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EEG principal component organization via time-frequency representation

Iordanidou Vasiliki

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URIhttp://purl.tuc.gr/dl/dias/D14CD00C-973D-4557-969D-F6D9D05BBD07-
Identifierhttp://www.library.tuc.gr/artemis/DT2009-0170/DT2009-0170.pdf-
Identifierhttps://doi.org/10.26233/heallink.tuc.12148-
Languageen-
Extent112 pagesen
TitleEEG principal component organization via time-frequency representationen
CreatorIordanidou Vasilikien
CreatorΙορδανιδου Βασιλικηel
Contributor [Thesis Supervisor]Zervakis Michailen
Contributor [Thesis Supervisor]Ζερβακης Μιχαηλel
PublisherTechnical University of Creteen
PublisherΠολυτεχνείο Κρήτηςel
Academic UnitΠολυτεχνείο Κρήτης::Τμήμα Ηλεκτρονικών Μηχανικών και Μηχανικών Υπολογιστώνel
Content SummaryOver the past few years there has been an increased interest in studying the underlying neural mechanism of cognitive brain activity related to memory. In this direction, we study the brain activity based on its independent components instead of the EEG signal itself aiming towards identifying and analyzing induced responses being attributed to oscillatory bursts from local or distant neural assemblies, with variable latency and frequency, in an auditory working memory paradigm. The significance of the components is determined via intertrial coherence measures. The contribution and functional coupling of independent components to evoked and/or induced oscillatory activities is investigated through the concept of the recently introduced partial directed coherence method, which can also reveal the direction of the statistically significant relationships. The results on real data from an oddball experiment are in accordance with previous psychophysiology studies suggesting increased phase locked activity most prominently in the delta/ theta band, while alpha is also apparent in measures of non phase-locked activity. Dynamic synchronization is inferred between the alpha and delta bands, whereas some influence of the theta band is also detected. This study indicates that functional connectivity during cognitive processes may be successfully assessed using spectral power measures applied on independent components, which reflect distinct spatial patterns of activity.el
Type of ItemΔιπλωματική Εργασίαel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2014-03-24-
Date of Publication2009-
SubjectΔΙΠ2217el
Bibliographic CitationVasiliki Iordanidou, "EEG principal component organization via time-frequency representation", Diploma Work, Department of Electrical and Computer Engineering, Technical University of Crete, Chania, Greece, 2009el

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