Please use this identifier to cite or link to this item: http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/1333
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dc.contributor.authorMOZUMDAR, KUNALen_US
dc.contributor.authorAMBIKA, G.en_US
dc.date.accessioned2018-11-12T10:49:55Z
dc.date.available2018-11-12T10:49:55Z
dc.date.issued2019-04en_US
dc.identifier.citationCommunications in Nonlinear Science and Numerical Simulation, 69, 320-328.en_US
dc.identifier.issn1007-5704en_US
dc.identifier.urihttp://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/1333-
dc.identifier.urihttps://doi.org/10.1016/j.cnsns.2018.09.026en_US
dc.description.abstractWe report the emergent dynamics of a community structured modular network of chaotic Hindmarsh-Rose (HR) neurons with inhibitory synapses. We find the inhibitory coupling between the neuronal modules lead to complete synchronization of neurons in a module, and also pushes modules into interesting sequences of travelling burst patterns. When dynamical time-scales vary for neurons in different modules, hence breaking the symmetry among them, we see specific sequences of travelling burst patterns that are characteristic of the time-scale mismatch and coupling strengths. Thus for a modular network with two time-scales, the neuronal communities enter into synchronized frequency locked clusters with the bursting sequences having recurring patterns. Our study provides a complete characterization of the spatio-temporal regularity in terms of frequency locking for temporal order and burst sequence patterns for spatial order in the collective dynamics of the neuronal clusters. Our results have significance in the process of information coding in terms of frequency of firing dynamics among neurons and in selective communication based on the sequences of bursts.en_US
dc.language.isoenen_US
dc.publisherElsevier B.V.en_US
dc.subjectModular inhibitory neuronal networksen_US
dc.subjectMultiple time-scaleen_US
dc.subjectTravelling burstsen_US
dc.subjectTOC-NOV-2018en_US
dc.subject2019en_US
dc.titleFrequency locking and travelling burst sequences in community structured network of inhibitory neurons with differing time-scalesen_US
dc.typeArticleen_US
dc.contributor.departmentDept. of Physicsen_US
dc.identifier.sourcetitleCommunications in Nonlinear Science and Numerical Simulationen_US
dc.publication.originofpublisherForeignen_US
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