  We investigate the relative merit of phase-based methods---mean phase
coherence, unweighted and weighted phase lag index---for estimating the
strength of interactions between dynamical systems from empirical time series
which are affected by common sources and noise. By numerically analyzing the
interaction dynamics of coupled model systems, we compare these methods to each
other with respect to their ability to distinguish between different levels of
coupling for various simulated experimental situations. We complement our
numerical studies by investigating consistency and temporal variations of the
strength of interactions within and between brain regions using intracranial
electroencephalographic recordings from an epilepsy patient. Our findings
indicate that the unweighted and weighted phase lag index are less prone to the
influence of common sources but that this advantage may lead to constrictions
limiting the applicability of these methods.
