Laetitia Colombani ; Pierre Le Bris - Propagation of chaos in mean field networks of FitzHugh-Nagumo neurons

mna:9748 - Mathematical Neuroscience and Applications, June 19, 2023, Volume 3 - https://doi.org/10.46298/mna.9748
Propagation of chaos in mean field networks of FitzHugh-Nagumo neuronsArticle

Authors: Laetitia Colombani ORCID; Pierre Le Bris

    In this article, we are interested in the behavior of a fully connected network of $N$ neurons, where $N$ tends to infinity. We assume that the neurons follow the stochastic FitzHugh-Nagumo model, whose specificity is the non-linearity with a cubic term. We prove a result of uniform in time propagation of chaos of this model in a mean-field framework. We also exhibit explicit bounds. We use a coupling method initially suggested by A. Eberle (arXiv:1305.1233), and recently extended in (1805.11387), known as the reflection coupling. We simultaneously construct a solution of the $N$-particle system and $N$ independent copies of the non-linear McKean-Vlasov limit in such a way that, considering an appropriate semi-metric that takes into account the various possible behaviors of the processes, the two solutions tend to get closer together as $N$ increases, uniformly in time. The reflection coupling allows us to deal with the non-convexity of the underlying potential in the dynamics of the quantities defining our network, and show independence at the limit for the system in mean field interaction with sufficiently small Lipschitz continuous interactions.


    Volume: Volume 3
    Published on: June 19, 2023
    Accepted on: May 3, 2023
    Submitted on: June 28, 2022
    Keywords: Mathematics - Probability,92C20, 60H10, 60F99

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