Abstracts

Independent component analysis (ICA) is a novel system that finds independent sources in recorded signals. One of its capabilities is probably to separate epileptiform activity of different origin. The goal of this study was to probe that ICA is useful for differentiating focal and multifocal epilepsies We analyzed with ICA 120 samples of 12 patients with unifocal (temporal (n=3), frontal (n=3) or multifocal epilepsy (bitemporal (n=3), extratemporal (n=3)). Each sample contained at least 2 spikes. The samples were recorded digitally with a 32-channels Lamont amplifiers and Harmonie 5.2b program. ICA was applied using the JADE algorithm implemented in a Matlab platform. The components were identified visually. The EEG and the isovoltage map of the suspected components were reconstructed to probe the nature and location of each spike. In multifocal epilepsies, the spikes were separated in different components in all cases. In unifocal epilepsies ICA found in a single component all the spikes of the same location. In some of these cases, other components were responsible for small parts of the spikes. Frontal spikes were separated very often in several components, but if they were unifocal a single component included part of all the spikes. The components of the waves were separated in different components both in the unifocal and in the multifocal samples. ICA separates in different components multifocal spikes while includes in a single component spikes of the same focus. ICA might be a useful tool to distinguish between unifocal and multifocal epilepsies. (Supported by the [ldquo]UTE project CIMA[rdquo] and by the Government of Navarra, grants for research in Health 12/2003 and 16/2003. Dr Urrestarazu is a Research Fellow supported by a grant for research of the Department of Education of the Basque Government.)