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  BOLD and EEG signal variability at rest differently relate to aging in the human brain

Kumral, D., Sansal, F., Cesnaite, E., Mahjoory, K., Al, E., Gaebler, M., et al. (2019). BOLD and EEG signal variability at rest differently relate to aging in the human brain. NeuroImage. doi:10.1016/j.neuroimage.2019.116373.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0004-C7F1-B Version Permalink: http://hdl.handle.net/21.11116/0000-0005-42E4-F
Genre: Journal Article

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Kumral_Variability_23_08_EEG_BOLD_clean.pdf (Preprint), 42MB
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 Creators:
Kumral, Deniz1, 2, Author              
Sansal, Firat1, 3, Author              
Cesnaite, Elena1, Author              
Mahjoory, Keyvan1, 4, Author              
Al, Esra1, 2, Author              
Gaebler, Michael1, 2, Author              
Nikulin, Vadim V.1, 5, 6, Author              
Villringer, Arno1, 2, 7, 8, Author              
Affiliations:
1Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634549              
2MindBrainBody Institute, Berlin School of Mind and Brain, Humboldt University Berlin, Germany, ou_persistent22              
3International Graduate Program Medical Neurosciences, Charité University Medicine Berlin, Germany, ou_persistent22              
4Institute for Biomagnetism and Biosignal Analysis, Münster University, Germany, ou_persistent22              
5Neurophysics Group, Department of Neurology, Charité University Medicine Berlin, Germany, ou_persistent22              
6Centre for Cognition and Decision Making, National Research University Higher School of Economics, Moscow, Russia, ou_persistent22              
7Center for Stroke Research, Charité University Medicine Berlin, Germany, ou_persistent22              
8Clinic for Cognitive Neurology, University of Leipzig, Germany, ou_persistent22              

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Free keywords: Brain signal variability; Resting state; BOLD; fMRI; EEG; Aging; Sex; Default mode network
 Abstract: Variability of neural activity is regarded as a crucial feature of healthy brain function, and several neuroimaging approaches have been employed to assess it noninvasively. Studies on the variability of both evoked brain response and spontaneous brain signals have shown remarkable changes with aging but it is unclear if the different measures of brain signal variability – identified with either hemodynamic or electrophysiological methods – reflect the same underlying physiology. In this study, we aimed to explore age differences of spontaneous brain signal variability with two different imaging modalities (EEG, fMRI) in healthy younger (25 ± 3 years, N = 135) and older (67 ± 4 years, N = 54) adults. Consistent with the previous studies, we found lower blood oxygenation level dependent (BOLD) variability in the older subjects as well as less signal variability in the amplitude of low-frequency oscillations (1–12 Hz), measured in source space. These age-related reductions were mostly observed in the areas that overlap with the default mode network. Moreover, age-related increases of variability in the amplitude of beta-band frequency EEG oscillations (15–25 Hz) were seen predominantly in temporal brain regions. There were significant sex differences in EEG signal variability in various brain regions while no significant sex differences were observed in BOLD signal variability. Bivariate and multivariate correlation analyses revealed no significant associations between EEG- and fMRI-based variability measures. In summary, we show that both BOLD and EEG signal variability reflect aging-related processes but are likely to be dominated by different physiological origins, which relate differentially to age and sex.

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Language(s): eng - English
 Dates: 2019-10-172019-08-232019-11-172019-11-20
 Publication Status: Published online
 Pages: -
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 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.1016/j.neuroimage.2019.116373
Other: Epub ahead of print
PMID: 31759114
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Title: NeuroImage
Source Genre: Journal
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Publ. Info: Orlando, FL : Academic Press
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: - Identifier: ISSN: 1053-8119
CoNE: https://pure.mpg.de/cone/journals/resource/954922650166