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Brain dynamics supported by a hierarchy of complex correlation patterns defining a robust functional architecture

Functional magnetic resonance imaging (fMRI) provides insights into cognitive processes with significant clinical potential. However, delays in brain region communication and dynamic variations are often overlooked in functional network studies. We demonstrate that networks extracted from fMRI cross...

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Main Authors: Varga, Levente (Author) , Moca, Vasile V. (Author) , Molnár, Botond (Author) , Perez-Cervera, Laura (Author) , Selim, Mohamed Kotb (Author) , Díaz-Parra, Antonio (Author) , Moratal, David (Author) , Péntek, Balázs (Author) , Sommer, Wolfgang H. (Author) , Mureșan, Raul C. (Author) , Canals, Santiago (Author) , Ercsey-Ravasz, Maria (Author)
Format: Article (Journal)
Language:English
Published: 21 August 2024
In: Cell systems
Year: 2024, Volume: 15, Issue: 8, Pages: 770-786.e5
ISSN:2405-4720
DOI:10.1016/j.cels.2024.07.003
Online Access:Verlag, kostenfrei, Volltext: https://doi.org/10.1016/j.cels.2024.07.003
Verlag, kostenfrei, Volltext: https://www.sciencedirect.com/science/article/pii/S2405471224002023
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Author Notes:Levente Varga, Vasile V. Moca, Botond Molnár, Laura Perez-Cervera, Mohamed Kotb Selim, Antonio Díaz-Parra, David Moratal, Balázs Péntek, Wolfgang H. Sommer, Raul C. Mureșan, Santiago Canals, and Maria Ercsey-Ravasz

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520 |a Functional magnetic resonance imaging (fMRI) provides insights into cognitive processes with significant clinical potential. However, delays in brain region communication and dynamic variations are often overlooked in functional network studies. We demonstrate that networks extracted from fMRI cross-correlation matrices, considering time lags between signals, show remarkable reliability when focusing on statistical distributions of network properties. This reveals a robust brain functional connectivity pattern, featuring a sparse backbone of strong 0-lag correlations and weaker links capturing coordination at various time delays. This dynamic yet stable network architecture is consistent across rats, marmosets, and humans, as well as in electroencephalogram (EEG) data, indicating potential universality in brain dynamics. Second-order properties of the dynamic functional network reveal a remarkably stable hierarchy of functional correlations in both group-level comparisons and test-retest analyses. Validation using alcohol use disorder fMRI data uncovers broader shifts in network properties than previously reported, demonstrating the potential of this method for identifying disease biomarkers. 
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