Frontiers in Applied Mathematics and Statistics (Jan 2020)
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 non-linear 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 behavior is described analytically for iid noise as well. Stochastic transitions and coherence resonance-like behavior 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 anesthesia, 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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