Abstract
A detailed description of an effective connectivity measure applied to the analysis of apileptogenic networks is presented. Signals from an intracraneal electroencephalography (iEEG) are analyzed. These signals come from 9 deep electrodes. Two spontaneous seizures from on patient of the Ramos Mejia Hospital (RMH) were analysed.
A statistical approach based in two thresholding steps allows the comparison of the connectivity between seizures and the non ictal periods. As an example, the methods is used for the analysis of one seizure.
To meassure the epileptogenic networks connectivity makes the epileptogenic zone (EZ) identification easier, which is of vital importance in a possible resective surgery. Therefore this could imply a better quality of life of post-surgical patients.
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© 2015 Springer International Publishing Switzerland
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Collavini, S., Blenkmann, A., Kochen, S. (2015). Effective Connectivity in Epileptogenic Networks. In: Braidot, A., Hadad, A. (eds) VI Latin American Congress on Biomedical Engineering CLAIB 2014, Paraná, Argentina 29, 30 & 31 October 2014. IFMBE Proceedings, vol 49. Springer, Cham. https://doi.org/10.1007/978-3-319-13117-7_174
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DOI: https://doi.org/10.1007/978-3-319-13117-7_174
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-13116-0
Online ISBN: 978-3-319-13117-7
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