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Controlling the spiking activity in excitable membranes via poisoning

Author

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  • Schmid, Gerhard
  • Goychuk, Igor
  • Hänggi, Peter

Abstract

The influence of intrinsic channel noise on the spontaneous spiking activity of poisoned excitable membrane patches is studied by use of a stochastic generalization of the Hodgkin–Huxley model. Internal noise stemming from the stochastic dynamics of individual ion channels is known to affect the collective properties of the whole ion channel cluster. There exists an optimal size of the membrane patch for which, solely, the internal noise causes a most regular spontaneous generation of action potentials. In addition to the variation of the size of ion channel clusters, living organisms may adopt the densities of ion channels in order to optimally regulate the spontaneous spiking activity. In our model, we selectively control via poisoning the densities of specific, active ion channels. Interestingly enough, by such poisoning of some of the potassium, or the sodium ion channels, respectively, it is possible to either increase, or decrease the regularity of the spike train.

Suggested Citation

  • Schmid, Gerhard & Goychuk, Igor & Hänggi, Peter, 2004. "Controlling the spiking activity in excitable membranes via poisoning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(3), pages 665-670.
    • Handle: RePEc:eee:phsmap:v:344:y:2004:i:3:p:665-670
    DOI: 10.1016/j.physa.2004.06.049
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    Citations

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    Cited by:

    1. Wang, Qingyun & Zheng, Yanhong & Ma, Jun, 2013. "Cooperative dynamics in neuronal networks," Chaos, Solitons & Fractals, Elsevier, vol. 56(C), pages 19-27.
    2. Li, Jiajia & Wang, Rong & Du, Mengmeng & Tang, Jun & Wu, Ying, 2016. "Dynamic transition on the seizure-like neuronal activity by astrocytic calcium channel block," Chaos, Solitons & Fractals, Elsevier, vol. 91(C), pages 702-708.
    3. Uzun, Rukiye & Yilmaz, Ergin & Ozer, Mahmut, 2017. "Effects of autapse and ion channel block on the collective firing activity of Newman–Watts small-world neuronal networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 386-396.
    4. Liu, Zhilong & Zhou, Ping & Ma, Jun & Hobiny, Aatef & Alzahrani, Faris, 2020. "Autonomic learning via saturation gain method, and synchronization between neurons," Chaos, Solitons & Fractals, Elsevier, vol. 131(C).
    5. Xie, Huijuan & Gong, Yubing, 2017. "Multiple coherence resonances and synchronization transitions by time delay in adaptive scale-free neuronal networks with spike-timing-dependent plasticity," Chaos, Solitons & Fractals, Elsevier, vol. 94(C), pages 80-85.
    6. 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.
    7. Xiao, Fangli & Fu, Ziying & Jia, Ya & Yang, Lijian, 2023. "Resonance effects in neuronal-astrocyte model with ion channel blockage," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    8. Xie, Huijuan & Gong, Yubing & Wang, Baoying, 2018. "Spike-timing-dependent plasticity optimized coherence resonance and synchronization transitions by autaptic delay in adaptive scale-free neuronal networks," Chaos, Solitons & Fractals, Elsevier, vol. 108(C), pages 1-7.
    9. Uzun, Rukiye, 2017. "Influences of autapse and channel blockage on multiple coherence resonance in a single neuron," Applied Mathematics and Computation, Elsevier, vol. 315(C), pages 203-210.

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