4.7 Article

Chimera states in a thermosensitive FitzHugh-Nagumo neuronal network

Journal

APPLIED MATHEMATICS AND COMPUTATION
Volume 410, Issue -, Pages -

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.amc.2021.126461

Keywords

Synchronization; Chimera state; Thermosensitive neurons; FitzHugh-Nagumo neuron

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The study demonstrates the close relationship between the temperature sensitivity of neurons and the impact of thermistor on neuron behavior, with the temperature change coefficient in the thermistor playing a key role in the occurrence of chaos state. When neurons and thermistors in the network have different characteristics, the network behavior changes, and distributions with different standard deviations can influence the synchronization and extent of the chimera state in the network.
Temperature can affect the action potential of a neuron such that the firing pattern is changed under its variation. To incorporate the effects of the temperature, recently, a thermosensitive neuron was proposed in which a thermistor was added to a simple FitzHugh-Nagumo neuron model. Here, thermosensitive neurons are studied to realize the consequence of the thermistor on the neurons' collective behavior. For specific coupling strengths, the chimera state is developed. The parameter region of the occurrence of the chimera state is obtained by computing the strength of incoherence and shows that the occurrence of the chimera is highly dependent on the coefficient of temperature change in the thermistor. Since, in reality, the neurons are not identical and also the thermistors are not precisely the same, the network is further considered with non-identical neurons. For this purpose, the coefficient of temperature changes in thermistors is not fixed and se-lected randomly from a normal distribution. The results show that for distributions with a small standard deviation, the behavior of the network changes slightly. While with increas-ing the standard deviation, the synchronization is achieved for higher coupling strengths, and the region of chimera is extended. Furthermore, although in the asynchronous network the neurons have different attractors, by the appearance of coherent groups and creation of the chimera, the attractors become identical. (c) 2021 Elsevier Inc. All rights reserved.

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