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The collective bursting dynamics in a modular neuronal network with synaptic plasticity

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Abstract

In this study, how the synaptic plasticity influences the collective bursting dynamics in a modular neuronal network is numerically investigated. The synaptic plasticity is described by a modified Oja’s learning rule. The modular network is composed of some sub-networks, each of them having small-world characteristic. The result indicates that bursting synchronization can be induced by large coupling strength between different neurons, which is robust to the local dynamical parameter of individual neurons. With the emergence of synaptic plasticity, the bursting dynamics in the modular neuronal network, particularly the excitability and synchronizability of bursting neurons, is detected to be changed significantly. In detail, upon increasing synaptic learning rate, the excitability of bursting neurons is greatly enhanced; on the contrary, bursting synchronization between interacted neurons is a little suppressed by the increase in synaptic learning rate. The presented findings could be helpful to understand the important role of synaptic plasticity on neural coding in realistic neuronal network.

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Acknowledgements

This work is partially supported by the National Natural Science Foundation of China (Grant No. 11572180) and the Fundamental Funds Research for the Central Universities (Grant Nos. GK201602009, GK201701001).

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Authors and Affiliations

  1. College of Mathematics and Information Science, Shaanxi Normal University, Xi’an, 710062, People’s Republic of China

    Xiao Li Yang & Jia Yi Wang

  2. Department of Applied Mathematics, Northwestern Polytechnical University, Xi’an, 710072, People’s Republic of China

    Zhong Kui Sun

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  1. Xiao Li Yang
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  2. Jia Yi Wang
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  3. Zhong Kui Sun
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Correspondence to Xiao Li Yang.

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Yang, X.L., Wang, J.Y. & Sun, Z.K. The collective bursting dynamics in a modular neuronal network with synaptic plasticity. Nonlinear Dyn 89, 2593–2602 (2017). https://doi.org/10.1007/s11071-017-3606-y

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  • DOI: https://doi.org/10.1007/s11071-017-3606-y

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