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Cooperative dynamics in neuronal networks

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  • Wang, Qingyun
  • Zheng, Yanhong
  • Ma, Jun

Abstract

There exist rich cooperative behaviors and their transitions in biological neuronal systems as some key biological factors are changed. Among all of cooperative behaviors of neuronal systems, the existing experiments have shown that the spatiotemporal pattern and synchronization dynamics are very crucial, which are closely related to normal function and dysfunction of neuronal systems. Based on different neuron models, the recent works have been made to explore the mechanisms of pattern formation and synchronization transition. This paper mainly overviews the recent studies of the cooperative dynamics including the pattern formation and synchronization transition in biological neuronal networks. Firstly, we review complicated spatiotemporal pattern dynamics of neuronal networks. Secondly, the interesting synchronization transition is reviewed. Finally, conclusion is given and we put forward some outlooks of research on the cooperative behaviors in real neuronal networks.

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  • Wang, Qingyun & Zheng, Yanhong & Ma, Jun, 2013. "Cooperative dynamics in neuronal networks," Chaos, Solitons & Fractals, Elsevier, vol. 56(C), pages 19-27.
    • Handle: RePEc:eee:chsofr:v:56:y:2013:i:c:p:19-27
    DOI: 10.1016/j.chaos.2013.05.003
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    Cited by:

    1. Upadhyay, Ranjit Kumar & Mondal, Argha, 2017. "Synchronization of bursting neurons with a slowly varying d. c. current," Chaos, Solitons & Fractals, Elsevier, vol. 99(C), pages 195-208.
    2. Huang, Shoufang & Zhang, Jiqian & Wang, Maosheng & Hu, Chin-Kun, 2018. "Firing patterns transition and desynchronization induced by time delay in neural networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 88-97.
    3. Fedaravičius, Augustinas Povilas & Cao, Maosen & Ragulskis, Minvydas, 2016. "Control of a dendritic neuron driven by a phase-independent stimulation," Chaos, Solitons & Fractals, Elsevier, vol. 85(C), pages 77-83.
    4. Zheng, Y.G. & Bao, L.J., 2017. "Effect of topological structure on synchronizability of network with connection delay," Chaos, Solitons & Fractals, Elsevier, vol. 98(C), pages 145-151.
    5. Huang, Shoufang & Zhang, Jiqian & Hu, Chin-Kun, 2019. "Effects of external stimulations on transition behaviors in neural network with time-delay," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    6. Pham, Tuan D., 2014. "The butterfly effect in ER dynamics and ER-mitochondrial contacts," Chaos, Solitons & Fractals, Elsevier, vol. 65(C), pages 5-19.
    7. Mondal, Argha & Upadhyay, Ranjit Kumar, 2017. "Dynamics of a modified Hindmarsh–Rose neural model with random perturbations: Moment analysis and firing activities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 144-160.

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