We have proposed a generic analytic strategy for multi-channel ERP recordings that can overcome these limitations: first, convert reference-dependent surface potentials into reference-free current source density (CSD; surface Laplacian) waveforms representing the radial current flow into (sources) and out of (sinks) the scalp (any EEG reference will yield the same, unique CSD waveforms, with reduced volume-conducted contributions and sharper topographies than ERPs), and second, identify unique and orthogonal variance patterns in these reference-free data by means of temporal, unrestricted Varimax-PCA using the covariance matrix (Kayser and Tenke, 2006a, 2006b;for details on surface Laplacian estimates, see Tenke and Kayser, 2005; for detailed arguments regarding unrestricted factor extraction/rotation and preferability for covariance- over correlation-based factor loadings, see Kayser and Tenke, 2005, 2006c). Apart from the theoretical advantages of this CSD-PCA approach over traditional ERP analytic methods, a systematic comparison between ERP-PCA and CSD-PCA solutions has provided empirical evidence that no ERP information is distorted or lost after eliminating ambiguities stemming from the recording reference; instead, experimental effects were clarified and additional insights emerged when utilizing CSD as a bridge between montage-dependent scalp
