The different source imaging methods are all characterized by a source-leakage effect, namely that the measured activity coming from a single elementary source is projected onto several nearby sources depending on the point spread function of the specific imaging method (Hauk et al., 2011). Source-leakage may induce a fake connectivity profile, usually referred to as “artificial connectivity” (Palva and Palva, 2012). This effect can be mitigated by using functional connectivity methods which exclude zero-phase correlations between source signals (see e.g., Marzetti et al., 2008; Nolte et al., 2009; Brookes et al., 2011a). Similarly, a priori selecting regions-of-interest as seeds for connectivity analysis, as opposed to performing whole-brain estimation, can provide misleading results in terms of “spurious connectivity” (Palva and Palva, 2012) as the activity of the sources not selected as seeds may leak into the estimated activity of the selected seeds (Hari and Parkkonen, 2015).
