Dynamical robustness and firing modes in multilayer neuronal networks with threshold memristive synapses

Yuanyuan Liu, Zhongkui Sun, Nannan Zhao, Hanqi Zhang

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Article number129268
JournalEuropean Physical Journal: Special Topics
DOIs
StateAccepted/In press - 2025

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