MULTICHANNEL WAVELET-TYPE DECOMPOSITION OF EVOKED-POTENTIALS - MODEL-BASED RECOGNITION OF GENERATOR ACTIVITY

Scalp recording of electrical events allows the evaluation of human ce rebral function, but contributions of the specific brain structures ge nerating the recorded activity are ambiguous. This problem is ill-pose d and cannot be solved without physiological constraints based on the spatio-temporal characteristics of the generators' activity. In our mo del-based analysis of evoked potentials for the purpose of generator a ctivity detection, multichannel scalp-recorded signals are decomposed into a combination of wavelets, each of which can describe the neural mass coherent activity of cell assemblies. Elimination of contribution s of specific generators and/or distributed background activity can pr oduce physiologically motivated time-frequency filtering. The decompos ition and filtering procedures are demonstrated by three examples: sim ulation of the surface manifestation of known intracranial generators; decomposition and reconstruction of auditory brainstem evoked potenti als which reflect the differences among generators of these potentials ; and cognitive components of evoked potentials which are diminished i n the averaged recording but are clearly detected in single-trial sign als.