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Nonlinear responses in a neural network under spatial electromagnetic radiation

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  • Guo, Yitong
  • Xie, Ying
  • Ma, Jun

Abstract

Biological neurons are clustered and functional synapses are created to propagate electric signals accompanying with formation of spatial patterns in the neural network. From physical aspect, fast synaptic connections to neurons provide an effective shortcut for energy exchange and keeping energy balance between neurons. In fact, field coupling behaves effective bridge connections to neurons and then neural activities can be controlled by spatial induction currents in the neural network. In this paper, memristive neurons are controlled by magnetic flux by inducing gradient induction current in presence of electromagnetic radiation without synaptic connections. Differed from the previous uniform radiation, spatial radiation is imposed on the neural network and the stability of spatial patterns is explored by imposing a spatiotemporal disturbance on the network. Memristive neurons developed from Hindmarsh–Rose neurons by involving memristive term and magnetic flux variable are used to build a chain network and a lattice network under field coupling rather than using synaptic coupling. Synchronization factors are calculated to discern the synchronization dependence on noise, amplitude and frequency in the spatial electromagnetic radiation. An isolated neuron can present stochastic resonance under noise and radiation with diversity. Field coupling enhances energy exchange and local energy balance, and then synchronous patterns are controlled in absence of synaptic coupling. External noise and spatial disturbance can induce certain diversity in induction current and excitability, therefore, approach of complete synchronization and development of regular patterns are blocked because of local energy balance under field coupling. These results indicate that energy injection and control of energy flow are effective to prevent the occurrence of bursting synchronization and coexistence of multiple firing modes is formed in neural network composed of memristive neurons under spatial radiation.

Suggested Citation

  • Guo, Yitong & Xie, Ying & Ma, Jun, 2023. "Nonlinear responses in a neural network under spatial electromagnetic radiation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 626(C).
    • Handle: RePEc:eee:phsmap:v:626:y:2023:i:c:s0378437123006751
    DOI: 10.1016/j.physa.2023.129120
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    References listed on IDEAS

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    1. Andreev, Andrey V. & Makarov, Vladimir V. & Runnova, Anastasija E. & Pisarchik, Alexander N. & Hramov, Alexander E., 2018. "Coherence resonance in stimulated neuronal network," Chaos, Solitons & Fractals, Elsevier, vol. 106(C), pages 80-85.
    2. Yao, Zhao & Zhou, Ping & Alsaedi, Ahmed & Ma, Jun, 2020. "Energy flow-guided synchronization between chaotic circuits," Applied Mathematics and Computation, Elsevier, vol. 374(C).
    3. Ma, Jun & Wu, Fuqiang & Hayat, Tasawar & Zhou, Ping & Tang, Jun, 2017. "Electromagnetic induction and radiation-induced abnormality of wave propagation in excitable media," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 508-516.
    4. Moujahid, A. & d’Anjou, A. & Torrealdea, F.J. & Torrealdea, F., 2011. "Efficient synchronization of structurally adaptive coupled Hindmarsh–Rose neurons," Chaos, Solitons & Fractals, Elsevier, vol. 44(11), pages 929-933.
    5. 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.
    6. Palabas, Tugba & Torres, Joaquín J. & Perc, Matjaž & Uzuntarla, Muhammet, 2023. "Double stochastic resonance in neuronal dynamics due to astrocytes," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    7. Xu, Ying & Guo, Yeye & Ren, Guodong & Ma, Jun, 2020. "Dynamics and stochastic resonance in a thermosensitive neuron," Applied Mathematics and Computation, Elsevier, vol. 385(C).
    8. Hansen, Matheus & Protachevicz, Paulo R. & Iarosz, Kelly C. & Caldas, Iberê L. & Batista, Antonio M. & Macau, Elbert E.N., 2022. "The effect of time delay for synchronisation suppression in neuronal networks," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    9. Baysal, Veli & Yilmaz, Ergin, 2020. "Effects of electromagnetic induction on vibrational resonance in single neurons and neuronal networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    10. Xu, Ying & Ren, Guodong & Ma, Jun, 2023. "Patterns stability in cardiac tissue under spatial electromagnetic radiation," Chaos, Solitons & Fractals, Elsevier, vol. 171(C).
    11. Lü, Ling & Ge, Lianjun & Gao, Liyu & Han, Changhui & Li, Chengren, 2019. "Synchronization transmission of spiral wave and turbulence in uncertain time-delay neuronal networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 64-71.
    12. Klinshov, Vladimir V. & Kovalchuk, Andrey V. & Franović, Igor & Perc, Matjaž & Svetec, Milan, 2022. "Rate chaos and memory lifetime in spiking neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    13. Kafraj, Mohadeseh Shafiei & Parastesh, Fatemeh & Jafari, Sajad, 2020. "Firing patterns of an improved Izhikevich neuron model under the effect of electromagnetic induction and noise," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).
    14. Rajagopal, Karthikeyan & Karthikeyan, Anitha, 2022. "Spiral waves and their characterization through spatioperiod and spatioenergy under distinct excitable media," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    15. 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).
    16. Muni, Sishu Shankar & Rajagopal, Karthikeyan & Karthikeyan, Anitha & Arun, Sundaram, 2022. "Discrete hybrid Izhikevich neuron model: Nodal and network behaviours considering electromagnetic flux coupling," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    17. Rajagopal, Karthikeyan & Hussain, Iqtadar & Rostami, Zahra & Li, Chunbiao & Pham, Viet-Thanh & Jafari, Sajad, 2021. "Magnetic induction can control the effect of external electrical stimuli on the spiral wave," Applied Mathematics and Computation, Elsevier, vol. 390(C).
    18. Ma, Xiaowen & Xu, Ying, 2022. "Taming the hybrid synapse under energy balance between neurons," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
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