Abstract and Keywords
This chapter considers the relationship between ongoing electroencephalographic (EEG) activity as recorded in event-related paradigms and trial averages time locked to some class of experimental events, known as event-related potentials (ERPs). It first discusses the concept of the ERP as averaging potentials generated by spatially coherent activity within a number of cortical EEG source areas as well as nonbrain sources typically treated as data artifacts. Event-related potential image (ERP-image) plotting is used to visualize variability in EEG dynamics across trials associated with events of interest using an example data set. The concept and use of independent component analysis (ICA) is then introduced to undo the effects of source signal mixing at scalp electrodes and to identify EEG sources contributing to the averaged ERP. After presenting some basic time-frequency measures useful for studying trial-to-trial variability, the chapter takes another look at trial-to-trial variability, now focusing on the contributions of selected independent component processes to the recorded scalp signals.
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