Chimera-like state in the bistable excitatory-inhibitory cortical neuronal network

被引:4
|
作者
Li, Xuening [1 ]
Xie, Ying [1 ]
Ye, Zhiqiu [1 ]
Huang, Weifang [1 ]
Yang, Lijian [1 ]
Zhan, Xuan [1 ]
Jia, Ya [1 ]
机构
[1] Cent China Normal Univ, Dept Phys, Wuhan 430079, Peoples R China
基金
中国国家自然科学基金;
关键词
Chimera -like state; Excitatory -inhibitory cortical neuronal network; Synaptic noise; Hodgkin -Huxley neuronal model; SMALL-WORLD; SYNCHRONIZATION; DYNAMICS; MODEL;
D O I
10.1016/j.chaos.2024.114549
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
In recent years, the coexistence of different states in the neural system has attracted widespread interest. Researchers have found a coexisting state of spiking and resting in homogeneous networks, which is known as the chimera-like state. The real cortical network is a much more complex and heterogeneous network. Therefore, the excitatory-inhibitory cortical neuronal network is constructed based on Hodgkin-Huxley neuronal model in this paper, and the chimera-like state is further investigated in the heterogeneous network. It is found that the chimera-like state is related to the balance between excitatory and inhibitory synaptic currents. The excitatory coupling current can counteract the initial condition effect and promote synchronized firing of neurons in the network. The inhibitory coupling current desynchronizes the network and thus induces synaptic noise, resulting in an inverse bell-shaped dependence of the change in the number of spiking neurons. We analyzed the underlying mechanisms of synaptic noise in the phase plane diagram and found it has asymmetry for the neuronal state transition. In addition, neurons with low degrees have a higher probability of undergoing state transitions. Finally, we verified that the chimera-like state is robust to network topology and initial conditions. The results provide a new insight into neuronal interactions in heterogeneous networks and might help to reveal the mechanisms of coexistence of different states in the cortical network.
引用
收藏
页数:10
相关论文
共 50 条
  • [1] Signal transmission and energy consumption in excitatory-inhibitory cortical neuronal network
    Li, Xuening
    Yu, Dong
    Li, Tianyu
    Jia, Ya
    [J]. NONLINEAR DYNAMICS, 2024, 112 (04) : 2933 - 2948
  • [2] Irregular behavior in an excitatory-inhibitory neuronal network
    Park, Choongseok
    Terman, David
    [J]. CHAOS, 2010, 20 (02)
  • [3] Chimera-like states in a neuronal network model of the cat brain
    Santos, M. S.
    Szezech, J. D.
    Borges, F. S.
    Iarosz, K. C.
    Caldas, I. L.
    Batista, A. M.
    Viana, R. L.
    Kurths, J.
    [J]. CHAOS SOLITONS & FRACTALS, 2017, 101 : 86 - 91
  • [4] Local origin of excitatory-inhibitory tuning equivalence in a cortical network
    Duszkiewicz, Adrian J.
    Orhan, Pierre
    Carrasco, Sofia Skromne
    Brown, Eleanor H.
    Owczarek, Eliott
    Vite, Gilberto R.
    Wood, Emma R.
    Peyrache, Adrien
    [J]. NATURE NEUROSCIENCE, 2024, 27 (04) : 782 - 792
  • [5] Plasticity of Cortical Excitatory-Inhibitory Balance
    Froemke, Robert C.
    [J]. ANNUAL REVIEW OF NEUROSCIENCE, VOL 38, 2015, 38 : 195 - 219
  • [6] Excitatory-inhibitory balance modulates the formation and dynamics of neuronal assemblies in cortical networks
    Sadeh, Sadra
    Clopath, Claudia
    [J]. SCIENCE ADVANCES, 2021, 7 (45)
  • [7] Frequency separation by an excitatory-inhibitory network
    Borisyuk, Alla
    Best, Janet
    Terman, David
    [J]. JOURNAL OF COMPUTATIONAL NEUROSCIENCE, 2013, 34 (02) : 231 - 243
  • [8] Frequency separation by an excitatory-inhibitory network
    Alla Borisyuk
    Janet Best
    David Terman
    [J]. Journal of Computational Neuroscience, 2013, 34 : 231 - 243
  • [9] Nonlinear delayed feedback control of synchronization in an excitatory-inhibitory coupled neuronal network
    Zhang, Xiaohan
    Liu, Shenquan
    [J]. NONLINEAR DYNAMICS, 2019, 96 (04) : 2509 - 2522
  • [10] Learning excitatory-inhibitory neuronal assemblies in recurrent networks
    Mackwood, Owen
    Naumann, Laura B.
    Sprekeler, Henning
    [J]. ELIFE, 2021, 10