SPATIOTEMPORAL MULTIPLE SOURCE LOCALIZATION BY WAVELET-TYPE DECOMPOSITION OF EVOKED-POTENTIALS

Scalp recording of electrical events allows evaluation of human cerebr al function, but contributions of the specific brain structures genera ting the recorded activity are ambiguous. This problem is ill-posed an d cannot be solved without auxiliary physiological knowledge about the spatio-temporal characteristics of the generators' activity. In our s ource localization by model-based wavelet-type decomposition, scalp re corded signals are decomposed into a combination of wavelets, each of which may describe the coherent activity of a population of neurons. W e chose the Hermite functions (derived from the Gaussian function to f orm mono-, bi- and triphasic wave forms) as the mathematical model to describe the temporal pattern of mass neural activity. For each wavele t we solve the inverse problem for two symmetrically positioned and or iented dipoles, one of which attains zero magnitude when a single sour ce is more suitable. We use the wavelet to model the temporal activity pattern of the symmetrical dipoles. By this we reduce the dimension o f inverse problem and find a plausible solution. Once the number and t he initial parameters of the sources are given, we can apply multiple source localization to correct the solution for generators with overla pping activities. Application of the procedure to subcortical and cort ical components of somatosensory evoked potentials demonstrates its fe asibility.