Dynamics in stimulation-based tabu learning neuron model

被引:9
|
作者
Li, Hongmin [1 ,2 ]
Lu, Yingchun [1 ,2 ]
Li, Chunlai [1 ,2 ]
机构
[1] Hfvunan Inst Sci & Technol, Key Lab Hunan Prov Informat Photon & Freespace Op, Yueyang 414006, Peoples R China
[2] Hunan Inst Sci & Technol, Coll Phys & Elect, Yueyang 414006, Peoples R China
关键词
Tabu learning neuron; Nonlinear behavior; Circuit implementation; INFORMATION-TRANSMISSION; HOPF-BIFURCATION; CHAOS; NETWORK; BRAIN; DRIVEN; EEG;
D O I
10.1016/j.aeue.2021.153983
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Biological nervous system is very sensitive to external disturbance, and neuron will consume energy when responding to the disturbance. However, proper stimulation can help the organism to maintain neural function. In this paper, we explore the dynamics of tabu learning neuron models stimulated by different disturbances. Mathematical models of the tabu neuron are respectively built under external forced current stimulus, electromagnetic radiation stimulus, and both electromagnetic radiation and external forced current stimuli. The dynamical behaviors of these neuron models are studied by the analyses of equilibrium point, bifurcation diagram, Lyapunov exponential spectrum, phase trajectory and attraction basin. The Hamilton energy of these models are investigated based on the Helmholtz's theorem. It shows that the behavior of absorbing energy or dissipating energy in the firing process depends on the stimulation form on fvfvthe neuron model. Finally, a unified analog electronic neuron circuit is designed to observe different firing patterns by controlling the switches.
引用
收藏
页数:14
相关论文
共 50 条
  • [41] Visual Analytics of Learning Behavior Based on the Dendritic Neuron Model
    Tang, Cheng
    Chen, Li
    Li, Gen
    Minematsu, Tsubasa
    Okubo, Fumiya
    Taniguchi, Yuta
    Shimada, Atsushi
    KNOWLEDGE SCIENCE, ENGINEERING AND MANAGEMENT, PT II, KSEM 2024, 2024, 14885 : 192 - 203
  • [42] Extracellular Electrical Stimulation-based in Vitro Neuroscience A Minireview of Methods and a Paradigm Shift Proposal
    Tanskanen, Jarno M. A.
    Ahtiainen, Annika
    Hyttinen, Jari A. K.
    2019 26TH IEEE INTERNATIONAL CONFERENCE ON ELECTRONICS, CIRCUITS AND SYSTEMS (ICECS), 2019, : 883 - 886
  • [43] Optimal stimulation of spiking neuron using reinforcement learning: Single neuron study
    Singanamalla, Sai Kalyan Ranga
    Akella, Ashlesha
    Lin, Chin-Teng
    JOURNAL OF COMPUTATIONAL NEUROSCIENCE, 2021, 49 (SUPPL 1) : S111 - S112
  • [44] CNN templates learning based on tabu search
    Yang, Zhongxue
    Karahoca, Adem
    Qin, Xiaolin
    Journal of Information and Computational Science, 2009, 6 (01): : 259 - 264
  • [45] A tabu based neural network learning algorithm
    Ye, Jian
    Qiao, Junfei
    Li, Ming-ai
    Ruan, Xiaogang
    NEUROCOMPUTING, 2007, 70 (4-6) : 875 - 882
  • [46] Complex dynamics in a discrete adaptive synapse-based neuron model
    Zhuowu Wang
    Han Bao
    Huagan Wu
    Mo Chen
    Bocheng Bao
    The European Physical Journal Plus, 138
  • [47] Complex dynamics in a discrete adaptive synapse-based neuron model
    Wang, Zhuowu
    Bao, Han
    Wu, Huagan
    Chen, Mo
    Bao, Bocheng
    EUROPEAN PHYSICAL JOURNAL PLUS, 2023, 138 (06):
  • [48] Stimulation Strategies for Tinnitus Suppression in a Neuron Model
    Paffi, Alessandra
    Camera, Francesca
    Carocci, Chiara
    Apollonio, Francesca
    Liberti, Micaela
    COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE, 2018, 2018
  • [49] Electrical Muscle Stimulation-Based Approach for Enhancing Hand-eye Coordination Training
    Zhou, Shuo
    Segawa, Norihisa
    EXTENDED ABSTRACTS OF THE 2024 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, CHI 2024, 2024,
  • [50] Symbolic dynamics of a chaotic neuron model
    K. Fukuda
    K. Aihara
    K. Aihara
    Artificial Life and Robotics, 2003, 7 (3) : 136 - 144