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Dynamic Behaviors in Coupled Neuron System with the Excitatory and Inhibitory Autapse under Electromagnetic Induction

Author

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  • Ying Xu
  • Ya Jia
  • John Billy Kirunda
  • Jian Shen
  • Mengyan Ge
  • Lulu Lu
  • Qiming Pei

Abstract

The induced current produced by electromagnetic induction can adjust the membrane potential of neuron through the feedback of a magnetic flux-controlled memristor. We adopt the numerical simulation method with the aim of investigating the synchronous behavior in the neuronal system that is coupled by chemical and electrical synapses under electromagnetic induction. Within the improved model, the effects of electromagnetic induction on neurons are described with additive memristive current on the membrane variable, and the memristive current is dependent on the variation of magnetic flow. The simulation results show that the two coupling modes play an important role in the synchronization of the system. By increasing the chemical synaptic feedback gain, we observe a transition from mixed oscillatory to periodic state at a critical value. In addition, two Hopf bifurcation points are found with the change of the external stimuli, and the state of neuron discharge is influenced by initial values. Furthermore, there is a domain of coupling strength and feedback gain values, in which the two coupled neuron system is synchronized and longer time lag is not conducive to the system synchronization.

Suggested Citation

  • Ying Xu & Ya Jia & John Billy Kirunda & Jian Shen & Mengyan Ge & Lulu Lu & Qiming Pei, 2018. "Dynamic Behaviors in Coupled Neuron System with the Excitatory and Inhibitory Autapse under Electromagnetic Induction," Complexity, Hindawi, vol. 2018, pages 1-13, July.
    • Handle: RePEc:hin:complx:3012743
    DOI: 10.1155/2018/3012743
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    Cited by:

    1. Ge, Mengyan & Jia, Ya & Xu, Ying & Lu, Lulu & Wang, Huiwen & Zhao, Yunjie, 2019. "Wave propagation and synchronization induced by chemical autapse in chain Hindmarsh–Rose neural network," Applied Mathematics and Computation, Elsevier, vol. 352(C), pages 136-145.
    2. Yu, Dong & Lu, Lulu & Wang, Guowei & Yang, Lijian & Jia, Ya, 2021. "Synchronization mode transition induced by bounded noise in multiple time-delays coupled FitzHugh–Nagumo model," Chaos, Solitons & Fractals, Elsevier, vol. 147(C).
    3. Yu, Dong & Wang, Guowei & Ding, Qianming & Li, Tianyu & Jia, Ya, 2022. "Effects of bounded noise and time delay on signal transmission in excitable neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    4. Cheng, Guanghui & Gui, Rong & Yao, Yuangen & Yi, Ming, 2019. "Enhancement of temporal regularity and degradation of spatial synchronization induced by cross-correlated sine-Wiener noises in regular and small-world neuronal networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 361-369.
    5. Hou, Zhangliang & Ma, Jun & Zhan, Xuan & Yang, Lijian & Jia, Ya, 2021. "Estimate the electrical activity in a neuron under depolarization field," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    6. Lu, Lulu & Ge, Mengyan & Xu, Ying & Jia, Ya, 2019. "Phase synchronization and mode transition induced by multiple time delays and noises in coupled FitzHugh–Nagumo model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    7. Aghababaei, Sajedeh & Balaraman, Sundarambal & Rajagopal, Karthikeyan & Parastesh, Fatemeh & Panahi, Shirin & Jafari, Sajad, 2021. "Effects of autapse on the chimera state in a Hindmarsh-Rose neuronal network," Chaos, Solitons & Fractals, Elsevier, vol. 153(P2).
    8. Ge, Mengyan & Lu, Lulu & Xu, Ying & Mamatimin, Rozihajim & Pei, Qiming & Jia, Ya, 2020. "Vibrational mono-/bi-resonance and wave propagation in FitzHugh–Nagumo neural systems under electromagnetic induction," Chaos, Solitons & Fractals, Elsevier, vol. 133(C).
    9. Ni Zhang & Dongxi Li & Yanya Xing, 2021. "Autapse-induced multiple inverse stochastic resonance in a neural system," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 94(1), pages 1-11, January.
    10. Wang, Guowei & Yu, Dong & Ding, Qianming & Li, Tianyu & Jia, Ya, 2021. "Effects of electric field on multiple vibrational resonances in Hindmarsh-Rose neuronal systems," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    11. Qu, Lianghui & Du, Lin & Cao, Zilu & Hu, Haiwei & Deng, Zichen, 2021. "Pattern transition of neuronal networks induced by chemical autapses with random distribution," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    12. Moghadam, Nastaran Navid & Ramamoorthy, Ramesh & Nazarimehr, Fahimeh & Rajagopal, Karthikeyan & Jafari, Sajad, 2022. "Tipping points of a complex network biomass model: Local and global parameter variations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).

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