Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/26505
DC FieldValueLanguage
dc.contributor.authorDragana Manasovaen_US
dc.contributor.authorTomislav Stankovskien_US
dc.date.accessioned2023-05-18T08:19:04Z-
dc.date.available2023-05-18T08:19:04Z-
dc.date.issued2023-05-01-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/26505-
dc.description.abstractThe human brain presents a heavily connected complex system. From a relatively fixed anatomy, it can enable a vast repertoire of functions. One important brain function is the process of natural sleep, which alters consciousness and voluntary muscle activity. On neural level, these alterations are accompanied by changes of the brain connectivity. In order to reveal the changes of connectivity associated with sleep, we present a methodological framework for reconstruction and assessment of functional interaction mechanisms. By analyzing EEG (electroencephalogram) recordings from human whole night sleep, first, we applied a time-frequency wavelet transform to study the existence and strength of brainwave oscillations. Then we applied a dynamical Bayesian inference on the phase dynamics in the presence of noise. With this method we reconstructed the cross-frequency coupling functions, which revealed the mechanism of how the interactions occur and manifest. We focus our analysis on the delta-alpha coupling function and observe how this cross-frequency coupling changes during the different sleep stages. The results demonstrated that the delta-alpha coupling function was increasing gradually from Awake to NREM3 (non-rapid eye movement), but only during NREM2 and NREM3 deep sleep it was significant in respect of surrogate data testing. The analysis on the spatially distributed connections showed that this significance is strong only for within the single electrode region and in the front-to-back direction. The presented methodological framework is for the whole-night sleep recordings, but it also carries general implications for other global neural states.en_US
dc.language.isoenen_US
dc.relation.ispartofNeuroscienceen_US
dc.subjectCoupling functionen_US
dc.subjectCross-frequency couplingen_US
dc.subjectBayesian inferenceen_US
dc.subjectEEGen_US
dc.subjectsleepen_US
dc.titleNeural Cross-Frequency Coupling Functions in Sleepen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.1016/j.neuroscience.2023.05.016-
item.grantfulltextopen-
item.fulltextWith Fulltext-
crisitem.author.deptFaculty of Medicine-
Appears in Collections:Faculty of Medicine: Journal Articles
Files in This Item:
File Description SizeFormat 
NCFS_Rev16_preprint.pdf3.34 MBAdobe PDFView/Open
Show simple item record

Page view(s)

52
checked on May 17, 2024

Download(s)

51
checked on May 17, 2024

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.