Spatio-Temporal Linear Response of Spiking Neuronal Network Models

Rodrigo Cofre 1 Bruno Cessac 2
2 NEUROMATHCOMP - Mathematical and Computational Neuroscience
CRISAM - Inria Sophia Antipolis - Méditerranée , JAD - Laboratoire Jean Alexandre Dieudonné : UMR6621
Abstract : We study the impact of a weak time-dependent external stimulus on the collective statistics of spiking responses in neuronal networks. We extend the current knowledge, assessing the impact over firing rates and cross correlations, to any higher order spatio-temporal correlation [1]. Our approach is based on Gibbs distributions (in a general setting considering non stationary dynamics and infinite memory) [2] and linear response theory. The linear response is written in terms of a correlation matrix, computed with respect to the spiking dynamics without stimulus. We give an example of application in a conductance based integrate-and fire model.
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https://hal.inria.fr/hal-01235318
Contributeur : Bruno Cessac <>
Soumis le : lundi 30 novembre 2015 - 08:24:17
Dernière modification le : jeudi 3 mai 2018 - 13:32:58
Document(s) archivé(s) le : mardi 1 mars 2016 - 10:52:56

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  • HAL Id : hal-01235318, version 1

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Rodrigo Cofre, Bruno Cessac. Spatio-Temporal Linear Response of Spiking Neuronal Network Models. ISCLANE 15, Sep 2015, Barcelone, Spain. 〈hal-01235318〉

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