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The Not-So-Global Blood Oxygen Level-Dependent Signal
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SYSNO ASEP 0545817 Druh ASEP J - Článek v odborném periodiku Zařazení RIV Záznam nebyl označen do RIV Poddruh J Článek ve WOS Název The Not-So-Global Blood Oxygen Level-Dependent Signal Tvůrce(i) Billings, Jacob (UIVT-O) SAI, ORCID, RID
Keilholz, S. (US)Celkový počet autorů 2 Zdroj.dok. Brain Connectivity - ISSN 2158-0014
Roč. 8, č. 3 (2018), s. 121-128Jazyk dok. eng - angličtina Země vyd. US - Spojené státy americké Klíč. slova neural activity ; brain networks ; spatiotemporal dynamics ; functional connectivity ; eeg vigilance ; fmri signal ; bold fmri ; fluctuations ; oscillation ; variability ; blood oxygen level-dependent (BOLD) signal ; global BOLD signal ; global signal regression ; noise ; quasi-periodic patterns (QPPs) ; resting-state functional magnetic resonance imaging (rs-fMRI) UT WOS 000440870900001 EID SCOPUS 85046022723 DOI https://doi.org/10.1089/brain.2017.0517 Anotace Global signal regression is a controversial processing step for resting-state functional magnetic resonance imaging, partly because the source of the global blood oxygen level-dependent (BOLD) signal remains unclear. On the one hand, nuisance factors such as motion can readily introduce coherent BOLD changes across the whole brain. On the other hand, the global signal has been linked to neural activity and vigilance levels, suggesting that it contains important neurophysiological information and should not be discarded. Any widespread pattern of coordinated activity is likely to contribute appreciably to the global signal. Such patterns may include large-scale quasiperiodic spatiotemporal patterns, known also to be tied to performance on vigilance tasks. This uncertainty surrounding the separability of the global BOLD signal from concurrent neurological processes motivated an examination of the global BOLD signal's spatial distribution. The results clarify that although the global signal collects information from all tissue classes, a diverse subset of the BOLD signal's independent components contribute the most to the global signal. Further, the timing of each network's contribution to the global signal is not consistent across volunteers, confirming the independence of a constituent process that comprises the global signal. Pracoviště Ústav informatiky Kontakt Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Rok sběru 2022
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