Analyzing and Visualizing Single-Trial Event-Related Potentials

Event-related potentials (ERPs), are portions of electroencephalographic (EEG) recordings that are both timeand phase-locked to experimental events. ERPs are usually averaged to increase their signal/noise ratio relative to non-phase locked EEG activity, regardless of the fact that response activity in single epochs may vary widely in time course and scalp distribution. This study applies a linear decomposition tool, Independent Component Analysis (ICA) [1], to multichannel single-trial EEG records to derive spatial filters that decompose single-trial EEG epochs into a sum of temporally independent and spatially fixed components arising from distinct or overlapping brain or extra-brain networks. Our results on normal and autistic subjects show that ICA can separate artifactual, stimulus-locked, response-locked, and. non-event related background EEG activities into separate components, allowing ( 1) removal of pervasive artifacts of all types from single-trial EEG records, and (2) identification of both stimulusand responselocked EEG components. Second, this study proposes a new visualization tool, the 'ERP image', for investigating variability in latencies and amplitudes of event-evoked responses in spontaneous EEG or MEG records. We show that sorting single-trial ERP epochs in order of reaction time and plotting the potentials in 2-D clearly reveals underlying patterns of response variability linked to performance. These analysis and visualization tools appear broadly applicable to electrophyiological research on both normal and clinical populations. Analyzing and Visualizing Single-Trial Event-Related Potentials 119