Reduced and bifurcation analysis of intrinsically bursting neuron model

被引:4
作者
Lu, Bo [1 ,2 ]
Jiang, Xiaofang [2 ]
机构
[1] Henan Normal Univ, Postdoctoral Res Stn Phys, Xinxiang 453007, Peoples R China
[2] Henan Inst Sci & Technol, Sch Math Sci, Xinxiang 453003, Peoples R China
来源
ELECTRONIC RESEARCH ARCHIVE | 2023年 / 31卷 / 10期
关键词
intrinsic bursting; neuronal model; projection reduction method; Bogdanov-Tankens; bifurcation; homoclinic orbit;
D O I
10.3934/era.2023301
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Intrinsic bursting neurons represent a common neuronal type that displays bursting patterns upon depolarization stimulation. These neurons can be described by a system of seven-dimensional equations, which pose a challenge for dynamical analysis. To overcome this limitation, we employed the projection reduction method to reduce the dimensionality of the model. Our approach demonstrated that the reduced model retained the inherent bursting characteristics of the original model. Following reduction, we investigated the bi-parameter bifurcation of the equilibrium point in the reduced model. Specifically, we analyzed the Bogdanov-Takens bifurcation that arises in the reduced system. Notably, the topological structure of the neuronal model near the bifurcation point can be effectively revealed with our proposed method. By leveraging the proposed projection reduction method, we could explore the bursting mechanism in the reduced Pospischil model with greater precision. Our approach offers an effective foundation for generating theories and hypotheses that can be tested experimentally. Fur-thermore, it enables links to be drawn between neuronal morphology and function, thereby facilitating a deeper understanding of the complex dynamical behaviors that underlie intrinsic bursting neurons.
引用
收藏
页码:5928 / 5945
页数:18
相关论文
共 50 条
  • [1] Bifurcation mechanism of mixed bursting in neuron model under the electromagnetic field
    Ji W.
    Duan L.
    Qi H.
    Duan, Lixia (duanlx@ncut.edu), 1733, Chinese Society of Theoretical and Applied Mechanics (53): : 1733 - 1746
  • [2] Bursting types and bifurcation analysis of the temperature-sensitive Purkinje neuron
    Xing, Miaomiao
    Yang, Zhuoqin
    Chen, Yong
    NONLINEAR DYNAMICS, 2023, 111 (02) : 1819 - 1834
  • [3] Bursting types and bifurcation analysis of the temperature-sensitive Purkinje neuron
    Miaomiao Xing
    Zhuoqin Yang
    Yong Chen
    Nonlinear Dynamics, 2023, 111 : 1819 - 1834
  • [4] Hidden Bursting Firings and Bifurcation Mechanisms in Memristive Neuron Model With Threshold Electromagnetic Induction
    Bao, Han
    Hu, Aihuang
    Liu, Wenbo
    Bao, Bocheng
    IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 31 (02) : 502 - 511
  • [5] Bifurcation analysis of a Morris–Lecar neuron model
    Congmin Liu
    Xuanliang Liu
    Shenquan Liu
    Biological Cybernetics, 2014, 108 : 75 - 84
  • [6] Bifurcation analysis of a Morris-Lecar neuron model
    Liu, Congmin
    Liu, Xuanliang
    Liu, Shenquan
    BIOLOGICAL CYBERNETICS, 2014, 108 (01) : 75 - 84
  • [7] BURSTING AND TWO-PARAMETER BIFURCATION IN THE CHAY NEURONAL MODEL
    Duan, Lixia
    Yang, Zhuoqin
    Liu, Shenquan
    Gong, Dunwei
    DISCRETE AND CONTINUOUS DYNAMICAL SYSTEMS-SERIES B, 2011, 16 (02): : 445 - 456
  • [8] Bifurcation, bursting and spike generation in a neural model
    Govaerts, W
    Dhooge, A
    INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS, 2002, 12 (08): : 1731 - 1741
  • [9] Bifurcation analysis on the reduced dopamine neuronal model
    Jiang, Xiaofang
    Zhou, Hui
    Wang, Feifei
    Zheng, Bingxin
    Lu, Bo
    ELECTRONIC RESEARCH ARCHIVE, 2024, 32 (07): : 4237 - 4254
  • [10] Bifurcation analysis of inhibitory responses of A PWC spiking neuron model
    Yamashita, Yutaro
    Torikai, Hiroyuki
    IEICE NONLINEAR THEORY AND ITS APPLICATIONS, 2012, 3 (04): : 557 - 572