On the Asymptotic Behavior of the NNLIF Neuron Model for General Connectivity Strength

Abstract We prove new results on the asymptotic behavior of the nonlinear integrate-and-fire neuron model. Among them, we give a criterion for the linearized stability or instability of equilibria, without restriction on the connectivity parameter, which provides a proof of stability or instability in some cases. In all cases, this criterion can be checked numerically, allowing us to give a full picture of the stable and unstable equilibria depending on the connectivity parameter b and transmission delay d . We also give further spectral results on the associated linear equation, and use them to give improved results on the nonlinear stability of equilibria for weak connectivity, and on the link between linearized and nonlinear stability.

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Publication Details

Journal
Communications in Mathematical Physics
Published
2025-04-21
DOI
https://doi.org/10.1007/s00220-025-05287-5
Citations
3
Primary Topic
Neural dynamics and brain function
Type
article
Field-Weighted Citation Impact
4.29

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article

On the Asymptotic Behavior of the NNLIF Neuron Model for General Connectivity Strength

María J. Cáceres, Alejandro Ramos-Lora, José A. Cañizo
3 citations
Communications in Mathematical Physics
Neural dynamics and brain function
4.29
article

On the Asymptotic Behavior of the NNLIF Neuron Model for General Connectivity Strength

María J. Cáceres, Alejandro Ramos-Lora, José A. Cañizo
article en
3 citations

Abstract

Abstract We prove new results on the asymptotic behavior of the nonlinear integrate-and-fire neuron model. Among them, we give a criterion for the linearized stability or instability of equilibria, without restriction on the connectivity parameter, which provides a proof of stability or instability in some cases. In all cases, this criterion can be checked numerically, allowing us to give a full picture of the stable and unstable equilibria depending on the connectivity parameter b and transmission delay d . We also give further spectral results on the associated linear equation, and use them to give improved results on the nonlinear stability of equilibria for weak connectivity, and on the link between linearized and nonlinear stability.

Communications in Mathematical PhysicsVol. 406(5)
Universidad de Granada (ES)
Universidad de Granada
Openalex Percentile: Top 6%
Neural dynamics and brain function
4.29
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On the Asymptotic Behavior of the NNLIF Neuron Model for General Connectivity Strength — María J. Cáceres, Alejandro Ramos-Lora, et al. · Communications in Mathematical Physics (2025) | TGRS Research Map | TGRS