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

• Published in: NeuroImage (Orlando, Fla.) Vol. 237; p. 118187
• Main Authors: Sheng, Jintao, Zhang, Liang, Feng, Junjiao, Liu, Jing, Li, Anqi, Chen, Wei, Shen, Yuedi, Wang, Jinhui, He, Yong, Xue, Gui
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Inc 15.08.2021; Elsevier Limited; Elsevier
• Subjects: Age; Alzheimer's disease; Blood flow; Brain; Brain mapping; Cerebral blood flow; Cognitive ability; Cognitive function; Datasets; Degree centrality; Disease vulnerability; Functional magnetic resonance imaging; Integration; Mean-scaled fractional BOLD signal variability; Mental disorders; Metabolism; Neuroimaging; Resting-state fMRI; Standard deviation; Beijing China; China; Resting-state fMRI; Degree centrality; Cognitive function; Mean-scaled fractional BOLD signal variability; Disease vulnerability
• ISSN: 1053-8119; 1095-9572; 1095-9572
• DOI: 10.1016/j.neuroimage.2021.118187

•The mean-scaled fractional BOLD signal variability (mfSDBOLD) was reliable.•The degree centrality (DC) and mfSDBOLD were correlated with cerebral blood flow.•The mfSDBOLD and DC were strongly coupled both across voxels and subjects.•The strength of DC-mfSDBOLD coupling predicted cognitive performance.•Regions with greater DC-mfSDBOLD mismatch were more vulnerable to brain diseases. 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., SDBOLD), the mean-scaled (standardized) fractional standard deviation of the BOLD signal (mfSDBOLD) 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 mfSDBOLD 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 mfSDBOLD and DC were correlated with CBF, suggesting a common physiological basis for both measures. Critically, the degree of coupling between mfSDBOLD and long-range DC was positively correlated with individuals’ cognitive total composite scores. Brain regions with greater mismatches between mfSDBOLD and long-range 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.