On the higher-order smallest ring star network of Chialvo neurons under diffusive couplings

Fuente: arXiv
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Autori principali: Nair, Anjana S., Ghosh, Indranil, Fatoyinbo, Hammed O., Muni, Sishu S.
Natura: Preprint
Pubblicazione: 2024
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author Nair, Anjana S.
Ghosh, Indranil
Fatoyinbo, Hammed O.
Muni, Sishu S.
author_facet Nair, Anjana S.
Ghosh, Indranil
Fatoyinbo, Hammed O.
Muni, Sishu S.
contents We put forward the dynamical study of a novel higher-order small network of Chialvo neurons arranged in a ring-star topology, with the neurons interacting via linear diffusive couplings. This model is perceived to imitate the nonlinear dynamical properties exhibited by a realistic nervous system where the neurons transfer information through higher-order multi-body interactions. We first analyze our model using the tools from nonlinear dynamics literature: fixed point analysis, Jacobian matrix, and bifurcation patterns. We observe the coexistence of chaotic attractors, and also an intriguing route to chaos starting from a fixed point, to period-doubling, to cyclic quasiperiodic closed invariant curves, to ultimately chaos. We numerically observe the existence of codimension-1 bifurcation patterns: saddle-node, period-doubling, and Neimark Sacker. We also qualitatively study the typical phase portraits of the system and numerically quantify chaos and complexity using the 0-1 test and sample entropy measure respectively. Finally, we study the collective behavior of the neurons in terms of two synchronization measures: the cross-correlation coefficient, and the Kuramoto order parameter.
format Preprint
id arxiv_https___arxiv_org_abs_2405_06000
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle On the higher-order smallest ring star network of Chialvo neurons under diffusive couplings
Nair, Anjana S.
Ghosh, Indranil
Fatoyinbo, Hammed O.
Muni, Sishu S.
Adaptation and Self-Organizing Systems
Chaotic Dynamics
We put forward the dynamical study of a novel higher-order small network of Chialvo neurons arranged in a ring-star topology, with the neurons interacting via linear diffusive couplings. This model is perceived to imitate the nonlinear dynamical properties exhibited by a realistic nervous system where the neurons transfer information through higher-order multi-body interactions. We first analyze our model using the tools from nonlinear dynamics literature: fixed point analysis, Jacobian matrix, and bifurcation patterns. We observe the coexistence of chaotic attractors, and also an intriguing route to chaos starting from a fixed point, to period-doubling, to cyclic quasiperiodic closed invariant curves, to ultimately chaos. We numerically observe the existence of codimension-1 bifurcation patterns: saddle-node, period-doubling, and Neimark Sacker. We also qualitatively study the typical phase portraits of the system and numerically quantify chaos and complexity using the 0-1 test and sample entropy measure respectively. Finally, we study the collective behavior of the neurons in terms of two synchronization measures: the cross-correlation coefficient, and the Kuramoto order parameter.
title On the higher-order smallest ring star network of Chialvo neurons under diffusive couplings
topic Adaptation and Self-Organizing Systems
Chaotic Dynamics
url https://arxiv.org/abs/2405.06000