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Dynamics and stochastic resonance in a thermosensitive neuron

Author

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  • Xu, Ying
  • Guo, Yeye
  • Ren, Guodong
  • Ma, Jun

Abstract

Temperature has distinct impact on the activation of neural activities by adjusting the excitability and channel conductance. Some biological neurons can percept slight changes of temperature and then appropriate firing modes are induced under different temperatures. Indeed, the temperature-dependent property can be described by using thermistors, which can be included to build functional neural circuits. Therefore, any changes in the resistance of the thermistor can regulate the branch current and also the output voltage completely. In the paper, thermistors are connected to the FitzHugh-Nagumo neural circuit driven by a voltage source, and a thermosensitive neuron oscillator is obtained by applying scale transformation for the physical variables and parameters in the neural circuit. The thermistor is connected to different branch circuits to enhance the sensitivity to changes of temperature. It is confirmed that the neural activities can present distinct mode transition from spiking to bursting and chaotic states. In particular, the external stimulus becomes dependent on temperature when the thermistor is connected to the external voltage source. Stochastic resonance and multiple modes are detected when additive Gaussian white noise is applied on an isolated neuron controlled by temperature. Therefore, a sensitive sensor of temperature is obtained, and this feasible neuron model can be effective to investigate the collective behaviors of neural networks in the presence of time-varying temperature. Also, the Hamilton energy is estimated to predict the mode selection and effect of noise.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:apmaco:v:385:y:2020:i:c:s009630032030388x
    DOI: 10.1016/j.amc.2020.125427
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    References listed on IDEAS

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    1. Chunni Wang & Shengli Guo & Ying Xu & Jun Ma & Jun Tang & Faris Alzahrani & Aatef Hobiny, 2017. "Formation of Autapse Connected to Neuron and Its Biological Function," Complexity, Hindawi, vol. 2017, pages 1-9, February.
    2. Qin, Huixin & Wang, Chunni & Cai, Ning & An, Xinlei & Alzahrani, Faris, 2018. "Field coupling-induced pattern formation in two-layer neuronal network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 141-152.
    3. Pablo Achard & Erik De Schutter, 2006. "Complex Parameter Landscape for a Complex Neuron Model," PLOS Computational Biology, Public Library of Science, vol. 2(7), pages 1-11, July.
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