When combined with source modeling, magneto- (MEG) and electroencephalography (EEG) can be used to study
long-range interactions among cortical processes non-invasively. Estimation of such inter-areal connectivity is
nevertheless hindered by instantaneous field spread and volume conduction, which artificially introduce linear
correlations and impair source separability in cortical current estimates. To overcome the inflating effects of linear
source mixing inherent to standard interaction measures, alternative phase- and amplitude-correlation based
connectivity measures, such as imaginary coherence and orthogonalized amplitude correlation have been proposed.
Being by definition insensitive to zero-lag correlations, these techniques have become increasingly popular
in the identification of correlations that cannot be attributed to field spread or volume conduction. We show here,
however, that while these measures are immune to the direct effects of linear mixing, they may still reveal large
numbers of spurious false positive connections through field spread in the vicinity of true interactions. This
fundamental problem affects both region-of-interest-based analyses and all-to-all connectome mappings. Most
importantly, beyond defining and illustrating the problem of spurious, or “ghost” interactions, we provide a
rigorous quantification of this effect through extensive simulations. Additionally, we further show that signal
mixing also significantly limits the separability of neuronal phase and amplitude correlations. We conclude that
spurious correlations must be carefully considered in connectivity analyses in MEG/EEG source space even when
using measures that are immune to zero-lag correlations.