Work

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

Year: 2025

Type: article

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.

Source: Communications in Mathematical Physics

DOI: 10.1007/s00220-025-05287-5

Authors: María J. Cáceres, José A. Cañizo, Alejandro Ramos-Lora

Institution: Universidad de Granada

Language: English

Topic: Neural dynamics and brain function

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: hybrid

Estimated APC paid: $2,990

Funder: Universidad de Granada