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Quantification of synchronization phenomena in two reciprocally gap-junction coupled bursting pancreatic β-cells

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  • Wang, Jing
  • Liu, Shenquan
  • Liu, Xuanliang

Abstract

This paper aims to discuss our research into synchronized transitions in two reciprocally gap-junction coupled bursting pancreatic β-cells. Numerical results revealed that propagations of synchronous states could be induced not only by changing the coupling strength, but also by varying the slow time constant. Firstly, these asynchronous and synchronous states such as out-of-phase, almost in-phase and in-phase synchronization were specifically demonstrated by phase portraits and time evolutions. By comparing interspike intervals (ISI) bifurcation diagrams of two coupled neurons with an individual neuron, we found that coupling strength played a critical role in tonic-to-bursting transitions. In particular, with the phase difference and ISI-distance being introduced, regions of various synchronous and asynchronous states were plotted in a two-dimensional parameter space. More interestingly, it was found that the coupled neurons could always realize complete synchronization as long as the coupling strength was appropriate.

Suggested Citation

  • Wang, Jing & Liu, Shenquan & Liu, Xuanliang, 2014. "Quantification of synchronization phenomena in two reciprocally gap-junction coupled bursting pancreatic β-cells," Chaos, Solitons & Fractals, Elsevier, vol. 68(C), pages 65-71.
    • Handle: RePEc:eee:chsofr:v:68:y:2014:i:c:p:65-71
    DOI: 10.1016/j.chaos.2014.07.012
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    References listed on IDEAS

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    2. Liu, Chen & Wang, Jiang & Wang, Lin & Yu, Haitao & Deng, Bin & Wei, Xile & Tsang, Kaiming & Chan, Wailok, 2014. "Multiple synchronization transitions in scale-free neuronal networks with electrical and chemical hybrid synapses," Chaos, Solitons & Fractals, Elsevier, vol. 59(C), pages 1-12.
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    1. Wang, Jing & Ye, Weijie & Liu, Shenquan & Lu, Bo & Jiang, Xiaofang, 2016. "Qualitative and quantitative aspects of synchronization in coupled CA1 pyramidal neurons," Chaos, Solitons & Fractals, Elsevier, vol. 93(C), pages 32-38.

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