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The Impact of EEG/MEG Signal Processing and Modeling in the Diagnostic and Management of Epilepsy

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1 Author(s)
Fernando H. Lopes da Silva ; Center of Neurosci., Univ. of Amsterdam, Amsterdam

This overview covers recent advances in the field of EEG/MEG signal processing and modeling in epilepsy regarding both interictal and ictal phenomena. In the first part, the main methods used in the analysis of interictal EEG/MEG epileptiform spikes are presented and discussed. Source and volume conductor models are passed in review, namely the equivalent dipole source concept, the requirements for adequate time and spatial sampling, the question of how to validate source solutions, particularly by comparing solutions obtained using scalp and intracranial EEG signals, EEG & MEG data, or EEG simultaneously recorded with fMRI (BOLD signals). In the second part, methods used for the characterization of seizures are considered, namely dipolar modeling of spikes at seizure onset, decomposition of seizure EEG signals into sets of orthogonal spatio-temporal components, and also methods (linear and nonlinear) of estimating seizure propagation. In the third part, the crucial issue of how the transition between interictal and seizure activity takes place is examined. In particular the vicissitudes of the efforts along the road to seizure prediction are shortly reviewed. It is argued that this question can be reduced to the problem of estimating the excitability state of neuronal populations in the course of time as a seizure approaches. The value of active probing methods in contrast with passive analytical methods is emphasized. In the fourth part modeling aspects are considered in the light of two special kinds of epilepsies, absences characterized by spike-and-wave discharges and mesial temporal lobe epilepsy. These two types correspond to different scenarios regarding the transition to epileptic seizures, namely the former is a case of a jump transition and the latter is a typical case of gradual transition. In conclusion, the necessity of developing comprehensive computational models of epileptic seizures is emphasized.

Published in:

IEEE Reviews in Biomedical Engineering  (Volume:1 )