Chimera State in the Network of Fractional-Order FitzHugh–Nagumo Neurons

The fractional calculus in the neuronal models provides the memory properties. In the fractional-order neuronal model, the dynamics of the neuron depends on the derivative order, which can produce various types of memory-dependent dynamics. In this paper, the behaviors of the coupled fractional-orde...

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Main Authors: Janarthanan Ramadoss, Sajedeh Aghababaei, Fatemeh Parastesh, Karthikeyan Rajagopal, Sajad Jafari, Iqtadar Hussain
Format: Article
Language:English
Published: Wiley 2021-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2021/2437737
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author Janarthanan Ramadoss
Sajedeh Aghababaei
Fatemeh Parastesh
Karthikeyan Rajagopal
Sajad Jafari
Iqtadar Hussain
author_facet Janarthanan Ramadoss
Sajedeh Aghababaei
Fatemeh Parastesh
Karthikeyan Rajagopal
Sajad Jafari
Iqtadar Hussain
author_sort Janarthanan Ramadoss
collection DOAJ
description The fractional calculus in the neuronal models provides the memory properties. In the fractional-order neuronal model, the dynamics of the neuron depends on the derivative order, which can produce various types of memory-dependent dynamics. In this paper, the behaviors of the coupled fractional-order FitzHugh–Nagumo neurons are investigated. The effects of the coupling strength and the derivative order are under consideration. It is revealed that the level of the synchronization is decreased by decreasing the derivative order, and the chimera state emerges for stronger couplings. Furthermore, the patterns of the formed chimeras rely on the order of the derivatives.
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institution Kabale University
issn 1076-2787
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language English
publishDate 2021-01-01
publisher Wiley
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spelling doaj-art-8d322f9e2efc4c18bb7ef3165657e6b12025-02-03T01:24:49ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/24377372437737Chimera State in the Network of Fractional-Order FitzHugh–Nagumo NeuronsJanarthanan Ramadoss0Sajedeh Aghababaei1Fatemeh Parastesh2Karthikeyan Rajagopal3Sajad Jafari4Iqtadar Hussain5Centre for Artificial Intelligence, Chennai Institute of Technology, Malayambakkam, IndiaDepartment of Biomedical Engineering, Amirkabir University of Technology, No. 350, Hafez Ave, Valiasr Square, Tehran 159163-4311, IranDepartment of Biomedical Engineering, Amirkabir University of Technology, No. 350, Hafez Ave, Valiasr Square, Tehran 159163-4311, IranCentre for Nonlinear Systems, Chennai Institute of Technology, Malayambakkam, IndiaDepartment of Biomedical Engineering, Amirkabir University of Technology, No. 350, Hafez Ave, Valiasr Square, Tehran 159163-4311, IranDepartment of Mathematics, Statistics and Physics, Qatar University, Doha 2713, QatarThe fractional calculus in the neuronal models provides the memory properties. In the fractional-order neuronal model, the dynamics of the neuron depends on the derivative order, which can produce various types of memory-dependent dynamics. In this paper, the behaviors of the coupled fractional-order FitzHugh–Nagumo neurons are investigated. The effects of the coupling strength and the derivative order are under consideration. It is revealed that the level of the synchronization is decreased by decreasing the derivative order, and the chimera state emerges for stronger couplings. Furthermore, the patterns of the formed chimeras rely on the order of the derivatives.http://dx.doi.org/10.1155/2021/2437737
spellingShingle Janarthanan Ramadoss
Sajedeh Aghababaei
Fatemeh Parastesh
Karthikeyan Rajagopal
Sajad Jafari
Iqtadar Hussain
Chimera State in the Network of Fractional-Order FitzHugh–Nagumo Neurons
Complexity
title Chimera State in the Network of Fractional-Order FitzHugh–Nagumo Neurons
title_full Chimera State in the Network of Fractional-Order FitzHugh–Nagumo Neurons
title_fullStr Chimera State in the Network of Fractional-Order FitzHugh–Nagumo Neurons
title_full_unstemmed Chimera State in the Network of Fractional-Order FitzHugh–Nagumo Neurons
title_short Chimera State in the Network of Fractional-Order FitzHugh–Nagumo Neurons
title_sort chimera state in the network of fractional order fitzhugh nagumo neurons
url http://dx.doi.org/10.1155/2021/2437737
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