PT  - JOURNAL ARTICLE
AU  - D. Kumral
AU  - F. Şansal
AU  - E. Cesnaite
AU  - K. Mahjoory
AU  - E. Al
AU  - M. Gaebler
AU  - V. V. Nikulin
AU  - A. Villringer
TI  - BOLD and EEG Signal Variability at Rest Differently Relate to Aging in the Human Brain
AID  - 10.1101/646273
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 646273
4099  - http://biorxiv.org/content/early/2019/05/23/646273.short
4100  - http://biorxiv.org/content/early/2019/05/23/646273.full
AB  - 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 fronto-temporal and sensorimotor brain regions. There were significant sex differences in BOLD and EEG signal variability in various brain regions, but no significant interactions between age and sex were observed. Further, both univariate and multivariate correlation analyses revealed no significant associations between these two 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.