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Journal Articles Entropy Year : 2014

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

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.

Dates and versions

hal-01096213 , version 1 (17-12-2014)

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Hassan Nasser, Bruno Cessac. Parameter Estimation for Spatio-Temporal Maximum Entropy Distributions: Application to Neural Spike Trains. Entropy, 2014, 16 (4), pp.2244-2277. ⟨10.3390/e16042244⟩. ⟨hal-01096213⟩
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