title: Improved spatial characterization of the epileptic brain by focusing on nonlinearity.
abstract: An advanced characterization of the complicated dynamical system brain is one of science's biggest challenges. Nonlinear time series analysis allows characterizing nonlinear dynamical systems in which low-dimensional nonlinearity gives rise to complex and irregular behavior. While several studies indicate that nonlinear methods can extract valuable information from neuronal dynamics, others doubt their necessity and conjecture that the same information can be obtained using classical linear techniques. To address this issue, we compared these two concepts, but included furthermore a combination of nonlinear measures with surrogates, an approach that has been designed to specifically focus on nonlinearity. As a benchmark we used the discriminative power to detect the seizure-generating hemisphere in medically intractable mesial temporal lobe epilepsy. We analyzed intracranial electroencephalographic recordings from the seizure-free interval of 29 patients. While the performance of both linear and nonlinear measures was weak, if not insignificant, a very high performance was obtained by the use of surrogate-corrected measures. Focusing on nonlinearity by using a combination of nonlinear measures with surrogates appears as the key to a successful characterization of the spatial distribution of the epileptic process.
authors.affiliation: John von Neumann Institute for Computing, Forschungszentrum Jülich GmbH, Jülich, Germany. ralphandrzejak@yahoo.de
authors.forename: Ralph G
authors.initials: RG
authors.lastname: Andrzejak
authors.forename: Florian
authors.initials: F
authors.lastname: Mormann
authors.forename: Guido
authors.initials: G
authors.lastname: Widman
authors.forename: Thomas
authors.initials: T
authors.lastname: Kreuz
authors.forename: Christian E
authors.initials: CE
authors.lastname: Elger
authors.forename: Klaus
authors.initials: K
authors.lastname: Lehnertz
mesh_terms: D004569:Electroencephalography; D004594:Electrophysiology; D004828:Epilepsies, Partial / Q000503:physiopathology* / Q000601:surgery; D006624:Hippocampus / Q000503:physiopathology; D006801:Humans; D017711:Nonlinear Dynamics; D011300:Preoperative Care; D012189:Retrospective Studies; D013995:Time