Phase Coherence Induced by Additive Gaussian and Non-gaussian Noise in Excitable Networks With Application to Burst Suppression-Like Brain Signals - Hutt, Axel; Lefebvre, Jérémie; Hight, Darren; Kaiser, Heiko A. (Frontiers in Applied Mathematics and Statistics, 2020)
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 ana- lytical 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.