Cofré, R.; Maldonado, C.; Rosas, F. Large Deviations Properties of Maximum Entropy Markov Chains from Spike Trains. Entropy2018, 20, 573.
Cofré, R.; Maldonado, C.; Rosas, F. Large Deviations Properties of Maximum Entropy Markov Chains from Spike Trains. Entropy 2018, 20, 573.
Cofré, R.; Maldonado, C.; Rosas, F. Large Deviations Properties of Maximum Entropy Markov Chains from Spike Trains. Entropy2018, 20, 573.
Cofré, R.; Maldonado, C.; Rosas, F. Large Deviations Properties of Maximum Entropy Markov Chains from Spike Trains. Entropy 2018, 20, 573.
Abstract
We consider the maximum entropy Markov chain inference approach to characterize the collective statistics of neuronal spike trains, focusing on the statistical properties of the inferred model. We review large deviations techniques useful in this context to describe properties of accuracy and convergence in terms of sampling size. We use these results to study the statistical fluctuation of correlations, distinguishability and irreversibility of maximum entropy Markov chains. We illustrate these applications using simple examples where the large deviation rate function is explicitly obtained for maximum entropy models of relevance in this field.
Keywords
computational neuroscience; spike train statistics; maximum entropy principle; large deviation theory; out-of-equilibrium statistical mechanics; thermodynamic formalism; entropy production
Subject
Computer Science and Mathematics, Applied Mathematics
Copyright:
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