information discrepancy

Authors:
Guang-Li Wang;Xue Liu;Pu-Ming Zhang;Pei-Ji Liang
Affiliations:
Department of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China;Department of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China;Department of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China;Department of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
Venue:
ICONIP'06 Proceedings of the 13 international conference on Neural Information Processing - Volume Part I
Year:
2006

Citing 2
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Abstract

Simultaneous recording of multiple spike trains from population of neurons provides the possibility for understanding how neurons work together in response to various stimulations. But currently method is still lacking for researchers to perform multiple spike train data analysis and those existing techniques either allow people to analyze pair-wise neuronal activities only or are seriously subject to the selection of parameters. In this paper, a new measurement of information discrepancy, which is based on the comparisons of subsequence distributions, is applied to deal with a group of spike trains (n 2) and analyze the synchronization pattern among the neurons, where the analytical result mostly depends on the experimental data and is affected little by subjective interference.