An elapsed time model for strongly coupled inhibitory and excitatory neural networks-Reference-Cited by-同舟云学术

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An elapsed time model for strongly coupled inhibitory and excitatory neural networks

Published:2021-11 Issue: Volume:425 Page:132977
ISSN:0167-2789
Container-title:Physica D: Nonlinear Phenomena
language:en
Short-container-title:Physica D: Nonlinear Phenomena

Author:

Torres Nicolás^ORCID,Cáceres María J.,Perthame Benoît,Salort Delphine

Funder

Horizon 2020

Horizon 2020 Framework Programme

H2020 Marie Skłodowska-Curie Actions

Agence nationale de la recherche

Publisher

Elsevier BV

Subject

Condensed Matter Physics,Statistical and Nonlinear Physics

Reference23 articles.

1. Dynamics of a structured neuron population;Pakdaman;Nonlinearity,2010

2. Adaptation and fatigue model for neuron networks and large time asymptotics in a nonlinear fragmentation equation;Pakdaman;J. Math. Neurosci.,2014

3. Asymptotic behaviour of neuron population models structured by elapsed-time;Cañizo;Nonlinearity,2019

4. Weak and strong connectivity regimes for a general time elapsed neuron network model;Mischler;J. Stat. Phys.,2018

5. Relaxation in time elapsed neuron network models in the weak connectivity regime;Mischler;Acta Appl. Math.,2018

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1. Oscillations in a Fully Connected Network of Leaky Integrate-and-Fire Neurons with a Poisson Spiking Mechanism;Journal of Nonlinear Science;2023-11-17

2. Topological-numerical analysis of a two-dimensional discrete neuron model;Chaos: An Interdisciplinary Journal of Nonlinear Science;2023-04-01

3. A multiple time renewal equation for neural assemblies with elapsed time model;Nonlinearity;2022-08-29

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