Talk at the University of Wisconsin, Madison, March 2, 2001
Host: Dr. Amir Assadi

Cognitive Event-Related Brain Dynamics

For nearly forty years, the study of human event-related brain dynamics was dominated by the study of averaged event-related potentials (ERPs) or magnetic 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. Second, the averaging era encouraged an enduring separation between the fields of human electrophysiology and animal neurophysiology, potentiated by the near-total neglect of local field potentials by neurophysiologists who record them.

Currently, however, a new approach to analysis of electromagnetic brain data is emerging, a field I call cognitive event-related brain dynamics. The ever-increasing availability of fast computational resources allow new generations of cognitive neuroscientists to study the event-related dynamics of the scalp-recorded electromagnetic field using combinations of complex and sophisticated methods including independent component analysis, time/frequency analysis, event-related coherence, non-linear dynamics and source imaging. Applying these new techniques to multi-channel EEG data from a variety of cognitive experiments reveals that the EEG data contain a great deal of still unresolved information about mechanisms of neural synchronization within and between brain areas. Further, this information appears to converge with new findings in cellular and sub-cellular neuroscience.

I will present some recent results of our studies of temporally independent components of EEG data sets recorded during visual selective attention tasks. The results suggest that new models of event-related brain dynamics may give more information about brain processes supporting cognition than standard measures of averaged ERPs, EEG spectral power and coherence. These results, combined with many others now appearing in the scientific literature, suggest that new measures of event-related brain dynamics may soon produce much more complete, testable models of the brain processes supporting human awareness and cognition.

Scott Makeig
The Salk Institute and
Institute for Neural Computation
University of California San Diego

Return to Current Abstracts