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  Decoding brain states on the intrinsic manifold of human brain dynamics across wakefulness and sleep

Rué-Queralt, J., Stevner, A., Tagliazucchi, E., Laufs, H., Kringelbach, M. L., Deco, G., et al. (2021). Decoding brain states on the intrinsic manifold of human brain dynamics across wakefulness and sleep. Communications Biology, 4(1): 854. doi:10.1038/s42003-021-02369-7.

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 Creators:
Rué-Queralt, Joan1, Author
Stevner, Angus2, 3, Author
Tagliazucchi, Enzo4, Author
Laufs, Helmut5, 6, Author
Kringelbach, Morten L.2, 3, Author
Deco, Gustavo1, 7, 8, 9, Author           
Atasoy, Selen2, 3, Author
Affiliations:
1Center for Brain and Cognition, University Pompeu Fabra, Barcelona, Spain, ou_persistent22              
2Centre for Eudaimonia and Human Flourishing, University of Oxford, United Kingdom, ou_persistent22              
3Center for Music in the Brain, Aarhus University, Denmark, ou_persistent22              
4Department of Physics, University of Buenos Aires, Argentina, ou_persistent22              
5Department of Neurology, Goethe University, Frankfurt, Germany, ou_persistent22              
6Department of Neurology, University Hospital of Schleswig-Holstein, Kiel, Germany, ou_persistent22              
7Catalan Institution for Research and Advanced Studies (ICREA), University Pompeu Fabra, Barcelona, Spain, ou_persistent22              
8Department Neuropsychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634551              
9School of Psychological Sciences, Monash University, Melbourne, Australia, ou_persistent22              

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Free keywords: Consciousness; Dynamical systems; Network models
 Abstract: Current state-of-the-art functional magnetic resonance imaging (fMRI) offers remarkable imaging quality and resolution, yet, the intrinsic dimensionality of brain dynamics in different states (wakefulness, light and deep sleep) remains unknown. Here we present a method to reveal the low dimensional intrinsic manifold underlying human brain dynamics, which is invariant of the high dimensional spatio-temporal representation of the neuroimaging technology. By applying this intrinsic manifold framework to fMRI data acquired in wakefulness and sleep, we reveal the nonlinear differences between wakefulness and three different sleep stages, and successfully decode these different brain states with a mean accuracy across participants of 96%. Remarkably, a further group analysis shows that the intrinsic manifolds of all participants share a common topology. Overall, our results reveal the intrinsic manifold underlying the spatiotemporal dynamics of brain activity and demonstrate how this manifold enables the decoding of different brain states such as wakefulness and various sleep stages.

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Language(s): eng - English
 Dates: 2020-06-262021-06-182021-07-09
 Publication Status: Published online
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1038/s42003-021-02369-7
PMID: 34244598
PMC: PMC8270946
 Degree: -

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Title: Communications Biology
Source Genre: Journal
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Publ. Info: London : Springer Nature
Pages: - Volume / Issue: 4 (1) Sequence Number: 854 Start / End Page: - Identifier: ISSN: 2399-3642
CoNE: https://pure.mpg.de/cone/journals/resource/2399-3642