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We investigate the relative merit of phase-based methods---mean phasecoherence, unweighted and weighted phase lag index---for estimating thestrength of interactions between dynamical systems from empirical time serieswhich are affected by common sources and noise. By numerically analyzing theinteraction dynamics of coupled model systems, we compare these methods to eachother with respect to their ability to distinguish between different levels ofcoupling for various simulated experimental situations. We complement ournumerical studies by investigating consistency and temporal variations of thestrength of interactions within and between brain regions using intracranialelectroencephalographic recordings from an epilepsy patient. Our findingsindicate that the unweighted and weighted phase lag index are less prone to theinfluence of common sources but that this advantage may lead to constrictionslimiting the applicability of these methods.

Can spurious indications for phase synchronization due to superimposed signals be avoided?