Epileptic seizures as extreme events in the human brain: Possibilities for prediction and prevention

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Epilepsy affects 60 million humans worldwide, approximately 1% of the world population. In about 25% of individuals with epilepsy, seizures cannot be controlled by any available therapy. A method capable of detecting seizure precursors could significantly improve the therapeutic possibilities and thereby the quality of life for epilepsy patients. Currently available analysis techniques used to detect seizure precursors from the ongoing electroencephalogram (EEG), however, are not yet sufficient to provide clinically satisfactory solutions. During the previous funding period world-wide efforts have thus been made to improve this situation. With our EEG analysis and neuron network modeling approaches we could achieve an improved characterization of spatial-temporal aspects of the seizure generating process in epileptic brain networks. Nevertheless, we also identified a number of poorly understood factors that appear to affect analytical and modeling approaches, thus hampering an improved detection of seizure precursors and an improved understanding of the epileptic process. In order to achieve the long-term goal of this project - the development of an automated system for the prediction of epileptic seizures - we therefore aim to further improve our analytical and modeling approaches, and to enhance the EEG-based prediction of seizures through a combination of both approaches.