Statistics of spike trains: A dynamical systems perspective

Bruno Cessac 1, 2 Horacio Rostro 1 Juan-Carlos Vasquez 3 Thierry Viéville 4
1 NEUROMATHCOMP
CRISAM - Inria Sophia Antipolis - Méditerranée , INRIA Rocquencourt, ENS Paris - École normale supérieure - Paris, UNS - Université Nice Sophia Antipolis, CNRS - Centre National de la Recherche Scientifique : UMR8548
4 CORTEX - Neuromimetic intelligence
Inria Nancy - Grand Est, LORIA - AIS - Department of Complex Systems, Artificial Intelligence & Robotics
Abstract : We review recent results dealing with the analysis of spike train statistics in neural networks models, using methods from dynamical systems (thermodynamic formalism). We discuss why Gibbs distributions are natural candidates and present some consequences at the theoretical and algorithmic level.
Type de document :
Communication dans un congrès
Stochastic models in neuroscience, Jan 2010, Marseille, France. 2010
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https://hal.inria.fr/hal-00847435
Contributeur : Pierre Kornprobst <>
Soumis le : mardi 23 juillet 2013 - 15:40:23
Dernière modification le : jeudi 3 mai 2018 - 13:32:58

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  • HAL Id : hal-00847435, version 1

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Bruno Cessac, Horacio Rostro, Juan-Carlos Vasquez, Thierry Viéville. Statistics of spike trains: A dynamical systems perspective. Stochastic models in neuroscience, Jan 2010, Marseille, France. 2010. 〈hal-00847435〉

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