Event-driven mathematical framework for noisy integrate-and-fire neuron networks: spike trains statistics via stochastic calculus, network analysis inspired by queuing theory and an event-driven simulator

Jonathan Touboul; Olivier Faugeras; Olivier Rochel

Journal articles

Event-driven mathematical framework for noisy integrate-and-fire neuron networks: spike trains statistics via stochastic calculus, network analysis inspired by queuing theory and an event-driven simulator

Jonathan Touboul ^{1, *} Olivier Faugeras ¹ Olivier Rochel ¹

* 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

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Journal articles

Domain :

Life Sciences [q-bio] / Neurons and Cognition [q-bio.NC]

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https://hal.inria.fr/hal-00784470
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Submitted on : Monday, February 4, 2013 - 1:13:38 PM
Last modification on : Thursday, July 1, 2021 - 5:58:03 PM
Long-term archiving on: : Monday, June 17, 2013 - 6:47:14 PM

Event-driven mathematical framework for noisy integrate-and-fire neuron networks: spike trains statistics via stochastic calculus, network analysis inspired by queuing theory and an event-driven simulator

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Event-driven mathematical framework for noisy integrate-and-fire neuron networks: spike trains statistics via stochastic calculus, network analysis inspired by queuing theory and an event-driven simulator

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385

324

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