Unifying turbulent dynamics framework distinguishes different brain states

  • Significant advances have been made by identifying the levels of synchrony of the underlying dynamics of a given brain state. This research has demonstrated that non-conscious dynamics tend to be more synchronous than in conscious states, which are more asynchronous. Here we go beyond this dichotomy to demonstrate that different brain states are underpinned by dissociable spatiotemporal dynamics. We investigated human neuroimaging data from different brain states (resting state, meditation, deep sleep and disorders of consciousness after coma). The model-free approach was based on Kuramoto’s turbulence framework using coupled oscillators. This was extended by a measure of the information cascade across spatial scales. Complementarily, the model-based approach used exhaustive in silico perturbations of whole-brain models fitted to these measures. This allowed studying of the information encoding capabilities in given brain states. Overall, this framework demonstrates that elements from turbulence theory provide excellent tools for describing and differentiating between brain states.

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Author:Anira EscrichsORCiD, Yonatan Sanz PerlORCiD, Carme UribeORCiD, Estela CàmaraORCiDGND, Basak Türker, Nadya PyatigorskayaORCiD, Ane López-GonzálezORCiD, Carla PallaviciniORCiD, Rajanikant PandaORCiD, Jitka AnnenORCiD, Olivia GrosseriesORCiDGND, Steven LaureysGND, Lionel NaccacheORCiDGND, Jacobo D. SittORCiD, Helmut LaufsORCiDGND, Enzo TagliazucchiORCiDGND, Morten L. KringelbachORCiDGND, Gustavo DecoORCiDGND
URN:urn:nbn:de:hebis:30:3-737860
DOI:https://doi.org/10.1038/s42003-022-03576-6
ISSN:2399-3642
Parent Title (German):Communications Biology
Publisher:Springer Nature
Place of publication:London
Document Type:Article
Language:English
Date of Publication (online):2022/06/29
Date of first Publication:2022/06/29
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2023/05/03
Volume:5
Issue:Article number 638
Page Number:13
HeBIS-PPN:508513332
Institutes:Medizin
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Sammlungen:Universitätspublikationen
Licence (German):License LogoCreative Commons - Namensnennung 4.0