A coarse-grained framework for spiking neuronal networks: between homogeneity and synchrony

Journal of Computational Neuroscience
Jiwei ZhangAaditya V Rangan

Abstract

Homogeneously structured networks of neurons driven by noise can exhibit a broad range of dynamic behavior. This dynamic behavior can range from homogeneity to synchrony, and often incorporates brief spurts of collaborative activity which we call multiple-firing-events (MFEs). These multiple-firing-events depend on neither structured architecture nor structured input, and are an emergent property of the system. Although these MFEs likely play a major role in the neuronal avalanches observed in culture and in vivo, the mechanisms underlying these MFEs cannot easily be captured using current population-dynamics models. In this work we introduce a coarse-grained framework which illustrates certain dynamics responsible for the generation of MFEs. By using a new kind of ensemble-average, this coarse-grained framework can not only address the nucleation of MFEs, but can also faithfully capture a broad range of dynamic regimes ranging from homogeneity to synchrony.

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Oct 26, 2012·Journal of Computational Neuroscience·Aaditya V Rangan, Lai-Sang Young
Mar 23, 2013·Journal of Computational Neuroscience·Aaditya V Rangan, Lai-Sang Young
Jul 16, 2013·Journal of Computational Neuroscience·Jiwei ZhangAaditya Rangan

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Citations

Jul 16, 2013·Journal of Computational Neuroscience·Jiwei ZhangAaditya Rangan
Mar 26, 2016·Frontiers in Physiology·Hong LeiAaditya V Rangan
Jan 21, 2015·Journal of Computational Neuroscience·J W Zhang, A V Rangan
Jul 12, 2019·Journal of Mathematical Biology·Yao Li, Hui Xu
Apr 3, 2019·Physical Review. E·Zhi-Qin John XuDavid Cai
Sep 8, 2021·Frontiers in Computational Neuroscience·Yuhang CaiZhuo-Cheng Xiao

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