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Ramazanov I. R., Korneev I. A., Slepnev A. V., Vadivasova T. E. Synchronization of excitation waves in a two-layer network of FitzHugh–Nagumo neurons with noise modulation of interlayer coupling parameters. Izvestiya VUZ. Applied Nonlinear Dynamics, 2022, vol. 30, iss. 6, pp. 732-748. DOI: 10.18500/0869-6632-003016

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537.86; 519.21

Synchronization of excitation waves in a two-layer network of FitzHugh–Nagumo neurons with noise modulation of interlayer coupling parameters

Ramazanov Ibadulla Ramzesovich, Saratov State University
Korneev Ivan Aleksandrovich, Saratov State University
Slepnev Andrej Vjacheslavovich, Saratov State University
Vadivasova Tatjana Evgenevna, Saratov State University

The purpose of this work is to study the possibility of synchronization of wave processes in distributed excitable systems by means of noise modulation of the coupling strength between them. Methods. A simple model of a neural network, which consists of two coupled layers of excitable FitzHugh–Nagumo oscillators with a ring topology, is studied by numerical simulation methods. The connection between the layers has a random component, which is set for each pair of coupled oscillators by independent sources of colored Gaussian noise. Results. The possibility to obtain a regime close to full (in-phase) synchronization of traveling waves in the case of identical interacting layers and a regime of synchronization of wave propagation velocities in the case of non-identical layers differing in the values of the coefficients of intra-layer coupling is shown for certain values of parameters of coupling noise (intensity and correlation time). Conclusion. It is shown that the effects of synchronization of phases and propagation velocities of excitation waves in ensembles of neurons can be controlled using random processes of interaction of excitable oscillators set by statistically independent noise sources. In this case, both the noise intensity and its correlation time can serve as control parameters. The results obtained on a simple model can be quite general.

This work was supported by Russian Science Foundation, grant No. 20-12-00119
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