Asymptotic behaviour of neuron population models structured by elapsed-time
| Autor: | José A. Cañizo, Havva Yoldaş |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Steady state (electronics)
Applied Mathematics 010102 general mathematics structured population dynamics nonlinear asymptotic stability neuron populations Doeblin theory General Physics and Astronomy Statistical and Nonlinear Physics State (functional analysis) Space (mathematics) 01 natural sciences Constructive 010101 applied mathematics Nonlinear system Mathematics - Analysis of PDEs 35F15 35B10 92B20 FOS: Mathematics Applied mathematics Spectral gap Relaxation (approximation) 0101 mathematics Mathematical Physics Variable (mathematics) Mathematics Analysis of PDEs (math.AP) |
| Zdroj: | BIRD: BCAM's Institutional Repository Data instname |
| DOI: | 10.48550/arxiv.1803.07062 |
| Popis: | We study two population models describing the dynamics of interacting neurons, initially proposed by Pakdaman et al (2010 Nonlinearity 23 55–75) and Pakdaman et al (2014 J. Math. Neurosci. 4 1–26). In the first model, the structuring variable s represents the time elapsed since its last discharge, while in the second one neurons exhibit a fatigue property and the structuring variable is a generic 'state'. We prove existence of solutions and steady states in the space of finite, nonnegative measures. Furthermore, we show that solutions converge to the equilibrium exponentially in time in the case of weak nonlinearity (i.e. weak connectivity). The main innovation is the use of Doeblin's theorem from probability in order to show the existence of a spectral gap property in the linear (no-connectivity) setting. Relaxation to the steady state for the nonlinear models is then proved by a constructive perturbation argument. MTM2014-52056-P, MTM2017-85067-P, "la Caixa" Foundation |
| Databáze: | OpenAIRE |
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