中国物理B ›› 2024, Vol. 33 ›› Issue (4): 48701-048701.doi: 10.1088/1674-1056/ad1483

• • 上一篇    

Dynamical behaviors in discrete memristor-coupled small-world neuronal networks

Jieyu Lu(鲁婕妤)1, Xiaohua Xie(谢小华)1, Yaping Lu(卢亚平)1, Yalian Wu(吴亚联)1, Chunlai Li(李春来)2, and Minglin Ma(马铭磷)1,†   

  1. 1 School of Automation and Electronic Information, Xiangtan University, Xiangtan 411105, China;
    2 School of Computer Science School of Cyberspace Science, Xiangtan University, Xiangtan 411105, China
  • 收稿日期:2023-10-21 修回日期:2023-11-29 接受日期:2023-12-12 出版日期:2024-03-19 发布日期:2024-04-01
  • 通讯作者: Minglin Ma E-mail:minglin_ma@xtu.edu.cn
  • 基金资助:
    Project supported by the Key Projects of Hunan Provincial Department of Education (Grant No. 23A0133), the Natural Science Foundation of Hunan Province (Grant No. 2022JJ30572), and the National Natural Science Foundations of China (Grant No. 62171401).

Dynamical behaviors in discrete memristor-coupled small-world neuronal networks

Jieyu Lu(鲁婕妤)1, Xiaohua Xie(谢小华)1, Yaping Lu(卢亚平)1, Yalian Wu(吴亚联)1, Chunlai Li(李春来)2, and Minglin Ma(马铭磷)1,†   

  1. 1 School of Automation and Electronic Information, Xiangtan University, Xiangtan 411105, China;
    2 School of Computer Science School of Cyberspace Science, Xiangtan University, Xiangtan 411105, China
  • Received:2023-10-21 Revised:2023-11-29 Accepted:2023-12-12 Online:2024-03-19 Published:2024-04-01
  • Contact: Minglin Ma E-mail:minglin_ma@xtu.edu.cn
  • Supported by:
    Project supported by the Key Projects of Hunan Provincial Department of Education (Grant No. 23A0133), the Natural Science Foundation of Hunan Province (Grant No. 2022JJ30572), and the National Natural Science Foundations of China (Grant No. 62171401).

RichHTML

0

PDF (PC)

70

赞

摘要： The brain is a complex network system in which a large number of neurons are widely connected to each other and transmit signals to each other. The memory characteristic of memristors makes them suitable for simulating neuronal synapses with plasticity. In this paper, a memristor is used to simulate a synapse, a discrete small-world neuronal network is constructed based on Rulkov neurons and its dynamical behavior is explored. We explore the influence of system parameters on the dynamical behaviors of the discrete small-world network, and the system shows a variety of firing patterns such as spiking firing and triangular burst firing when the neuronal parameter α is changed. The results of a numerical simulation based on Matlab show that the network topology can affect the synchronous firing behavior of the neuronal network, and the higher the reconnection probability and number of the nearest neurons, the more significant the synchronization state of the neurons. In addition, by increasing the coupling strength of memristor synapses, synchronization performance is promoted. The results of this paper can boost research into complex neuronal networks coupled with memristor synapses and further promote the development of neuroscience.

关键词: small-world networks, Rulkov neurons, memristor, synchronization

Abstract: The brain is a complex network system in which a large number of neurons are widely connected to each other and transmit signals to each other. The memory characteristic of memristors makes them suitable for simulating neuronal synapses with plasticity. In this paper, a memristor is used to simulate a synapse, a discrete small-world neuronal network is constructed based on Rulkov neurons and its dynamical behavior is explored. We explore the influence of system parameters on the dynamical behaviors of the discrete small-world network, and the system shows a variety of firing patterns such as spiking firing and triangular burst firing when the neuronal parameter α is changed. The results of a numerical simulation based on Matlab show that the network topology can affect the synchronous firing behavior of the neuronal network, and the higher the reconnection probability and number of the nearest neurons, the more significant the synchronization state of the neurons. In addition, by increasing the coupling strength of memristor synapses, synchronization performance is promoted. The results of this paper can boost research into complex neuronal networks coupled with memristor synapses and further promote the development of neuroscience.

Key words: small-world networks, Rulkov neurons, memristor, synchronization

中图分类号:  (Models of single neurons and networks)

  • 87.19.ll
87.19.lj (Neuronal network dynamics) 05.45.Xt (Synchronization; coupled oscillators)