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

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  • Joan Rué-Queralt, Pompeu Fabra University
  • ,
  • Angus Stevner
  • Enzo Tagliazucchi, Universidad de Buenos Aires
  • ,
  • Helmut Laufs, Goethe University Frankfurt, Kiel University
  • ,
  • Morten L. Kringelbach
  • Gustavo Deco, Pompeu Fabra University, ICREA, Max Planck Institute for Human Cognitive and Brain Sciences, Monash University
  • ,
  • Selen Atasoy, University of Oxford

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.

Original languageEnglish
Article number854
JournalCommunications Biology
Volume4
Issue1
DOIs
Publication statusPublished - Dec 2021

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