Multi-channels coupling-induced pattern transition in a tri-layer neuronal network

Fuqiang Wu, Ya Wang, Jun Ma, Wuyin Jin and Aatef Hobiny

Physica A: Statistical Mechanics and its Applications, 2018, vol. 493, issue C, 54-68

Abstract: Neurons in nerve system show complex electrical behaviors due to complex connection types and diversity in excitability. A tri-layer network is constructed to investigate the signal propagation and pattern formation by selecting different coupling channels between layers. Each layer is set as different states, and the local kinetics is described by Hindmarsh–Rose neuron model. By changing the number of coupling channels between layers and the state of the first layer, the collective behaviors of each layer and synchronization pattern of network are investigated. A statistical factor of synchronization on each layer is calculated. It is found that quiescent state in the second layer can be excited and disordered state in the third layer is suppressed when the first layer is controlled by a pacemaker, and the developed state is dependent on the number of coupling channels. Furthermore, the collapse in the first layer can cause breakdown of other layers in the network, and the mechanism is that disordered state in the third layer is enhanced when sampled signals from the collapsed layer can impose continuous disturbance on the next layer.

Keywords: Neuronal network; Collapse; Target wave; Pattern formation (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:493:y:2018:i:c:p:54-68

DOI: 10.1016/j.physa.2017.10.041

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