English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
Add to Basket
  DetailsSummary

Released
Journal Article

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

MPS-Authors
/persons/resource/persons225365

Kumral,  Deniz
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
MindBrainBody Institute, Berlin School of Mind and Brain, Humboldt University Berlin, Germany;

/persons/resource/persons228111

Sansal,  Firat
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
International Graduate Program Medical Neurosciences, Charité University Medicine Berlin, Germany;

/persons/resource/persons203573

Cesnaite,  Elena
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

/persons/resource/persons225368

Mahjoory,  Keyvan
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Institute for Biomagnetism and Biosignal Analysis, Münster University, Germany;

/persons/resource/persons222350

Al,  Esra
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
MindBrainBody Institute, Berlin School of Mind and Brain, Humboldt University Berlin, Germany;

/persons/resource/persons134458

Gaebler,  Michael
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
MindBrainBody Institute, Berlin School of Mind and Brain, Humboldt University Berlin, Germany;

/persons/resource/persons201758

Nikulin,  Vadim V.
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Neurophysics Group, Department of Neurology, Charité University Medicine Berlin, Germany;
Centre for Cognition and Decision Making, National Research University Higher School of Economics, Moscow, Russia;

/persons/resource/persons20065

Villringer,  Arno
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
MindBrainBody Institute, Berlin School of Mind and Brain, Humboldt University Berlin, Germany;
Center for Stroke Research, Charité University Medicine Berlin, Germany;
Clinic for Cognitive Neurology, University of Leipzig, Germany;

External Resource

https://www.biorxiv.org/content/10.1101/646273v2
(Preprint)

Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)

Kumral_Variability_2019
(Preprint), 42MB

Kumral_2020.pdf
(Publisher version), 2MB

Supplementary Material (public)
There is no public supplementary material available
Citation

Kumral, D., Sansal, F., Cesnaite, E., Mahjoory, K., Al, E., Gaebler, M., et al. (2020). BOLD and EEG signal variability at rest differently relate to aging in the human brain. NeuroImage, 207: 116373. doi:10.1016/j.neuroimage.2019.116373.


Cite as: https://hdl.handle.net/21.11116/0000-0004-C7F1-B
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.