https://doi.org/10.1140/epjs/s11734-025-01650-8
Regular Article
Dynamical robustness and firing modes in multilayer neuronal networks with threshold memristive synapses
1
School of Science, Xi’an University of Posts & Telecommunications, 710121, Xi’an, China
2
School of Mathematics and Statistics, Northwestern Polytechnical University, 710129, Xi’an, China
3
School of Science, Chang’an University, 710064, Xi’an, China
Received:
2
February
2025
Accepted:
24
April
2025
Published online:
7
May
2025
The combined effects of electromagnetic induction and multilayer structure on dynamical robustness and firing modes in the neuronal networks are investigated in this paper. Numerical results show that electrical coupling within layers makes mesoscopic oscillation of intermediate is stronger than that of top layer, bottom layer, even macroscopic oscillation of the whole network. Dynamical robustness of intermediate layer and the whole network is stronger than that of top and bottom layer with increasing electrical coupling strength or threshold memristive coupling strength. Interestingly, the oscillation of each layer and the entire network shows irregular variation with increasing ratio of inactive neurons in the case of strong threshold memristive coupling between layers. The firing modes of neurons can be switched by electrical coupling strength, threshold memristive coupling strength and the ratio of inactive neurons. Analog circuit implementation of multilayer neuronal networks with inter-layer threshold memristive synapses is built on Multisim. The obtained results may give new mechanism explanation for neural information process.
Supplementary Information The online version contains supplementary material available at https://doi.org/10.1140/epjs/s11734-025-01650-8.
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© 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.
