BOLD and EEG signal variability at rest differently relate to aging in the human brain
D. Kumral,
F. Şansal,
E. Cesnaite,
K. Mahjoory,
E. Al,
M. Gaebler,
V.V. Nikulin,
A. Villringer
Affiliations
D. Kumral
Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; MindBrainBody Institute at the Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany; Corresponding author. Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstrasse 1A, 04103, Leipzig, Germany.
F. Şansal
International Graduate Program Medical Neurosciences, Charité-Universitätsmedizin, Berlin, Germany; Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
E. Cesnaite
Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
K. Mahjoory
Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Institute for Biomagnetism and Biosignalanalysis, University of Muenster, Muenster, Germany
E. Al
MindBrainBody Institute at the Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany; Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
M. Gaebler
Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; MindBrainBody Institute at the Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
V.V. Nikulin
Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Neurophysics Group, Department of Neurology, Campus Benjamin Franklin, Charité Universitätsmedizin Berlin, Berlin, Germany; Centre for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia
A. Villringer
Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; MindBrainBody Institute at the Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany; Center for Stroke Research Berlin, Charité – Universitätsmedizin Berlin, Berlin, Germany; Department of Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
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.
