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Discovery of key whole-brain transitions and dynamics during human wakefulness and non-REM sleep

Author

Listed:
  • A. B. A. Stevner

    (University of Oxford, Warneford Hospital
    Aarhus University
    Aarhus University)

  • D. Vidaurre

    (University of Oxford, Warneford Hospital)

  • J. Cabral

    (University of Oxford, Warneford Hospital
    University of Minho)

  • K. Rapuano

    (Dartmouth College)

  • S. F. V. Nielsen

    (Technical University of Denmark)

  • E. Tagliazucchi

    (Netherlands Institute for Neuroscience
    Christian-Alrbrechts-Universität
    Goethe University)

  • H. Laufs

    (Christian-Alrbrechts-Universität
    Goethe University)

  • P. Vuust

    (Aarhus University)

  • G. Deco

    (Universitat Pompeu Fabra
    Passeig Lluís Companys 23
    Max Planck Institute for Human Cognitive and Brain Sciences
    Monash University, Melbourne)

  • M. W. Woolrich

    (University of Oxford, Warneford Hospital)

  • E. Someren

    (Netherlands Institute for Neuroscience
    VU University and Medical Center)

  • M. L. Kringelbach

    (University of Oxford, Warneford Hospital
    Aarhus University
    Aarhus University
    University of Minho)

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.

Suggested Citation

  • A. B. A. Stevner & D. Vidaurre & J. Cabral & K. Rapuano & S. F. V. Nielsen & E. Tagliazucchi & H. Laufs & P. Vuust & G. Deco & M. W. Woolrich & E. Someren & M. L. Kringelbach, 2019. "Discovery of key whole-brain transitions and dynamics during human wakefulness and non-REM sleep," Nature Communications, Nature, vol. 10(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-08934-3
    DOI: 10.1038/s41467-019-08934-3
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    Cited by:

    1. Xiao-yu Sun & Bin Ye, 2023. "The functional differentiation of brain–computer interfaces (BCIs) and its ethical implications," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-9, December.

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