Memristors-coupled neuron models with multiple firing patterns and homogeneous and heterogeneous multistability

doi:10.1088/1674-1056/ad6256

Abstract Memristors are extensively used to estimate the external electromagnetic stimulation and synapses for neurons. In this paper, two distinct scenarios, i.e., an ideal memristor serves as external electromagnetic stimulation and a locally active memristor serves as a synapse, are formulated to investigate the impact of a memristor on a two-dimensional Hindmarsh-Rose neuron model. Numerical simulations show that the neuronal models in different scenarios have multiple burst firing patterns. The introduction of the memristor makes the neuronal model exhibit complex dynamical behaviors. Finally, the simulation circuit and DSP hardware implementation results validate the physical mechanism, as well as the reliability of the biological neuron model.

Keywords: memristor multistability Hamilton energy firing pattern Neuron model hardware implementation

Received: 19 June 2024
Revised: 08 July 2024
Accepted manuscript online: 12 July 2024

PACS:	05.45.-a	(Nonlinear dynamics and chaos)
	05.45.Gg	(Control of chaos, applications of chaos)

Fund: Project supported by the National Natural Science Foundation of China (Grant No. 62061014), Technological Innovation Projects in the Field of Artificial Intelligence in Liaoning province (Grant No. 2023JH26/10300011), and Basic Scientific Research Projects in Department of Education of Liaoning Province (Grant No. JYTZD2023021).

Corresponding Authors: Jun Mou
E-mail: moujun@dlpu.edu.cn

Cite this article:

Xuan Wang(王暄), Santo Banerjee, Yinghong Cao(曹颖鸿), and Jun Mou(牟俊) Memristors-coupled neuron models with multiple firing patterns and homogeneous and heterogeneous multistability 2024 Chin. Phys. B 33 100501

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Memristors-coupled neuron models with multiple firing patterns and homogeneous and heterogeneous multistability

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