{"title":"Multilayer structure-induced collective dynamics in uncoupled memristive Rulkov neurons: Impact of field coupling and intralayer connections","authors":"Deivasundari Muthukumar , Dorsa Nezhad Hajian , Hayder Natiq , Mahtab Mehrabbeik , Nikhil Pal , Sajad Jafari","doi":"10.1016/j.physd.2024.134464","DOIUrl":null,"url":null,"abstract":"<div><div>In this study, we explore a multilayered structure in which the coupled oscillators of one layer serve as a shared medium for an uncoupled population of neurons. The layers function based on the memristive Rulkov map, and interlayer connections are established through magnetic flux variables, referred to as field coupling. We adopt both hybrid (electrical and chemical) and exclusively chemical couplings for intralayer connectivity. The study highlights the pivotal role of the reversal potential in the dynamics of chemical coupling, while the firing threshold and sigmoid slope play lesser roles. Synchrony analysis reveals distinct synchronization behaviors between the layers. Notably, although the coupled layer can achieve phase synchrony, it fails to induce comparable synchrony in the uncoupled layer. Our findings also highlight the emergence of distinct collective dynamics in the uncoupled network, influenced by the coherence level of the flux variables in the coupled layer. Specifically, incoherent, two-clustered, and globally synchronized oscillations of flux variables in the coupled layer lead to chimera states, two-cluster synchronization, and complete synchronization in the uncoupled neurons, respectively.</div></div>","PeriodicalId":20050,"journal":{"name":"Physica D: Nonlinear Phenomena","volume":"471 ","pages":"Article 134464"},"PeriodicalIF":2.7000,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physica D: Nonlinear Phenomena","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167278924004147","RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 0
Abstract
In this study, we explore a multilayered structure in which the coupled oscillators of one layer serve as a shared medium for an uncoupled population of neurons. The layers function based on the memristive Rulkov map, and interlayer connections are established through magnetic flux variables, referred to as field coupling. We adopt both hybrid (electrical and chemical) and exclusively chemical couplings for intralayer connectivity. The study highlights the pivotal role of the reversal potential in the dynamics of chemical coupling, while the firing threshold and sigmoid slope play lesser roles. Synchrony analysis reveals distinct synchronization behaviors between the layers. Notably, although the coupled layer can achieve phase synchrony, it fails to induce comparable synchrony in the uncoupled layer. Our findings also highlight the emergence of distinct collective dynamics in the uncoupled network, influenced by the coherence level of the flux variables in the coupled layer. Specifically, incoherent, two-clustered, and globally synchronized oscillations of flux variables in the coupled layer lead to chimera states, two-cluster synchronization, and complete synchronization in the uncoupled neurons, respectively.
期刊介绍:
Physica D (Nonlinear Phenomena) publishes research and review articles reporting on experimental and theoretical works, techniques and ideas that advance the understanding of nonlinear phenomena. Topics encompass wave motion in physical, chemical and biological systems; physical or biological phenomena governed by nonlinear field equations, including hydrodynamics and turbulence; pattern formation and cooperative phenomena; instability, bifurcations, chaos, and space-time disorder; integrable/Hamiltonian systems; asymptotic analysis and, more generally, mathematical methods for nonlinear systems.