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Phase coherence induced by additive Gaussian and non-Gaussian noise in excitable networks with application to burst suppression-like brain signals

Abstract : It is well-known that additive noise affects the stability of nonlinear systems. Using a network composed of two interacting populations , detailed stochastic and non-linear analysis demonstrates that increasing the intensity of iid additive noise induces a phase transition from a spectrally broad-band state to a phase-coherent oscillatory state. Corresponding coherence resonance-like system behaviour is described analytically for iid noise as well. Stochastic transitions and coherence resonance-like behaviour were also found to occur for non-iid additive noise induced by increased heterogeneity, corresponding analytical results complement the analysis. Finally, the results are applied to burst suppression-like patterns observed in electroencephalographic data under anaesthesia, providing strong evidence that these patterns reflect jumps between random and phase-coherent neural states induced by varying external additive noise levels.
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https://hal.inria.fr/hal-02428175
Contributor : Axel Hutt <>
Submitted on : Monday, January 6, 2020 - 2:18:20 PM
Last modification on : Tuesday, June 9, 2020 - 11:10:02 AM
Long-term archiving on: : Tuesday, April 7, 2020 - 7:25:02 PM

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Axel Hutt, Jérémie Lefebvre, Darren Hight, Heiko Kaiser. Phase coherence induced by additive Gaussian and non-Gaussian noise in excitable networks with application to burst suppression-like brain signals. Frontiers in Applied Mathematics and Statistics, Frontiers Media S.A, In press. ⟨hal-02428175⟩

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