The Statistics Of Spikes Trains For Some Simple Types Of Neuron Models

Olivier Faugeras 1 Théodore Papadopoulo 1 Jonathan Touboul 1, * Denis Talay 2 Etienne Tanré 2 Mireille Bossy 2
* Corresponding author
1 ODYSSEE - Computer and biological vision
DI-ENS - Département d'informatique de l'École normale supérieure, CRISAM - Inria Sophia Antipolis - Méditerranée , ENS Paris - École normale supérieure - Paris, Inria Paris-Rocquencourt, ENPC - École des Ponts ParisTech
2 TOSCA
INRIA Lorraine, CRISAM - Inria Sophia Antipolis - Méditerranée , UHP - Université Henri Poincaré - Nancy 1, Université Nancy 2, INPL - Institut National Polytechnique de Lorraine, CNRS - Centre National de la Recherche Scientifique : UMR7502
Abstract : This paper describes some preliminary results of a research program for characterizing the statistics of spikes trains for a variety of commonly used neuron models in the presence of stochastic noise and deterministic input. The main angle of attack of the problem is through the use of stochastic calculus and ways of representing (local)martingales as Brownianmotions by changing the time scale
Keywords : Integrate and fire neuron Brownian motion Integrate and fire with synaptic conductances spikes statistics
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Submitted on : Wednesday, October 24, 2007 - 11:21:01 AM
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Olivier Faugeras, Théodore Papadopoulo, Jonathan Touboul, Denis Talay, Etienne Tanré, et al.. The Statistics Of Spikes Trains For Some Simple Types Of Neuron Models. [Research Report] RR-5950, INRIA. 2007, pp.15. ⟨inria-00084905v4⟩

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