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  Unifying turbulent dynamics framework distinguishes different brain states

Escrichs, A., Perl, Y. S., Uribe, C., Camara, E., Türker, B., Pyatigorskaya, N., et al. (2022). Unifying turbulent dynamics framework distinguishes different brain states. Communications Biology, 5(1): 638. doi:10.1038/s42003-022-03576-6.

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 Creators:
Escrichs, Anira1, Author
Perl, Yonatan Sanz1, Author
Uribe, Carme1, Author
Camara, Estela1, Author
Türker, Basak1, Author
Pyatigorskaya, Nadya1, Author
López-González, Ane1, Author
Pallavicini, Carla1, Author
Panda, Rajanikant1, Author
Annen, Jitka1, Author
Gosseries, Olivia1, Author
Laureys, Steven1, Author
Naccache, Lionel1, Author
Sitt, Jacobo D.1, Author
Laufs, Helmut1, Author
Tagliazucchi, Enzo1, Author
Kringelbach, Morten L.1, Author
Deco, Gustavo2, Author           
Affiliations:
1External Organizations, ou_persistent22              
2Department Neuropsychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634551              

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Free keywords: Computational neuroscience; Functional magnetic resonance imaging
 Abstract: 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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Language(s): eng - English
 Dates: 2021-11-152022-06-102022-06-29
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1038/s42003-022-03576-6
PMID: 35768641
PMC: PMC9243255
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Project name : Human Brain Project
Grant ID : 945539
Funding program : -
Funding organization : -
Project name : -
Grant ID : 896354
Funding program : Horizon 2020
Funding organization : European Union

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Title: Communications Biology
Source Genre: Journal
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Publ. Info: London : Springer Nature
Pages: - Volume / Issue: 5 (1) Sequence Number: 638 Start / End Page: - Identifier: ISSN: 2399-3642
CoNE: https://pure.mpg.de/cone/journals/resource/2399-3642