For example, this approach revealed scalp locations of maximum alpha/theta energy that could be directly related to CSD dipoles observed in the time domain (e.g., N1 ERS with N1 sink, NVS ERS with NVS), or be plausibly linked to known neurophysiological principles (e.g., a regional alpha/mu generator pattern). Although PCA has been employed to decompose time-frequency structure of ERP averages (e.g., Bernat et al., 2007), and EEG epochs have been CSD-transformed before employing time-frequency analysis (e.g., Cohen et al., 2009; Roberts et al., 2013), the combined CSD-PCA approach for the time-frequency analysis of EEG epochs (i.e., ERSP) is an important development. It is also noteworthy that distinct time-frequency CSD components were observed for higher frequencies (i.e., beta; cf. supplementary Fig. S2), and, while not a focus of the present study, may offer promise for the study of high-frequency oscillations, particularly given the negative impact of volume conduction on conventional EEG measures (e.g., Fein et al., 1988; Guevara et al., 2005; Roach & Mathalon, 2008; Schiff, 2005; Uhlhaas et al., 2008).
