https://doi.org/10.1140/epjb/s10051-023-00549-4
Regular Article - Statistical and Nonlinear Physics
Synchronization and patterns in a memristive network in noisy electric field
1
College of Electrical and Information Engineering, Lanzhou University of Technology, 730050, Lanzhou, China
2
School of Science, Chongqing University of Posts and Telecommunications, 400065, Chongqing, China
3
Department of Physics, Lanzhou University of Technology, 730050, Lanzhou, China
Received:
31
March
2023
Accepted:
30
May
2023
Published online:
16
June
2023
A simple neural circuit coupled by magnetic flux-controlled memristor (MFCM) can be controlled to describe the electromagnetic effect and radiation on biological neurons. In this paper, the effect of external electric field on biophysical neurons is identified by adding a charge-controlled memristor into a nonlinear circuit. This memristive circuit can present a variety of firing patterns by tuning the angular frequency of an external voltage source. As a result, the physical field energy in this neural circuit and its equivalent Hamilton energy for memristive neuron are dependent on the firing modes of neural activities. For clustered neurons, field energy is exchanged and propagated to obtain fast energy balance by regulating the charge flow in the chain network. Indeed, the growth of coupling intensity is controlled by the energy difference between adjacent neurons, and perfect energy balance keeps a saturation value for coupling intensity. The collective behaviors of memristive neurons in the chain network are adjusted by regulating the coupling intensity for the exchange of charges. In addition, noisy disturbance from external electric field is applied to study the synchronization stability and wave propagation in the network, and energy flow is estimated.
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© The Author(s), under exclusive licence to EDP Sciences, SIF and Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
