中国物理B ›› 2024, Vol. 33 ›› Issue (10): 100501-100501.doi: 10.1088/1674-1056/ad6256

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

Xuan Wang(王暄)1, Santo Banerjee2, Yinghong Cao(曹颖鸿)1, and Jun Mou(牟俊)1,†   

  1. 1 School of Information Science and Engineering, Dalian Polytechnic University, Dalian 116034, China;
    2 Department of Mathematical Sciences, Giuseppe Luigi Lagrange, Politecnico di Torino, Corso Duca degli Abruzzi 24, Torino, Italy
  • 收稿日期:2024-06-19 修回日期:2024-07-08 接受日期:2024-07-12 出版日期:2024-10-15 发布日期:2024-10-15
  • 通讯作者: Jun Mou E-mail:moujun@dlpu.edu.cn
  • 基金资助:
    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).

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

Xuan Wang(王暄)1, Santo Banerjee2, Yinghong Cao(曹颖鸿)1, and Jun Mou(牟俊)1,†   

  1. 1 School of Information Science and Engineering, Dalian Polytechnic University, Dalian 116034, China;
    2 Department of Mathematical Sciences, Giuseppe Luigi Lagrange, Politecnico di Torino, Corso Duca degli Abruzzi 24, Torino, Italy
  • Received:2024-06-19 Revised:2024-07-08 Accepted:2024-07-12 Online:2024-10-15 Published:2024-10-15
  • Contact: Jun Mou E-mail:moujun@dlpu.edu.cn
  • Supported by:
    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).

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摘要： 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.

关键词: memristor, multistability, Hamilton energy, firing pattern, Neuron model, hardware implementation

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.

Key words: memristor, multistability, Hamilton energy, firing pattern, Neuron model, hardware implementation

中图分类号:  (Nonlinear dynamics and chaos)

  • 05.45.-a
05.45.Gg (Control of chaos, applications of chaos)