Decomposition of EEG signals for multichannel neural activity analysis in animal experiments

Abstract. We describe in this paper an advanced protocol for the discrimination and the classification of neuronal spike waveforms within multichannel electro-physiological recordings. Sparse decomposition was used to serarate the linearly independent signals underlying sensory information in cortical spike firing pat-terns. We introduce some modifications in the the IDE algorithm to take into account prior knowledge on the spike waveforms. We have investigated motor cortex responses recorded during movement in freely moving rats to provide ev-idence for the relationship between these patterns and special behavioral task