with temporal, spatial or spatiotemporal PCA being fairly common (e.g., Barry and De Blasio, 2013; Kayser and Tenke, 2003; Spencer et al., 2001; van Boxtel, 1998). For a covariance association matrix, a common choice for factor extraction, the PCA identifies the variance structure by removal of the grand mean (i.e., the variance around the grand mean), which differs for every EEG reference. Thus, regardless of erroneous claims in the literature, a PCA or any other multivariate procedure that depends on data variance or absolute values does not constitute a reference-free approach (i.e., it will yields different results depending on the EEG reference).
