Multichannel MP + EEG IS

We present a new approach to the preprocessing of the electroencephalographic time series for EEG inverse solutions. As the first step, EEG recordings are decomposed by multichannel matching pursuit algorithm in this study we introduce a computationally e±cient, suboptimal solution. Then, based upon the parameters of the waveforms fitted to the EEG (frequency, amplitude and duration), we choose those corresponding to the the phenomena of interest, like e.g. sleep spindles. For each structure, the corresponding weights of each channel define a topographic signature, which can be subject to an inverse solution procedure, like e.g. Loreta, used in this work. As an example, we present an automatic detection and parameterization of sleep spindles, appearing in overnight polysomnographic recordings. Inverse solutions obtained for single sleep spindles are coherent with the averages obtained for 20 overnight EEG recordings analyzed in this study, as well as with the results reported previously in literature as inter-subject averages of solutions for spectral integrals, computed on visually selected spindles.

Piotr J. Durka (a) Artur Matysiak (a) Eduardo Martinez Montes (b) Pedro Valdes Sosa (b) Katarzyna J. Blinowska (a) (a) Department of Biomedical Physics, Institute of Experimental Physics, Warsaw University, ul. Hoża 69, 00-681 Warszawa, Poland, http://brain.fuw.edu.pl. (b) Cuban Neuroscience Center, Ave 25 #15202 esquina 158 Cubanacan, Playa, Area Code 11600, Habana, Cuba. Accepted for publication in Journal of Neuroscience Methods, 2005 My Related Items From Eeg.Pl