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dc.contributor.authorSchindler, K
dc.contributor.authorRummel, C
dc.contributor.authorAndrzejak, RG
dc.contributor.authorGoodfellow, M
dc.contributor.authorZubler, F
dc.contributor.authorAbela, E
dc.contributor.authorWiest, R
dc.contributor.authorPollo, C
dc.contributor.authorSteimer, A
dc.contributor.authorGast, H
dc.date.accessioned2016-08-02T08:17:46Z
dc.date.issued2016-07-12
dc.description.abstractOBJECTIVE: To show that time-irreversible EEG signals recorded with intracranial electrodes during seizures can serve as markers of the epileptogenic zone. METHODS: We use the recently developed method of mapping time series into directed horizontal graphs (dHVG). Each node of the dHVG represents a time point in the original intracranial EEG (iEEG) signal. Statistically significant differences between the distributions of the nodes' number of input and output connections are used to detect time-irreversible iEEG signals. RESULTS: In 31 of 32 seizure recordings we found time-irreversible iEEG signals. The maximally time-irreversible signals always occurred during seizures, with highest probability in the middle of the first seizure half. These signals spanned a large range of frequencies and amplitudes but were all characterized by saw-tooth like shaped components. Brain regions removed from patients who became post-surgically seizure-free generated significantly larger time-irreversibilities than regions removed from patients who still had seizures after surgery. CONCLUSIONS: Our results corroborate that ictal time-irreversible iEEG signals can indeed serve as markers of the epileptogenic zone and can be efficiently detected and quantified in a time-resolved manner by dHVG based methods. SIGNIFICANCE: Ictal time-irreversible EEG signals can help to improve pre-surgical evaluation in patients suffering from pharmaco-resistant epilepsies.en_GB
dc.description.sponsorshipK.S. gratefully acknowledges support by the Swiss National Science Foundation (SNF 32003B_155950). H.G. gratefully acknowledges support by a Research Grant of the Inselspital Bern. R.G.A. acknowledges funding from the Volkswagen foundation and was supported by the Spanish Ministry of Economy and Competitiveness (Grant FIS2014-54177- R). This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 642563 (R.G.A.). MG gratefully acknowledges the financial support of the EPSRC via grant EP/N014391/1, funding from Epilepsy Research UK via grant number A1007 and was generously supported by a Wellcome Trust Institutional Strategic Support Award (WT105618MA).en_GB
dc.identifier.citationClinical Neurophysiology, 2016, Vol. 127, pp. 3051 Issue 9, pp. 3051- 3058en_GB
dc.identifier.doi10.1016/j.clinph.2016.07.001
dc.identifier.urihttp://hdl.handle.net/10871/22828
dc.language.isoenen_GB
dc.publisherElsevieren_GB
dc.relation.urlhttp://www.ncbi.nlm.nih.gov/pubmed/27472540en_GB
dc.rights.embargoreasonPublisher policyen_GB
dc.rightsThis is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.en_GB
dc.subjectComplex networksen_GB
dc.subjectPre-surgical evaluationen_GB
dc.subjectQuantitative EEGen_GB
dc.subjectSeizure dynamicsen_GB
dc.subjectSymbolic analysisen_GB
dc.titleIctal time-irreversible intracranial EEG signals as markers of the epileptogenic zone.en_GB
dc.typeArticleen_GB
dc.identifier.issn1388-2457
dc.identifier.journalClinical Neurophysiologyen_GB


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