Estimation of Synchronization from Noisy Data with Application to Human Brain Activity

We discuss the problem of analysis of bivariate time series from the viewpoint of synchronization theory; it is assumed that the data are measured at the outputs of two possibly interacting self-sustained oscillators. We show that analyzing the relation between instantaneous phases of two signals we can estimate the degree of interaction between the systems. We briefly sketch how to apply our analysis to magnetoencephalography data.

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