We used a novel application of principal components
analysis (spatiotemporal PCA) to decompose the event-related
brain potentials (ERPs) obtained with a dense electrode
array, with the purpose of elucidating the late ERP components
elicited by deviant stimuli under “attend”
and “ignore” conditions. First, a “spatial”
PCA was performed to identify a set of scalp distributions
(spatial factors or “virtual electrodes”) that
accounted for the spatial variance in the data set. The
data were expressed as spatial factor scores or “virtual
ERPs” measured at each of the virtual electrodes.
These virtual ERPs were submitted to a “temporal”
PCA, yielding a set of temporal factors or “virtual
epochs.” Statistical analyses of the temporal factor
scores found that (1) attended deviant stimuli elicited
the P300 and Novelty P3 components, the latter being largest
for highly salient nontargets; (2) “ignored”
deviants elicited a small Novelty P3, and depending on
the primary task, a small P300; and (3) the classical Slow
Wave consisted of separate frontal-negative and posterior-positive
components.