Slow EEG Pattern Predicts Reduced Intrinsic Functional Connectivity in the Default Mode Network: An Inter-Subject Analysis
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F10%3A00345971" target="_blank" >RIV/67985807:_____/10:00345971 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Slow EEG Pattern Predicts Reduced Intrinsic Functional Connectivity in the Default Mode Network: An Inter-Subject Analysis
Original language description
The study of spontaneous brain activity is gaining on importance in neuroscience. Resting state networks (RSN) are defined by synchronisation of blood oxygenation level dependent (BOLD) signal. Simultaneous EEG/fMRI has been previously used to study theneurophysiological signature of RSN by comparing EEG power with BOLD amplitude. We hypothesised that band-limited EEG power may be directly related to network specific functional connectivity (FC) of BOLD signal time courses, focusing on the default modenetwork (DMN). Analysing combined EEG/fMRI resting state data of 20 subjects, we showed network and frequency specific relation between RSN FC and EEG band-powers explaining 70% of DMN-FC variance, with partial correlations of DMN-FC to delta and beta power. The identified EEG pattern has been previously associated with increased alertness. The study opens a new perspective to EEG/fMRI correlation. Direct evidence was provided for a distinct neurophysiological correlate of DMN-FC.
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
FH - Neurology, neuro-surgery, nuero-sciences
OECD FORD branch
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Result continuities
Project
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Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Neuroimage
ISSN
1053-8119
e-ISSN
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Volume of the periodical
53
Issue of the periodical within the volume
1
Country of publishing house
US - UNITED STATES
Number of pages
8
Pages from-to
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UT code for WoS article
000280818900026
EID of the result in the Scopus database
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