Number of the records: 1  

Infraslow Electroencephalographic and Dynamic Resting State Network Activity

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    SYSNO ASEP0545853
    Document TypeJ - Journal Article
    R&D Document TypeThe record was not marked in the RIV
    Subsidiary JČlánek ve WOS
    TitleInfraslow Electroencephalographic and Dynamic Resting State Network Activity
    Author(s) Grooms, J.K. (US)
    Thompson, G. J. (US)
    Pan, W.J. (US)
    Billings, Jacob (UIVT-O) SAI, ORCID, RID
    Schumacher, E.H. (US)
    Epstein, C.M. (US)
    Keilholz, S. (US)
    Number of authors7
    Source TitleBrain Connectivity - ISSN 2158-0014
    Roč. 7, č. 5 (2017), s. 265-280
    Languageeng - English
    CountryUS - United States
    Keywordsdc-eeg ; functional connectivity ; infraslow ; resting state MRI ; sliding window correlation
    UT WOS000570291900001
    EID SCOPUS85020749124
    DOI10.1089/brain.2017.0492
    AnnotationA number of studies have linked the blood oxygenation level dependent (BOLD) signal to electroencephalographic (EEG) signals in traditional frequency bands (delta, theta, alpha, beta, and gamma), but the relationship between BOLD and its direct frequency correlates in the infraslow band (<1Hz) has been little studied. Previously, work in rodents showed that infraslow local field potentials play a role in functional connectivity, particularly in the dynamic organization of large-scale networks. To examine the relationship between infraslow activity and network dynamics in humans, direct current (DC) EEG and resting state magnetic resonance imaging data were acquired simultaneously. The DC EEG signals were correlated with the BOLD signal in patterns that resembled resting state networks. Subsequent dynamic analysis showed that the correlation between DC EEG and the BOLD signal varied substantially over time, even within individual subjects. The variation in DC EEG appears to reflect the time-varying contribution of different resting state networks. Furthermore, some of the patterns of DC EEG and BOLD correlation are consistent with previous work demonstrating quasiperiodic spatiotemporal patterns of large-scale network activity in resting state. These findings demonstrate that infraslow electrical activity is linked to BOLD fluctuations in humans and that it may provide a basis for large-scale organization comparable to that observed in animal studies.
    WorkplaceInstitute of Computer Science
    ContactTereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
    Year of Publishing2022
Number of the records: 1  

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