Unlocking the Cognitive Dynamics of the Frontal Lobes
EEG and Clinical Neuroscience Society (ECNS) satellite meeting "Electrophysiology in Clinical Practice and Research" Istanbul, June 27-29, 2001 Scott Makeig The Salk Institute and Swartz Center for Computational Neuroscience Institute for Neural Computation University of California San Diego http://www.sccn.ucsd.edu/~scott
For nearly forty years, the study of human event-related brain dynamics was dominated by the study of event-related potentials (ERPs) or magnetic fields (ERFs) 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 complex, multidimensional data sets to a small set of average response measures actually conceals, rather than reveals, most of the event-related brain dynamics contained in the data. Unfortunate effects of response averaging include artificial separations between ERP and EEG research and between human and animal electrophysiology, the latter potentiated by the near-total neglect by neurophysiologists of local field potentials. Currently, however, new approaches to the analysis of electromagnetic brain data are making possible a more adequate study of human event-related brain dynamics. Affordable high-speed computational resources allow new generations of researchers to study the event-related dynamics of the scalp-recorded electromagnetic field using combinations of new analysis techniques including independent component analysis (ICA), time/frequency analysis, event-related coherence, non-linear dynamics and inverse source imaging. Applying these new techniques to multi-channel EEG data recorded in cognitive experiments reveals information about neural synchronization within and between brain areas that recent neurophysiological results suggest may be fundamental to brain function. I will present some recent results on the dynamics of temporally independent components of EEG data recorded during a variety of tasks. ICA allows for the removal of eye and muscle artifacts without degrading the quality of brain activity projecting to the frontal and periocular scalp, revealing new details of EEG dynamics in the frontal lobes. Our recent work has found at least three categories of frontal and midline EEG sources whose separate and joint dynamics are coupled to cognitive performance. Applications to clinical research in psychiatric and neurological disorders appears promising. These and other new measures of event-related brain dynamics may soon lead to more complete and testable models of macroscopic brain processes supporting human awareness and cognition.