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White noise-induced spiral waves and multiple spatial coherence resonances in a neuronal network with type I excitability

Author

Listed:
  • Gu, Hua-Guang
  • Jia, Bing
  • Li, Yu-Ye
  • Chen, Guan-Rong

Abstract

White noise-induced pattern formation is studied in a network composed of Morris–Lecar neuronal models with type I excitability and with initial values higher than that of the resting potential. The appearance and disappearance of spiral waves, as well as the transitions between spiral wave patterns with different kinds of complexity characterized by the normalized spatial autocorrelation function, enable changes in the order of the network so as to exhibit a scenario with two or more locally maximal peaks, as can be clearly seen in the signal to noise ratio curves, as the noise intensity is adjusted from small to large in a wide range. A possible physical mechanism of the multiple resonances based on the dynamics of type I excitability and initial values is provided. The potential biological significance of the noise-induced spiral waves is discussed.

Suggested Citation

  • Gu, Hua-Guang & Jia, Bing & Li, Yu-Ye & Chen, Guan-Rong, 2013. "White noise-induced spiral waves and multiple spatial coherence resonances in a neuronal network with type I excitability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1361-1374.
    • Handle: RePEc:eee:phsmap:v:392:y:2013:i:6:p:1361-1374
    DOI: 10.1016/j.physa.2012.11.049
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    Citations

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    Cited by:

    1. 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.
    2. Liu, Yancai & Cai, Rui & Duan, Jinqiao, 2019. "Lévy noise induced escape in the Morris–Lecar model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 531(C), pages 1-1.
    3. Qin, Ying-Mei & Che, Yan-Qiu & Zhao, Jia, 2018. "Effects of degree distributions on signal propagation in noisy feedforward neural networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 763-774.
    4. Li, Fan, 2020. "Effect of field coupling on the wave propagation in the neuronal network," Chaos, Solitons & Fractals, Elsevier, vol. 141(C).
    5. Song, Xinlin & Wang, Chunni & Ma, Jun & Ren, Guodong, 2016. "Collapse of ordered spatial pattern in neuronal network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 95-112.
    6. Ma, Jun & Xu, Ying & Wang, Chunni & Jin, Wuyin, 2016. "Pattern selection and self-organization induced by random boundary initial values in a neuronal network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 586-594.
    7. Yu, Haitao & Wang, Jiang & Liu, Chen & Deng, Bin & Wei, Xile, 2013. "Delay-induced synchronization transitions in small-world neuronal networks with hybrid electrical and chemical synapses," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5473-5480.
    8. 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.
    9. Feng, Peihua & Fan, Qiang & Yuan, Zhixuan & Wu, Ying, 2021. "Transition from regular to labyrinth pattern in a neuronal network with fast inhibitory synapses," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).

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