A mean-field model of Integrate-and-Fire neurons: non-linear stability of the stationary solutions

Fuente: arXiv
Salvato in:
Dettagli Bibliografici
Autore principale: Cormier, Quentin
Natura: Preprint
Pubblicazione: 2020
Soggetti:
Accesso online:
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866914961532387328
author Cormier, Quentin
author_facet Cormier, Quentin
contents We investigate a stochastic network composed of Integrate-and-Fire spiking neurons, focusing on its mean-field asymptotics. We consider an invariant probability measure of the McKean-Vlasov equation and establish an explicit sufficient condition to ensure the local stability of this invariant distribution. Furthermore, we prove a conjecture proposed initially by J. Touboul and P. Robert regarding the bistable nature of a specific instance of this neuronal model.
format Preprint
id arxiv_https___arxiv_org_abs_2002_08649
institution arXiv
publishDate 2020
record_format arxiv
spellingShingle A mean-field model of Integrate-and-Fire neurons: non-linear stability of the stationary solutions
Cormier, Quentin
Probability
Analysis of PDEs
60H10 (Primary) 60K35, 45D05, 37A30 (Secondary)
We investigate a stochastic network composed of Integrate-and-Fire spiking neurons, focusing on its mean-field asymptotics. We consider an invariant probability measure of the McKean-Vlasov equation and establish an explicit sufficient condition to ensure the local stability of this invariant distribution. Furthermore, we prove a conjecture proposed initially by J. Touboul and P. Robert regarding the bistable nature of a specific instance of this neuronal model.
title A mean-field model of Integrate-and-Fire neurons: non-linear stability of the stationary solutions
topic Probability
Analysis of PDEs
60H10 (Primary) 60K35, 45D05, 37A30 (Secondary)
url https://arxiv.org/abs/2002.08649