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Circadian dynamics of high frequency oscillations in patients with epilepsy
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SYSNO ASEP 0472661 Druh ASEP C - Konferenční příspěvek (mezinárodní konf.) Zařazení RIV D - Článek ve sborníku Název Circadian dynamics of high frequency oscillations in patients with epilepsy Tvůrce(i) Balach, J. (CZ)
Ježdík, P. (CZ)
Janča, R. (CZ)
Čmejla, R. (CZ)
Kršek, P. (CZ)
Marusič, P. (CZ)
Jiruška, Přemysl (FGU-C) RID, ORCID, SAIZdroj.dok. Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS. - Rome : SciTePress, 2016 - ISBN 978-989758170-0 Rozsah stran s. 284-289 Poč.str. 6 s. Forma vydání Online - E Akce BIOSIGNALS 2016 - International Conference on Bio-Inspired Systems and Signal Processing /9./,Part of 9th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2016 Datum konání 21.02.2016 - 23.02.2016 Místo konání Rome Země IT - Itálie Typ akce WRD Jazyk dok. eng - angličtina Země vyd. IT - Itálie Klíč. slova circadian rhythms ; epilepsy ; high-frequency oscillations ; intracerebral EEG ; seizure onset zone Vědní obor RIV FH - Neurologie, neurochirurgie, neurovědy CEP NT14489 GA MZd - Ministerstvo zdravotnictví GA14-02634S GA ČR - Grantová agentura ČR NV15-29835A GA MZd - Ministerstvo zdravotnictví Institucionální podpora FGU-C - RVO:67985823 EID SCOPUS 84969180504 DOI 10.5220/0005827602840289 Anotace High frequency oscillations (HFOs) are novel biomarker of epileptogenic tissue. HFOs are currently used to localize the seizure generating areas of the brain, delineate the resection and to monitor the disease activity. It is well established that spatiotemporal dynamics of HFOs can be modified by sleep-wake cycle. In this study we aimed to evaluate in detail circadian and ultradian changes in HFO dynamics using techniques of automatic HFO detection. For this purpose we have developed and implemented novel algorithm to automatic detection and analysis of HFOs in long-term intracranial recordings of six patients. In 5/6 patients HFO rates significantly increased during NREM sleep. The largest NREM related increase in HFO rates were observed in brain areas which spatially overlapped with seizure onset zone. Analysis of long-term recording revealed existence of ultradian changes in HFO dynamics. This study demonstrated reliability of automatic HFO detection in the analysis of long-term intracranial recordings in humans. Obtained results can foster practical implementation of automatic HFO detecting algorithms into presurgical examination, dramatically decrease human labour and increase the information yield of HFOs. Pracoviště Fyziologický ústav Kontakt Lucie Trajhanová, lucie.trajhanova@fgu.cas.cz, Tel.: 241 062 400 Rok sběru 2017
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