Independent component analysis for source localization of EEG sleep spindle components

dc.contributor.author	Βεντούρας, Ερρίκος Μ.	el
dc.contributor.author	Κτώνας, Περικλής Υ.	el
dc.contributor.author	Τσέκου, Χαρά	el
dc.contributor.author	Παπαρρηγόπουλος, Θωμάς	el
dc.contributor.author	Καλατζής, Ιωάννης	el
dc.date.accessioned	2015-02-06T10:00:51Z
dc.date.available	2015-02-06T10:00:51Z
dc.date.issued	2015-02-06
dc.identifier.uri	http://hdl.handle.net/11400/5728
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.source	http://www.hindawi.com/	en
dc.subject	Sleep spindles
dc.subject	Electroencephalography
dc.subject	Άτρακτοι ύπνου
dc.subject	Ηλεκτροεγκεφαλογράφημα
dc.title	Independent component analysis for source localization of EEG sleep spindle components	en
heal.type	journalArticle
heal.generalDescription	Open access journal	en
heal.classification	Medicine
heal.classification	Medical technology
heal.classification	Ιατρική
heal.classification	Ιατρικά όργανα και εξοπλισμός
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh00006614
heal.classificationURI	http://skos.um.es/unescothes/C02465
heal.classificationURI	N/A-Ιατρική
heal.classificationURI	N/A-Ιατρικά όργανα και εξοπλισμός
heal.keywordURI	http://lod.nal.usda.gov/19230
heal.contributorName	Σολδάτος, Κωνσταντίνος Ρ.	el
heal.identifier.secondary	doi:10.1155/2010/329436
heal.language	en
heal.access	free
heal.recordProvider	Τ.Ε.Ι. Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Βιοϊατρικής Τεχνολογίας Τ.Ε.	el
heal.publicationDate	2010
heal.bibliographicCitation	Vnetouras, E., Ktonas. P., Tsekou, H., Paparrigopoulos, T., Kalatzis, I., et al. (2010). Independent component analysis for source localization of EEG sleep spindle components. Computational Intelligence and Neuroscience. vol. 2010. Hindawi Publishing Corporation. Available from: http://www.hindawi.com	en
heal.abstract	Sleep spindles are bursts of sleep electroencephalogram (EEG) quasirhythmic activity within the frequency band of 11–16 Hz, characterized by progressively increasing, then gradually decreasing amplitude. The purpose of the present study was to process sleep spindles with Independent Component Analysis (ICA) in order to investigate the possibility of extracting, through visual analysis of the spindle EEG and visual selection of Independent Components (ICs), spindle “components” (SCs) corresponding to separate EEG activity patterns during a spindle, and to investigate the intracranial current sources underlying these SCs. Current source analysis using Low-Resolution Brain Electromagnetic Tomography (LORETA) was applied to the original and the ICA-reconstructed EEGs. Results indicated that SCs can be extracted by reconstructing the EEG through back-projection of separate groups of ICs, based on a temporal and spectral analysis of ICs. The intracranial current sources related to the SCs were found to be spatially stable during the time evolution of the sleep spindles.	en
heal.publisher	Hindawi Publishing Corporation	en
heal.journalName	Computational Intelligence and Neuroscience	en
heal.journalType	peer-reviewed
heal.fullTextAvailability	true