The work aims to investigate the nonlinear dynamics in CEN/DMN networks. To this end, we applied phase-space embedding and multivariate autoregressive modeling of the phase-space trajectory. Furthermore, the AR coefficients were analyzed with a linear discriminant analysis to identify principle features that distinguish between patients and controls. The method was able to reveal differences in nonlinear dynamics in CEN and DMN networks respectively and jointly.
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