ArticleJournal of computational neuroscience2014
A coarse-grained framework for spiking neuronal networks: between homogeneity and synchrony.
Article in Journal of computational neuroscience, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Model Reduction Captures Stochastic Gamma Oscillations on Low-Dimensional Manifolds.Frontiers in computational neuroscience · 2021Article
- Dimensional reduction of emergent spatiotemporal cortical dynamics via a maximum entropy moment closure.PLoS computational biology · 2020Article
- Stochastic neural field model: multiple firing events and correlations.Journal of mathematical biology · 2019Article
- A coarse-graining framework for spiking neuronal networks: from strongly-coupled conductance-based integrate-and-fire neurons to augmented systems of ODEs.Journal of computational neuroscience · 2019Article
- Intrinsic and Network Mechanisms Constrain Neural Synchrony in the Moth Antennal Lobe.Frontiers in physiology · 2016Article
- A reduction for spiking integrate-and-fire network dynamics ranging from homogeneity to synchrony.Journal of computational neuroscience · 2015Article
- Distribution of correlated spiking events in a population-based approach for Integrate-and-Fire networks.Journal of computational neuroscience · 2014Article
- Granger causality network reconstruction of conductance-based integrate-and-fire neuronal systems.PloS one · 2014Article
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4 authors.
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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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