https://doi.org/10.1140/epjs/s11734-025-01638-4
Regular Article
The dynamics of a memristive neuron model and the elimination of spiral waves in neural networks composed of such models
School of Mathematics and Statistics, Yancheng Teachers University, 224002, Yancheng, China
Received:
7
March
2025
Accepted:
15
April
2025
Published online:
30
April
2025
Some heart diseases are associated with the formation or the rupture of spiral waves in the heart. The numerical research on the elimination of spiral waves can offer valuable insights and serves as a reference for advancements in the field of life and health sciences. This paper proposes the schemes to eliminate spiral waves in the neural network composed of memristive neuron models. The abundant dynamical behaviors of the neuron model are presented by numerical calculations and circuit simulations. In the neural network, the spiral waves are induced under special network conditions, and can be eliminated by adjusting the condition of periodic excitation and memristor. By analyzing the network synchronization factors, the ranges of the amplitude of periodic excitation and the coefficient of memristor required for the elimination of spiral waves are determined. Compared with the coefficient of memristor, smaller changes in the amplitude of periodic excitation are required to eliminate the spiral waves. Due to the influence of parameter changes in both the external excitation and the memristors on all neuron nodes within the neural network, spiral waves can be fundamentally suppressed.
Copyright comment 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.
© The Author(s), under exclusive licence to EDP Sciences, Springer-Verlag GmbH Germany, part of Springer Nature 2025
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.
