Abstract：
:The modern understanding of sleep is based on the classification of sleep into stages defined by their electroencephalography (EEG) signatures, but the underlying brain dynamics remain unclear. Here we aimed to move significantly beyond the current state-of-the-art description of sleep, and in particular to characterise the spatiotemporal complexity of whole-brain networks and state transitions during sleep. In order to obtain the most unbiased estimate of how whole-brain network states evolve through the human sleep cycle, we used a Markovian data-driven analysis of continuous neuroimaging data from 57 healthy participants falling asleep during simultaneous functional magnetic resonance imaging (fMRI) and EEG. This Hidden Markov Model (HMM) facilitated discovery of the dynamic choreography between different whole-brain networks across the wake-non-REM sleep cycle. Notably, our results reveal key trajectories to switch within and between EEG-based sleep stages, while highlighting the heterogeneities of stage N1 sleep and wakefulness before and after sleep.
journal_name
Nat Communjournal_title
Nature communicationsauthors
Stevner ABA,Vidaurre D,Cabral J,Rapuano K,Nielsen SFV,Tagliazucchi E,Laufs H,Vuust P,Deco G,Woolrich MW,Van Someren E,Kringelbach MLdoi
10.1038/s41467-019-08934-3subject
Has Abstractpub_date
2019-03-04 00:00:00pages
1035issue
1issn
2041-1723pii
10.1038/s41467-019-08934-3journal_volume
10pub_type
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