Entropy and information in neural spike trains: Progress on the sampling problem

Ilya Nemenman; William Bialek; Rob De Ruyter Van Steveninck

Entropy and information in neural spike trains: Progress on the sampling problem

Ilya Nemenman, William Bialek, Rob De Ruyter Van Steveninck

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Abstract

The Bayesian entropy estimator was used for reliable estimation of entropy-like quantities in information theoretic analysis of neural responses and other biological data. The estimator was applied to synthetic data inspired by experiments, and to real experimental spike trains. It was found that the estimator performed well even in the undersampled regime. This shows that the estimator can increase the possibilities for the information theoretic analysis of experiments.

Original language	English (US)
Article number	056111
Pages (from-to)	056111-1-056111-6
Journal	Physical Review E - Statistical, Nonlinear, and Soft Matter Physics
Volume	69
Issue number	5 1
State	Published - May 2004

All Science Journal Classification (ASJC) codes

Statistical and Nonlinear Physics
Statistics and Probability
Condensed Matter Physics

Cite this

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abstract = "The Bayesian entropy estimator was used for reliable estimation of entropy-like quantities in information theoretic analysis of neural responses and other biological data. The estimator was applied to synthetic data inspired by experiments, and to real experimental spike trains. It was found that the estimator performed well even in the undersampled regime. This shows that the estimator can increase the possibilities for the information theoretic analysis of experiments.",

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Entropy and information in neural spike trains: Progress on the sampling problem

Abstract

All Science Journal Classification (ASJC) codes

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