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

• Published in: bioRxiv
• Main Authors: Kumral, Deniz, Sansal, Firat, Cesnaite, Elena, Mahjoory, Keyvan, Al, Esra, Gaebler, Michael, Nikulin, Vadim V, Villringer, Arno
• Format: Paper
• Language: English
• Published: Cold Spring Harbor Cold Spring Harbor Laboratory Press 23.08.2019; Cold Spring Harbor Laboratory
• Edition: 1.2
• Subjects: Age; Age differences; Aging; Brain; Brain mapping; EEG; Functional magnetic resonance imaging; Neuroimaging; Neuroscience; Oscillations; Sensorimotor system; Sex differences; fMRI; resting state; EEG; sex; brain signal variability; BOLD; aging; default mode network
• ISSN: 2692-8205; 2692-8205
• DOI: 10.1101/646273

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 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. Footnotes * http://fcon_1000.projects.nitrc.org/indi/retro/MPI_LEMON.html * https://doi.org/10.18112/OPENNEURO.DS000221.V2