title: Role of multiple-scale modeling of epilepsy in seizure forecasting.
abstract: 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, we review the literature on the multiple-scale neural modeling of epilepsy and the use of such models to infer physiologic changes underlying epilepsy and epileptic seizures. The authors argue how these methods can be applied to advance the state-of-the-art in seizure forecasting.
authors.affiliation: *Neuroengineering Laboratory, Department of Electrical and Electronic Engineering, The University of Melbourne, Melbourne, Victoria, Australia; †Brain Dynamics Unit, Brain and Psychological Sciences Research Centre, Swinburne University of Technology, Hawthorn, Victoria, Australia; ‡Centre for Neural Engineering, The University of Melbourne, Melbourne, Victoria, Australia; §Bionics Institute, East Melbourne, Victoria, Australia; ‖St. Vincent's Hospital Melbourne, Fitzroy, Victoria, Australia; ¶INSERM, U1099, Rennes, France; #Université de Rennes, LTSI, Rennes, France; and **Departments of Engineering Science and Mechanics, Center for Neural Engineering, Neurosurgery, and Physics, The Pennsylvania State University, University Park, Pennsylvania, U.S.A.
authors.forename: Levin
authors.initials: L
authors.lastname: Kuhlmann
authors.forename: David B
authors.initials: DB
authors.lastname: Grayden
authors.forename: Fabrice
authors.initials: F
authors.lastname: Wendling
authors.forename: Steven J
authors.initials: SJ
authors.lastname: Schiff
mesh_terms: D000818:Animals; D004827:Epilepsy / Q000503:physiopathology*; D005544:Forecasting; D006801:Humans; D008959:Models, Neurological; D009415:Nerve Net / Q000503:physiopathology; D066230:Patient-Specific Modeling