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Channel block-optimized spiking activity of Hodgkin–Huxley neurons on random networks

Author

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  • Gong, Yubing
  • Hao, Yinghang
  • Xie, Yanhang

Abstract

In this paper, we numerically study the effect of channel block on the spiking temporal coherence and spatial synchronization on Hodgkin–Huxley (HH) neuron networks. It is found that under sodium CB the spike coherence is badly reduced, and the synchronization can, depending on the network randomness (the fraction of random shortcuts), be either enhanced or reduced, while, under potassium CB, the spike coherence can be enhanced but the synchronization is reduced. Interestingly, for certain networks of relatively large randomness, the neuron firings can achieve the best temporal coherence at an optimal potassium CB. These results show that under certain conditions channel blocking can increase and optimize the spike coherence and the synchronization on the complex HH neuron networks, whereby the neurons would exhibit a better and the best sub-threshold signal encoding.

Suggested Citation

  • Gong, Yubing & Hao, Yinghang & Xie, Yanhang, 2010. "Channel block-optimized spiking activity of Hodgkin–Huxley neurons on random networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(2), pages 349-357.
  • Handle: RePEc:eee:phsmap:v:389:y:2010:i:2:p:349-357
    DOI: 10.1016/j.physa.2009.09.033
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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. 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.
    3. 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.

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