Pattern detection by cellular neuronal networks (CNN) in long-term recordings of a brain electrical activity in epilepsy

About 0.5% of the world population is suffering from a focal epilepsy (J. Engel et al., 2003), which is a widely spread disease. The goal of the investigations discussed in this paper is an early detection of precursors of an impending epileptic seizure by the analysis of brain electrical activity of multi-electrode EEG recordings. Therefore, methods of nonlinear signal processing were used in CNN simulations. This investigation is based on long-term recordings of approximately one week length, where analysis algorithms proposed in previous investigations (C. Niederhoefer et al., 2003) have been generalised toward new feature extraction methods which are presented in this paper.