title: Introducing spatio-temporal reasoning into the inverse problem in electroencephalography.
abstract: Studying the Brain's Electrical and Magnetic Signals (BEMS) requires the contribution of many area of research that include anatomy, neurophysiology and electromagnetic theory. NEUROLAB is a framework dedicated to the study of brain disorders. Upon completion, it should provide users with an intelligent computational environment that incorporates qualitative and quantitative models of the brain and head, and a model for representing and reasoning about time and space. Spatio-temporal knowledge of a given problem is represented as a constraint network where to each node of the network are attached temporal and spatial variables that must satisfy the constraints defined by the arch labels connecting the nodes. In this paper, we show how temporal reasoning can be combined with spatial descriptions to produce different scenarios of possible seizure spread. These scenarios can provide a priori information for the inverse problem the role of which is to localise the sources of the observed BEMS.
authors.affiliation: Departement d'Information Médicale, Université de Rennes I, France.
authors.forename: P
authors.initials: P
authors.lastname: Siregar
authors.forename: J P
authors.initials: JP
authors.lastname: Sinteff
mesh_terms: D001185:Artificial Intelligence; D004569:Electroencephalography; D005103:Expert Systems; D006801:Humans; D008959:Models, Neurological; D016571:Neural Networks, Computer; D012640:Seizures / Q000503:physiopathology; D013028:Space Perception / Q000502:physiology*; D013998:Time Perception / Q000502:physiology*