lagged connectivity measure has the important property of being relatively robust to the strength of the instantaneous component, i.e. it can still detect physiological “non-zero” lagged connectivity even in the presence of large instantaneous artifacts, while the imaginary part of the coherence fails to detect a lagged connection by tending to zero if the instantaneous component is large [24]. This would also apply to phase synchronization, since it is nothing more than the coherence for unit modulus (amplitude-free) Fourier transform coefficients. The phase lag index proposed by Stam et al. [41] represents an improvement over the imaginary part of the coherence because it is less affected by phase delay. However, it is also relatively insensitive to true changes in phase synchronization when the phase lies very close to zero, which is likely to happen as the instantaneous component increases. Because of a proper model for the two components of a connection (i.e., instantaneous and lagged), eLORETA connectivity algorithm is thought to detect genuine physiological connectivity. Furthermore, it can be applied to filtered data, thus giving a frequency decomposition of brain connectivity [24].
