Literature DB >> 28764400

Chimera states in a multilayer network of coupled and uncoupled neurons.

Soumen Majhi1, Matjaž Perc2, Dibakar Ghosh1.   

Abstract

We study the emergence of chimera states in a multilayer neuronal network, where one layer is composed of coupled and the other layer of uncoupled neurons. Through the multilayer structure, the layer with coupled neurons acts as the medium by means of which neurons in the uncoupled layer share information in spite of the absence of physical connections among them. Neurons in the coupled layer are connected with electrical synapses, while across the two layers, neurons are connected through chemical synapses. In both layers, the dynamics of each neuron is described by the Hindmarsh-Rose square wave bursting dynamics. We show that the presence of two different types of connecting synapses within and between the two layers, together with the multilayer network structure, plays a key role in the emergence of between-layer synchronous chimera states and patterns of synchronous clusters. In particular, we find that these chimera states can emerge in the coupled layer regardless of the range of electrical synapses. Even in all-to-all and nearest-neighbor coupling within the coupled layer, we observe qualitatively identical between-layer chimera states. Moreover, we show that the role of information transmission delay between the two layers must not be neglected, and we obtain precise parameter bounds at which chimera states can be observed. The expansion of the chimera region and annihilation of cluster and fully coherent states in the parameter plane for increasing values of inter-layer chemical synaptic time delay are illustrated using effective range measurements. These results are discussed in the light of neuronal evolution, where the coexistence of coherent and incoherent dynamics during the developmental stage is particularly likely.

Mesh:

Year:  2017        PMID: 28764400     DOI: 10.1063/1.4993836

Source DB:  PubMed          Journal:  Chaos        ISSN: 1054-1500            Impact factor:   3.642


  11 in total

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2.  Chimera states and cluster solutions in Hindmarsh-Rose neural networks with state resetting process.

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Journal:  Cogn Neurodyn       Date:  2021-06-30       Impact factor: 5.082

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Review 4.  Complex networks and deep learning for EEG signal analysis.

Authors:  Zhongke Gao; Weidong Dang; Xinmin Wang; Xiaolin Hong; Linhua Hou; Kai Ma; Matjaž Perc
Journal:  Cogn Neurodyn       Date:  2020-08-29       Impact factor: 3.473

5.  A two-layered brain network model and its chimera state.

Authors:  Ling Kang; Changhai Tian; Siyu Huo; Zonghua Liu
Journal:  Sci Rep       Date:  2019-10-07       Impact factor: 4.379

6.  Cooperation on Interdependent Networks by Means of Migration and Stochastic Imitation.

Authors:  Sayantan Nag Chowdhury; Srilena Kundu; Maja Duh; Matjaž Perc; Dibakar Ghosh
Journal:  Entropy (Basel)       Date:  2020-04-23       Impact factor: 2.524

7.  A New Chaotic System with Stable Equilibrium: Entropy Analysis, Parameter Estimation, and Circuit Design.

Authors:  Tomasz Kapitaniak; S Alireza Mohammadi; Saad Mekhilef; Fawaz E Alsaadi; Tasawar Hayat; Viet-Thanh Pham
Journal:  Entropy (Basel)       Date:  2018-09-05       Impact factor: 2.524

8.  Dynamics of a multiplex neural network with delayed couplings.

Authors:  Xiaochen Mao; Xingyong Li; Weijie Ding; Song Wang; Xiangyu Zhou; Lei Qiao
Journal:  Appl Math Mech       Date:  2021-02-02       Impact factor: 2.866

9.  Emergent Dynamics and Spatio Temporal Patterns on Multiplex Neuronal Networks.

Authors:  Umesh Kumar Verma; G Ambika
Journal:  Front Comput Neurosci       Date:  2021-12-02       Impact factor: 2.380

10.  Interlayer Connectivity Affects the Coherence Resonance and Population Activity Patterns in Two-Layered Networks of Excitatory and Inhibitory Neurons.

Authors:  David Ristič; Marko Gosak
Journal:  Front Comput Neurosci       Date:  2022-04-18       Impact factor: 3.387

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