Investigation of dynamical behaviors of neurons driven by memristive synapse. (March 2018)

• Record Type: Journal Article
• Authors: Zhang, Ge; Wang, Chunni; Alzahrani, Faris; Wu, Fuqiang; An, Xinlei
• Is Part Of: Chaos, solitons and fractals. Volume 108(2018)
• Page Start: 15
• Page End: 24
• Publication Date: 2018-03
• Subjects: Synapse -- Electrical activity -- Memristor -- Bifurcation; Chaotic behavior in systems -- Periodicals; Solitons -- Periodicals; Fractals -- Periodicals; Chaotic behavior in systems; Fractals; Solitons; Periodicals; 003.7
• DOI: 10.1016/j.chaos.2018.01.017
• Languages: English
• ISSNs: 0960-0779

Abstract

Highlights: Application of memristor on neurodynamics is confirmed. Memristive synapse is formed to enhance self-adaption of neuron. Biological function of self-adaptive synapse with memory is discussed. Electromagnetic induction and autapse connection are supplied to suppress imperfect of presented models. Abstract: Synapse is an important bridge for receiving and encoding signals, and the description for synapse current is critical for further signal processing. This paper investigates the dynamical characteristic in isolated neuron and chain neuronal networks with memristive autapse or synapses, respectively. Autapse plays important role in modulating the electrical activities, and thus the information encoding is enhanced. Within the improved neuron model, memristor is used to map the modulation of synapse current. Within an isolated new neuron model with memory, the modes in electrical activities can be controlled by the synapse current completely. Bifurcation analysis is carried out and mode transition is discussed. Furthermore, the modulation of synapse current on chain network is investigated, and the dependence of wave propagation on intensity of synapse is discussed. The diversity in synapse current can suppress the synchronization approach on the network.