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Detection of sub-threshold periodic signal by multiplicative and additive cross-correlated sine-Wiener noises in the FitzHugh–Nagumo neuron

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  • Yao, Yuangen
  • Ma, Chengzhang
  • Wang, Canjun
  • Yi, Ming
  • Gui, Rong

Abstract

We study the effects of multiplicative and additive cross-correlated sine-Wiener (CCSW) noises on the performance of sub-threshold periodic signal detection in the FitzHugh–Nagumo (FHN) neuron by calculating Fourier coefficients Q for measuring synchronization between sub-threshold input signal and the response of system. CCSW noises-induced transitions of electrical activity in the FHN neuron model can be observed. Moreover, the performance of sub-threshold periodic signal detection is achieved at moderate noise strength, cross-correlation time and cross-correlation strength of CCSW noises, which indicate the occurrence of CCSW noises-induced stochastic resonance. Furthermore, the performance of sub-threshold signal detection is strongly sensitive to cross-correlation time of CCSW noises. Therefore, the performance can be effectively controlled by regulating cross-correlation time of CCSW noises. These results provide a possible mechanism for amplifying or detecting the sub-threshold signal in the nervous system.

Suggested Citation

  • Yao, Yuangen & Ma, Chengzhang & Wang, Canjun & Yi, Ming & Gui, Rong, 2018. "Detection of sub-threshold periodic signal by multiplicative and additive cross-correlated sine-Wiener noises in the FitzHugh–Nagumo neuron," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 1247-1256.
    • Handle: RePEc:eee:phsmap:v:492:y:2018:i:c:p:1247-1256
    DOI: 10.1016/j.physa.2017.11.052
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    Citations

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    Cited by:

    1. 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).
    2. 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.
    3. Cesar Manchein & Paulo C. Rech, 2024. "Effects of external stimuli on the dynamics of deterministic and stochastic Hindmarsh–Rose neuron models," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 97(8), pages 1-16, August.
    4. Yuangen Yao & Wei Cao & Qiming Pei & Chengzhang Ma & Ming Yi, 2018. "Breakup of Spiral Wave and Order-Disorder Spatial Pattern Transition Induced by Spatially Uniform Cross-Correlated Sine-Wiener Noises in a Regular Network of Hodgkin-Huxley Neurons," Complexity, Hindawi, vol. 2018, pages 1-10, April.
    5. Zhang, Gang & Shu, Yichen & Zhang, Tianqi, 2022. "The study on dynamical behavior of FitzHugh–Nagumo neural model under the co-excitation of non-Gaussian and colored noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 587(C).
    6. Yao, Yuangen & Ma, Jun & Gui, Rong & Cheng, Guanghui, 2021. "Chaos-induced Set–Reset latch operation," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    7. Guo, Yongfeng & Wang, Linjie & Wei, Fang & Tan, Jianguo, 2019. "Dynamical behavior of simplified FitzHugh-Nagumo neural system driven by Lévy noise and Gaussian white noise," Chaos, Solitons & Fractals, Elsevier, vol. 127(C), pages 118-126.
    8. Cheng, Guanghui & Liu, Weidan & Gui, Rong & Yao, Yuangen, 2020. "Sine-Wiener bounded noise-induced logical stochastic resonance in a two-well potential system," Chaos, Solitons & Fractals, Elsevier, vol. 131(C).

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