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Estimation of the effect of magnetic field on a memristive neuron

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  • Wu, Fuqiang
  • Hu, Xikui
  • Ma, Jun

Abstract

A cell's action potential can be induced by rapid pumping and changes in intracellular and extracellular ions, and a magnetic field is generated to regulate neural activity effectively. Stochastic propagation and diffusion of ions across the cell membrane can break the balance of ion concentration. An appropriate external stimulus can speed up the exchange of ions and then different firing modes in the neuron can be induced for energy release. An improved neuron model is proposed and suggested to explore the effect of the magnetic field from the physical aspect, which a memristive channel with locally active feature is added to the known Hodgkin-Huxley (HH) neuron model by connecting a memristor in parallel with the HH neural circuit. That is, the memristive channel current is equivalent to the induction current, and an additive magnetic flux variable is introduced into the HH model, and its evolution is guided by the law of electromagnetic induction and energy conversion. The induction current can modulate the excitability and the threshold for inducing distinct action potentials. The transition from different-type firing patterns is induced by modulating the inductive current. In addition, an external magnetic field from two sources is applied to estimate the mode transition and firing patterns by regulating the magnetic flux, which induces further changes in the neural activity of the neuron. The neuron keeps quiescent when two identical magnetic field sources are emitted at high frequency. While the neuron can be activated to generate continuous firing patterns when the two applied magnetic field sources show certain diversity in the frequency. The potential mechanism is that the frequency synthesized by the two stimuli is close to the intrinsic frequency of the neuron, and then bursting can be induced effectively.

Suggested Citation

  • Wu, Fuqiang & Hu, Xikui & Ma, Jun, 2022. "Estimation of the effect of magnetic field on a memristive neuron," Applied Mathematics and Computation, Elsevier, vol. 432(C).
    • Handle: RePEc:eee:apmaco:v:432:y:2022:i:c:s0096300322004404
    DOI: 10.1016/j.amc.2022.127366
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    References listed on IDEAS

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    1. Wu, Fuqiang & Ma, Jun & Zhang, Ge, 2019. "A new neuron model under electromagnetic field," Applied Mathematics and Computation, Elsevier, vol. 347(C), pages 590-599.
    2. Wu, Fuqiang & Wang, Chunni & Jin, Wuyin & Ma, Jun, 2017. "Dynamical responses in a new neuron model subjected to electromagnetic induction and phase noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 81-88.
    3. Dmitri B. Strukov & Gregory S. Snider & Duncan R. Stewart & R. Stanley Williams, 2008. "The missing memristor found," Nature, Nature, vol. 453(7191), pages 80-83, May.
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    Citations

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    Cited by:

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    2. Njitacke, Zeric Tabekoueng & Ramadoss, Janarthanan & Takembo, Clovis Ntahkie & Rajagopal, Karthikeyan & Awrejcewicz, Jan, 2023. "An enhanced FitzHugh–Nagumo neuron circuit, microcontroller-based hardware implementation: Light illumination and magnetic field effects on information patterns," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    3. Yu, Xihong & Bao, Han & Chen, Mo & Bao, Bocheng, 2023. "Energy balance via memristor synapse in Morris-Lecar two-neuron network with FPGA implementation," Chaos, Solitons & Fractals, Elsevier, vol. 171(C).
    4. Xu, Ying & Ren, Guodong & Ma, Jun, 2023. "Patterns stability in cardiac tissue under spatial electromagnetic radiation," Chaos, Solitons & Fractals, Elsevier, vol. 171(C).
    5. Sun, Guoping & Yang, Feifei & Ren, Guodong & Wang, Chunni, 2023. "Energy encoding in a biophysical neuron and adaptive energy balance under field coupling," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    6. Feifei Yang & Xikui Hu & Guodong Ren & Jun Ma, 2023. "Synchronization and patterns in a memristive network in noisy electric field," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 96(6), pages 1-14, June.

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