Asymptotic Approximation of Fading Mode in Neurooscillator Dynamics

Fuente: arXiv
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Autores principales: Preobrazhenskaia, Margarita, Zelenova, Vera
Formato: Preprint
Publicado: 2024
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author Preobrazhenskaia, Margarita
Zelenova, Vera
author_facet Preobrazhenskaia, Margarita
Zelenova, Vera
contents We consider a system consisting of two delay differential equations with a large parameter, modeling the association of a pair of neurooscillators. The unknown functions describe the changes in the normalized membrane potentials of neurons over time, with the large parameter characterizing the speed of electrical processes. The first equation is separated from the system and represents a generalized Hutchinson equation. This equation, as known, possesses periodic solutions with high peaks over the period. The second equation is also based on the generalized Hutchinson equation, but with an additional term, linking it to an oscillator satisfying the first equation. For the second equation, it is possible to asymptotically construct the so-called fading neuron mode, which is as follows: for any natural number $n$, one can adjust the parameters of the problem in such a way that the solution is asymptotically close to a periodic function with high peaks over $n$ periods, and then, after a transient process represented by decreasing peaks, becomes asymptotically small.
format Preprint
id arxiv_https___arxiv_org_abs_2406_06155
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Asymptotic Approximation of Fading Mode in Neurooscillator Dynamics
Preobrazhenskaia, Margarita
Zelenova, Vera
Exactly Solvable and Integrable Systems
Dynamical Systems
Adaptation and Self-Organizing Systems
We consider a system consisting of two delay differential equations with a large parameter, modeling the association of a pair of neurooscillators. The unknown functions describe the changes in the normalized membrane potentials of neurons over time, with the large parameter characterizing the speed of electrical processes. The first equation is separated from the system and represents a generalized Hutchinson equation. This equation, as known, possesses periodic solutions with high peaks over the period. The second equation is also based on the generalized Hutchinson equation, but with an additional term, linking it to an oscillator satisfying the first equation. For the second equation, it is possible to asymptotically construct the so-called fading neuron mode, which is as follows: for any natural number $n$, one can adjust the parameters of the problem in such a way that the solution is asymptotically close to a periodic function with high peaks over $n$ periods, and then, after a transient process represented by decreasing peaks, becomes asymptotically small.
title Asymptotic Approximation of Fading Mode in Neurooscillator Dynamics
topic Exactly Solvable and Integrable Systems
Dynamical Systems
Adaptation and Self-Organizing Systems
url https://arxiv.org/abs/2406.06155