4.7 Article

The coupling of BOLD signal variability and degree centrality underlies cognitive functions and psychiatric diseases

Journal

NEUROIMAGE
Volume 237, Issue -, Pages -

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2021.118187

Keywords

Resting-state fMRI; Mean-scaled fractional BOLD signal variability; Degree centrality; Cognitive function; Disease vulnerability

Funding

  1. National Natural Science Foundation of China [31730038]
  2. NSFC [31861143040]
  3. Israel Science Foundation (ISF) [31861143040]
  4. Sino-German Collaborative Research Project Crossmodal Learning [NSFC 62061136001/DFG TRR169]
  5. Guangdong Pearl River Talents Plan Innovative and Entrepreneurial Team grant [2016ZT06S220]
  6. 16 NIH Institutes and Centers [1U54MH091657]
  7. McDonnell Center for Systems Neuroscience at Washington University [1U54MH091657]

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The study found that the mean-scaled fractional standard deviation of the BOLD signal (mfSD BOLD) demonstrated high reliability in test-retest, cross-site comparisons, and was less affected by head motion compared to existing variability measures. There was a strong reproducible coupling between mfSD BOLD and functional integration, as well as correlations with cognitive function and cerebral blood flow. This suggests that BOLD signal variability may serve as a meaningful index of local function underlying functional integration in the human brain.
Brain signal variability has been consistently linked to functional integration; however, whether this coupling is associated with cognitive functions and/or psychiatric diseases has not been clarified. Using multiple multimodality datasets, including resting-state functional magnetic resonance imaging (rsfMRI) data from the Human Connectome Project (HCP: N = 927) and a Beijing sample ( N = 416) and cerebral blood flow (CBF) and rsfMRI data from a Hangzhou sample ( N = 29), we found that, compared with the existing variability measure (i.e., SD BOLD ), the mean-scaled (standardized) fractional standard deviation of the BOLD signal (mfSD BOLD ) maintained very high test-retest reliability, showed greater cross-site reliability and was less affected by head motion. We also found strong reproducible couplings between the mfSD BOLD and functional integration measured by the degree centrality (DC), both cross-voxel and cross-subject, which were robust to scanning and preprocessing parameters. Moreover, both mfSD BOLD and DC were correlated with CBF, suggesting a common physiological basis for both measures. Critically, the degree of coupling between mfSD BOLD and long-range DC was positively correlated with individuals' cognitive total composite scores. Brain regions with greater mismatches between mfSD BOLD and longrange DC were more vulnerable to brain diseases. Our results suggest that BOLD signal variability could serve as a meaningful index of local function that underlies functional integration in the human brain and that a strong coupling between BOLD signal variability and functional integration may serve as a hallmark of balanced brain networks that are associated with optimal brain functions.

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