dc.contributor.author | Schindler, K | |
dc.contributor.author | Rummel, C | |
dc.contributor.author | Andrzejak, RG | |
dc.contributor.author | Goodfellow, M | |
dc.contributor.author | Zubler, F | |
dc.contributor.author | Abela, E | |
dc.contributor.author | Wiest, R | |
dc.contributor.author | Pollo, C | |
dc.contributor.author | Steimer, A | |
dc.contributor.author | Gast, H | |
dc.date.accessioned | 2016-08-02T08:17:46Z | |
dc.date.issued | 2016-07-12 | |
dc.description.abstract | OBJECTIVE: 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.sponsorship | K.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.citation | Clinical Neurophysiology, 2016, Vol. 127, pp. 3051 Issue 9, pp. 3051- 3058 | en_GB |
dc.identifier.doi | 10.1016/j.clinph.2016.07.001 | |
dc.identifier.uri | http://hdl.handle.net/10871/22828 | |
dc.language.iso | en | en_GB |
dc.publisher | Elsevier | en_GB |
dc.relation.url | http://www.ncbi.nlm.nih.gov/pubmed/27472540 | en_GB |
dc.rights.embargoreason | Publisher policy | en_GB |
dc.rights | This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record. | en_GB |
dc.subject | Complex networks | en_GB |
dc.subject | Pre-surgical evaluation | en_GB |
dc.subject | Quantitative EEG | en_GB |
dc.subject | Seizure dynamics | en_GB |
dc.subject | Symbolic analysis | en_GB |
dc.title | Ictal time-irreversible intracranial EEG signals as markers of the epileptogenic zone. | en_GB |
dc.type | Article | en_GB |
dc.identifier.issn | 1388-2457 | |
dc.identifier.journal | Clinical Neurophysiology | en_GB |