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Power spectra reveal distinct BOLD resting-state time courses in white matter.
- Source :
-
Proceedings of the National Academy of Sciences of the United States of America [Proc Natl Acad Sci U S A] 2021 Nov 02; Vol. 118 (44). - Publication Year :
- 2021
-
Abstract
- Accurate characterization of the time courses of blood-oxygen-level-dependent (BOLD) signal changes is crucial for the analysis and interpretation of functional MRI data. While several studies have shown that white matter (WM) exhibits distinct BOLD responses evoked by tasks, there have been no comprehensive investigations into the time courses of spontaneous signal fluctuations in WM. We measured the power spectra of the resting-state time courses in a set of regions within WM identified as showing synchronous signals using independent components analysis. In each component, a clear separation between voxels into two categories was evident, based on their power spectra: one group exhibited a single peak, and the other had an additional peak at a higher frequency. Their groupings are location specific, and their distributions reflect unique neurovascular and anatomical configurations. Importantly, the two categories of voxels differed in their engagement in functional integration, revealed by differences in the number of interregional connections based on the two categories separately. Taken together, these findings suggest WM signals are heterogeneous in nature and depend on local structural-vascular-functional associations.<br />Competing Interests: The authors declare no competing interest.
- Subjects :
- Adult
Brain physiology
Brain Mapping methods
Diffusion Tensor Imaging methods
Female
Hemodynamics physiology
Humans
Magnetic Resonance Imaging methods
Male
Neurochemistry methods
Oxygen Saturation physiology
Rest physiology
White Matter diagnostic imaging
White Matter metabolism
Hemodynamic Monitoring methods
White Matter physiology
Subjects
Details
- Language :
- English
- ISSN :
- 1091-6490
- Volume :
- 118
- Issue :
- 44
- Database :
- MEDLINE
- Journal :
- Proceedings of the National Academy of Sciences of the United States of America
- Publication Type :
- Academic Journal
- Accession number :
- 34716261
- Full Text :
- https://doi.org/10.1073/pnas.2103104118