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Periodicity induced by noise and interaction in the kinetic mean-field FitzHugh-Nagumo model

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abstract

We consider the long-time behavior of a population of mean-field oscillators modeling the activity of interacting excitable neurons in large population. Each neuron is represented by its voltage and recovery variables, which are solution to a FitzHugh-Nagumo system, and interacts with the rest of the population through a mean-field linear coupling, in the presence of noise. The aim of the paper is to study the emergence of collective oscillatory behaviors induced by noise and interaction on such a system. The main difficulty of the present analysis is that we consider the kinetic case, where interaction and noise are only imposed on the voltage variable. We prove the existence of a stable cycle for the infinite population system, in a regime where the local dynamics is small.

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math.ST 1

years

2025 1

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REJECT 1

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Statistical estimation of a mean-field FitzHugh-Nagumo model

math.ST · 2025-01-08 · reject · novelty 5.0

The paper proves a Bernstein inequality and an oracle inequality for kernel estimation of the Vlasov-Fokker-Planck density, and gives a moment estimator for FitzHugh-Nagumo parameters that contains algebraic errors in its estimating equations.

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  • Statistical estimation of a mean-field FitzHugh-Nagumo model math.ST · 2025-01-08 · reject · none · ref 22 · internal anchor

    The paper proves a Bernstein inequality and an oracle inequality for kernel estimation of the Vlasov-Fokker-Planck density, and gives a moment estimator for FitzHugh-Nagumo parameters that contains algebraic errors in its estimating equations.