title: Modeling epileptic brain states using EEG spectral analysis and topographic mapping.
abstract: Changes in the spatio-temporal behavior of the brain electrical activity are believed to be associated to epileptic brain states. We propose a novel methodology to identify the different states of the epileptic brain, based on the topographic mapping of the time varying relative power of delta, theta, alpha, beta and gamma frequency sub-bands, estimated from EEG. Using normalized-cuts segmentation algorithm, points of interest are identified in the topographic mappings and their trajectories over time are used for finding out relations with epileptogenic propagations in the brain. These trajectories are used to train a Hidden Markov Model (HMM), which models the different epileptic brain states and the transition among them. Applied to 10 patients suffering from focal seizures, with a total of 30 seizures over 497.3h of data, the methodology shows good results (an average point-by-point accuracy of 89.31%) for the identification of the four brain states--interictal, preictal, ictal and postictal. The results suggest that the spatio-temporal dynamics captured by the proposed methodology are related to the epileptic brain states and transitions involved in focal seizures.
authors: Center for Informatics and Systems of the University of Coimbra-CISUC, University of Coimbra, Pólo II, 3030-290 Coimbra, Portugal. brunodireito@dei.uc.pt
authors: Bruno
authors: B
authors: Direito
authors: César
authors: C
authors: Teixeira
authors: Bernardete
authors: B
authors: Ribeiro
authors: Miguel
authors: M
authors: Castelo-Branco
authors: Francisco
authors: F
authors: Sales
authors: António
authors: A
authors: Dourado
mesh_terms: D000465:Algorithms; D001921:Brain / Q000503:physiopathology*; D058256:Brain Waves / Q000502:physiology*; D004569:Electroencephalography; D004827:Epilepsy / Q000473:pathology* / Q000503:physiopathology; D006801:Humans; D008390:Markov Chains; D012016:Reference Values; D013057:Spectrum Analysis; D013997:Time Factors