State-of-the-art of seizure prediction

Although there are numerous studies exploring basic neuronal mechanisms that are likely to be associated with seizures, to date no definite information is available as to how, when, or why a seizure occurs in humans. The fact that seizures occur without warning in the majority of cases is one of the most disabling aspects of epilepsy. If it were possible to identify preictal precursors from the EEG of epilepsy patients, therapeutic possibilities and quality of life could improve dramatically. The last three decades have witnessed a rapid increase in the development of new EEG analysis techniques that appear to be capable of defining seizure precursors. Since the 1970s, studies on seizure prediction have advanced from preliminary descriptions of preictal phenomena and proof of principle studies via controlled studies to studies on continuous multiday recordings. At present, it is unclear whether prospective algorithms can predict seizures. If prediction algorithms are to be used in invasive seizure intervention techniques in humans, they must be proven to perform considerably better than a random predictor. The authors present an overview of the field of seizure prediction, its history, accomplishments, recent controversies, and potential for future development.