Dynamics, synchronization and traveling wave patterns of flux coupled network of Chay neurons.
Arnold tongue
Chay neuron
Imperfect chimera
Lyapunov stability theory
Master stability function
Journal
Bio Systems
ISSN: 1872-8324
Titre abrégé: Biosystems
Pays: Ireland
ID NLM: 0430773
Informations de publication
Date de publication:
28 Dec 2023
28 Dec 2023
Historique:
received:
11
10
2023
revised:
22
12
2023
accepted:
24
12
2023
medline:
2
1
2024
pubmed:
2
1
2024
entrez:
30
12
2023
Statut:
aheadofprint
Résumé
Studies in the literature have demonstrated the significance of the synchronization of neuronal electrical activity for signal transmission and information encoding. In light of this importance, we investigate the synchronization of the Chay neuron model using both theoretical analysis and numerical simulations. The Chay model is chosen for its comprehensive understanding of neuronal behavior and computational efficiency. Additionally, we explore the impact of electromagnetic induction, leading to the magnetic flux Chay neuron model. The single neuron model exhibits rich and complex dynamics for various parameter choices. We explore the bifurcation structure of the model through bifurcation diagrams and Lyapunov exponents. Subsequently, we extend our study to two coupled magnetic flux Chay neurons, identifying mode locking and structures reminiscent of Arnold's tongue. We evaluate the stability of the synchronized manifold using Lyapunov theory and confirm our findings through simulations. Expanding our study to networks of diffusively coupled flux Chay neurons, we observe coherent, incoherent, and imperfect chimera patterns. Our investigation of three network types highlights the impact of network topology on the emergent dynamics of the Chay neuron network. Regular networks exhibit diverse patterns, small-world networks demonstrate a critical transition to coherence, and random networks showcase synchronization at specific coupling strengths. These findings significantly contribute to our understanding of the synchronization patterns exhibited by the magnetic flux Chay neuron. To assess the synchronization stability of the Chay neuron network, we employ master stability function analysis.
Identifiants
pubmed: 38159671
pii: S0303-2647(23)00288-5
doi: 10.1016/j.biosystems.2023.105113
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
105113Informations de copyright
Copyright © 2023 Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Karthikeyan Rajagopal reports financial support was provided by Chennai Institute of Technology.