MULTIRESOLUTION DECOMPOSITION OF NONSTATIONARY EEG SIGNALS - A PRELIMINARY-STUDY

Wavelet representation is a recent development in the analysis of non- stationary signals. Its possibilities for use in the description of ti me-frequency characteristics of both transients in spontaneous EEG and time-varying rhythms in event related brain activity are explored her e. By way of illustration, multiresolution decompositions of a wide va riety of EEG transients are carried out in this work, including spike- and-waves, single spikes, sharp waves, blink artifacts, frontal interm ittent rhythmic delta activity (FIRDA) and paroxysmal delta activity. Also, the application of the wavelet representation to study event rel ated spectra perturbations is illustrated with data from psychophysica l experiments on the perception of image motion. The results demonstra te the capabilities of the wavelet transform, as an alternative to the Fourier transform, for the representation and analysis of non-station ary EEG signals.