Suchergebnisse

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. ; Spanish Research Project PSI2016-75688-P (AEI/FEDER) and by the European Union's Horizon 2020 research and innovation programme under Grant agreement no. 720270 (HBP SGA1). M.L.K. was supported by the ERC Consolidator Grant CAREGIVING (615539) and the Center for Music in the Brain, funded by the Danish National Research Foundation Grant DNRF117. J.C. was supported under the project ...