Over the past three decades, a number of seizure prediction, or forecasting, methods have been developed. Although major achievements were accomplished regarding the statistical evaluation of proposed algorithms, it is recognized that further progress is still necessary for clinical application in patients. The lack of physiological motivation can partly explain this limitation. Therefore, a natural question is raised: can computational models of epilepsy be used to improve these methods? Here

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... e review the literature on the multiple-scale neural modelling of epilepsy and the use of such models to infer physiological changes underlying epilepsy and epileptic seizures. We argue how these methods can be applied to advance the state-of-the-art in seizure forecasting. Glossary LFP local field potential EEG electroencephalography iEEG intracranial electroencephalography K + potassium ion Na+ sodium ion GABA gamma-aminobutyric acid CA1 hippocampus, Cornu Ammonis area 1 PSP post-synaptic potential TLE temporal lobe epilepsy Kuhlmann et al.