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  3. Localization of Epileptogenic Zone on Pre-surgical Intracranial EEG Recordings: Toward a Validation of Quantitative Signal Analysis Approaches
 

Localization of Epileptogenic Zone on Pre-surgical Intracranial EEG Recordings: Toward a Validation of Quantitative Signal Analysis Approaches

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BORIS DOI
10.7892/boris.58186
Date of Publication
June 15, 2014
Publication Type
Article
Division/Institute

Universitätsklinik fü...

Contributor
Andrzejak, Ralph G
David, Olivier
Gnatkovsky, Vadym
Wendling, Fabrice
Bartolomei, Fabrice
Francione, Stefano
Kahane, Philippe
Schindler, Kaspar
Universitätsklinik für Neurologie
de Curtis, Marco
Subject(s)

600 - Technology::610...

Series
Brain topography
ISSN or ISBN (if monograph)
0896-0267
Publisher
Springer
Language
English
Publisher DOI
10.1007/s10548-014-0380-8
PubMed ID
24929558
Description
In patients diagnosed with pharmaco-resistant epilepsy, cerebral areas responsible for seizure generation can be defined by performing implantation of intracranial electrodes. The identification of the epileptogenic zone (EZ) is based on visual inspection of the intracranial electroencephalogram (IEEG) performed by highly qualified neurophysiologists. New computer-based quantitative EEG analyses have been developed in collaboration with the signal analysis community to expedite EZ detection. The aim of the present report is to compare different signal analysis approaches developed in four different European laboratories working in close collaboration with four European Epilepsy Centers. Computer-based signal analysis methods were retrospectively applied to IEEG recordings performed in four patients undergoing pre-surgical exploration of pharmaco-resistant epilepsy. The four methods elaborated by the different teams to identify the EZ are based either on frequency analysis, on nonlinear signal analysis, on connectivity measures or on statistical parametric mapping of epileptogenicity indices. All methods converge on the identification of EZ in patients that present with fast activity at seizure onset. When traditional visual inspection was not successful in detecting EZ on IEEG, the different signal analysis methods produced highly discordant results. Quantitative analysis of IEEG recordings complement clinical evaluation by contributing to the study of epileptogenic networks during seizures. We demonstrate that the degree of sensitivity of different computer-based methods to detect the EZ in respect to visual EEG inspection depends on the specific seizure pattern.
Handle
https://boris-portal.unibe.ch/handle/20.500.12422/126111
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File(s)
FileFile TypeFormatSizeLicensePublisher/Copright statementContent
AndrzejakEtAlBrainTop2014.pdftextAdobe PDF1.7 MBpublishedOpen
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