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Formation of Autapse Connected to Neuron and Its Biological Function

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Listed:
  • Chunni Wang
  • Shengli Guo
  • Ying Xu
  • Jun Ma
  • Jun Tang
  • Faris Alzahrani
  • Aatef Hobiny

Abstract

Autapse is a specific synapse connected to the neuron via close loop, and its functional adjusting is described by applying time-delayed feedback on the membrane potential of the neuron. This paper discussed the possible formation mechanism and biological function of autapse connection on neurons. We believe that the formation and growth of autapse connected to neuron can be associated with injury on axon and blocking in signal transmission; thus auxiliary loop is developed to form an autapse. When autapse is set up, it can propagate the signals and change the modes of electrical activities under self-adaption. Based on the cable neuron model, the injury on axon is generated by poisoning and blocking in ion channels (of sodium); thus the conductance of ion channels are changed to form injury-associated defects. Furthermore, auxiliary loop with time delay is designed to restore and enhance signal propagation by setting different time delays and feedback gains. The numerical studies confirmed that appropriate time delay and feedback gain in electric or chemical autapse can help signal (or wave generated by external forcing) propagation across the blocked area. As a result, formation of autapse could be dependent on the injury of neuron and further enhances the self-adaption to external stimuli.

Suggested Citation

  • 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.
  • Handle: RePEc:hin:complx:5436737
    DOI: 10.1155/2017/5436737
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    References listed on IDEAS

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    Cited by:

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    4. Peng, Lu & Tang, Jun & Ma, Jun & Luo, Jinming, 2022. "The influence of autapse on synchronous firing in small-world neural networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
    5. Zhang, Ge & Wang, Chunni & Alzahrani, Faris & Wu, Fuqiang & An, Xinlei, 2018. "Investigation of dynamical behaviors of neurons driven by memristive synapse," Chaos, Solitons & Fractals, Elsevier, vol. 108(C), pages 15-24.
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    8. Shengli Guo & Jun Tang & Jun Ma & Chunni Wang, 2017. "Autaptic Modulation of Electrical Activity in a Network of Neuron-Coupled Astrocyte," Complexity, Hindawi, vol. 2017, pages 1-13, June.
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    13. Xu, Ying & Jia, Ya & Ma, Jun & Alsaedi, Ahmed & Ahmad, Bashir, 2017. "Synchronization between neurons coupled by memristor," Chaos, Solitons & Fractals, Elsevier, vol. 104(C), pages 435-442.
    14. Yuangen Yao & Lijian Yang & Canjun Wang & Quan Liu & Rong Gui & Juan Xiong & Ming Yi, 2018. "Subthreshold Periodic Signal Detection by Bounded Noise-Induced Resonance in the FitzHugh–Nagumo Neuron," Complexity, Hindawi, vol. 2018, pages 1-10, February.
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    17. Qu, Lianghui & Du, Lin & Cao, Zilu & Hu, Haiwei & Deng, Zichen, 2021. "Pattern transition of neuronal networks induced by chemical autapses with random distribution," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    18. Ma, Jun & Wang, Ya & Wang, Chunni & Xu, Ying & Ren, Guodong, 2017. "Mode selection in electrical activities of myocardial cell exposed to electromagnetic radiation," Chaos, Solitons & Fractals, Elsevier, vol. 99(C), pages 219-225.
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