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1. Parameter Estimation for Spatio-Temporal Maximum Entropy Distributions: Application to Neural Spike Trains.

Author

Nasser, Hassan and Cessac, Bruno

Subjects
*SPATIO-temporal variation, *PARAMETERS (Statistics), *ESTIMATION theory, *MAXIMUM entropy method, *ENTROPY (Information theory), *ARTIFICIAL neural networks
Abstract

We propose a numerical method to learn maximum entropy (MaxEnt) distributions with spatio-temporal constraints from experimental spike trains. This is an extension of two papers, [10] and [4], which proposed the estimation of parameters where only spatial constraints were taken into account. The extension we propose allows one to properly handle memory effects in spike statistics, for large-sized neural networks. [ABSTRACT FROM AUTHOR]

Published
2014
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