Nonstationary chimeras in a neuronal network
Chimeras are special states that are composed of coexisting spatial domains of coherent and incoherent dynamics, which typically emerge in identically coupled oscillators. In this paper, we study a network of nonlocally coupled Hindmarsh-Rose neurons that are subject to an alternating current. We sh...
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Published in | Europhysics letters Vol. 123; no. 4; pp. 48003 - 48007 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
Les Ulis
EDP Sciences, IOP Publishing and Società Italiana di Fisica
01.08.2018
IOP Publishing |
Subjects | |
Online Access | Get full text |
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Summary: | Chimeras are special states that are composed of coexisting spatial domains of coherent and incoherent dynamics, which typically emerge in identically coupled oscillators. In this paper, we study a network of nonlocally coupled Hindmarsh-Rose neurons that are subject to an alternating current. We show that chimera states emerge when the neurons are connected through electrical synapses. The considered model has two coexisting attractors, namely a limit cycle and a chaotic attractor, to which the dynamics converges in dependence on the initial conditions. While earlier research reported the existence of chimeras in Hindmarsh-Rose neuronal networks mainly through chemical synapses, here we show that an alternating current in an electrically coupled network can also evoke chimeras, whereby the spatial positions of coherent and incoherent domains vary with time. Remarkably, we also observe chimera states in locally coupled neurons through electrical synapses, which reduce the relaxation of nonlocallity in the coupling configuration. The existence of nonstationary chimeras is confirmed by means of a local order parameter. |
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Bibliography: | publisher-ID:epl19281 ark:/67375/80W-TXR7FTRW-S href:https://epljournal.edpsciences.org/0295-5075/123/i=4/a=48003/article istex:0B83066E5636DFD7F0203433692DB2C0C851402F ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
ISSN: | 0295-5075 1286-4854 1286-4854 |
DOI: | 10.1209/0295-5075/123/48003 |