8th Joint Symposium on Neural Computation
The Salk Institute
La Jolla, California
May 19, 2001
11:00 Scott Makeig, UCSD/Salk Institute
Inside-Out/Outside-In: EEG, Brain Dynamics and CognitionFor forty years, research in human electrophysiology has been dominated by studies of averaged event-related potentials (ERPs) 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, the standard 'ERP-plus-background-EEG' model of event-related changes in the EEG holds no mathematical privilege over any other linear decomposition of event-locked EEG data. This model would be a sufficient descriptor only if the EEG were a sum of noise processes with central tendency (e.g. Gaussian). However, the EEG has a low pass character, marked and complex oscillatory features, and a non-stationary temporal correlation structure. Changes in this structure induced by experimental events may produce the appearance of truly 'evoked' ERP activity in the response average.
Thus, contrary to common assumption evoked responses may not be produced by brief synchronous neural activations in brain areas briefly engaged in successive stages of stimulus-related information processing. Rather, every feature of an evoked response may actually be produced by event-related changes in the autocorrelation and cross-correlation structure of ongoing EEG processes, each reflecting synchronous activity occurring continuously in one or more brain regions, or by more subtle perturbations in their dynamics. Evidence derived by Independent Component Analysis (ICA), single-trial visualization, and time/frequency analysis shows that most or all features of averaged responses following target and nontarget stimuli in a visual selective attention experiment may be reinterpreted as artifacts of averaging applied to event-related changes in the dynamics of ongoing EEG processes. These can be measured as event-related changes in the phase distribution of the EEG (or MEG) time locked to experimental events. Recent neurophysiologic results from humans and animals are consonant with the picture of event-related brain dynamics produced by ICA applied to scalp EEG data.