For nearly forty years the study of human event-related brain dynamics was dominated by the study of averaged event-related potentials (ERPs) and fields (ERFs) recorded and averaged time locked to classes of experimental events. ERPs and ERFs provide unequivocal evidence of direct linkage between cognitive events and electrochemical brain events in a wide range of cognitive paradigms. However, collapsing a set of complex, multidimensional data epochs to a skeleton set of peak amplitude and latency measures of a response average actually conceals, rather than reveals, many important types of event-related EEG brain dynamics. The unfortunate side effects of the averaging era include, first, a near-complete divorce between the innately related sub-fields of ERP and of EEG research, and second, an enduring separation between the fields of human electrophysiology and animal neurophysiology, the latter potentiated by the near-total neglect of local field potentials by neurophysiologists who record them.

The recent millenary, however, coincides with the emergence of a field I propose to call cognitive event-related brain dynamics. The availability of ever-increasing computational resources allow new generations of cognitive neuroscientists to study the dynamics of the scalp-recorded electromagnetic field using combinations of complex and sophisticated methods including source imaging, time/frequency analysis, event-related coherence, non-linear dynamics and independent component analysis. Applying these new techniques reveals that the EEG and MEG data contain a great deal of yet unappreciated information about mechanisms of neural synchronization within and between brain areas. Further, this information appears to be convergent with new findings in cellular neuroscience. These and related views of event-related brain dynamics may soon combine to give a much richer picture of the brain processes supporting human cognition and consciousness.