Four-dimensional Hindmarsh–Rose neuron model with hidden firing multistability based on two memristors. (1st December 2022)

• Record Type: Journal Article
• Authors: Yan, Shaohui; Zhang, Yuyan; Ren, Yu; Sun, Xi; Wang, Ertong; Song, Zhenlong
• Is Part Of: Physica scripta. Volume 97:Number 12(2022)
• Publication Date: 2022-12-01
• Subjects: memristive neuron model -- firing -- multistability -- anti-monotonicity -- offset boosting; Physics -- Periodicals; 530.05
• DOI: 10.1088/1402-4896/ac99ad
• Languages: English
• ISSNs: 0031-8949

Abstract

Abstract: Since memristors can be used to describe electromagnetic induction effects, this paper proposes a novel 4D HindMarsh-Rose (HR) neuron model based on two flux-controlled memristors to show complex dynamics of neuronal electrical activity. It has no equilibrium point, revealing hidden dynamical behaviors. The complex dynamics of the system are illustrated by phase portraits, the time sequences, bifurcation diagrams, and Lyapunov exponents spectra. The presented 4D HR neuron model can produce coexisting multiple hidden firing patterns, for instance, periodic spiking, chaotic spiking, transient chaotic spiking, periodic bursting, chaotic bursting, transient chaotic bursting, stochastic bursting, and transient stochastic bursting. Besides, rich nonlinear dynamics, such as anti-monotonicity and initial offset boosting, are also found. Finally, Multisim circuit simulation is performed and the results are in accordance with numerical simulation.