Prediction Error Profiles allowing a Seizure Forecasting in Epilepsy ?

Although a large number of publications has appeared, the problem of seizure forecasting in epilepsy remains unsolved up to now. The main problem is the derivation of EEG signal features, which show distinct changes of an impending epileptic seizure, occurring as seizure precursors. In previous publications (Niederhofer and Tetzlaff, 2005) several approaches to the feature extraction problem based on Volterra-Systems (VS) and cellular nonlinear networks (CNN) (Chua, 1998) have been proposed. Because distinct changes in the behaviour of discrete-time CNN predictor systems have been observed before the onsets of seizures, a deeper analysis of long lasting recordings of EEG signals will be given throughout this contribution