Metabolic and Hemodynamic Resting-State Connectivity of the Human Brain: A High-Temporal Resolution Simultaneous BOLD-fMRI and FDG-fPET Multimodality Study

• Published in: Cerebral cortex (New York, N.Y. 1991) Vol. 31; no. 6; pp. 2855 - 2867
• Main Authors: Jamadar, Sharna D, Ward, Phillip G D, Liang, Emma X, Orchard, Edwina R, Chen, Zhaolin, Egan, Gary F
• Format: Journal Article
• Language: English
• Published: United States 10.05.2021
• Subjects: Adolescent; Brain - diagnostic imaging; Brain - metabolism; Female; Fluorodeoxyglucose F18 - metabolism; Glucose - metabolism; Hemodynamics - physiology; Humans; Magnetic Resonance Imaging - methods; Male; Multimodal Imaging - methods; Nerve Net - diagnostic imaging; Nerve Net - metabolism; Positron-Emission Tomography - methods; Rest - physiology; Young Adult; FDG-PET; simultaneous MR-PET; functional connectivity; fPET; BOLD-fMRI; metabolic connectivity; resting-state
• ISSN: 1047-3211; 1460-2199; 1460-2199
• DOI: 10.1093/cercor/bhaa393

Simultaneous [18F]-fluorodeoxyglucose positron emission tomography functional magnetic resonance imaging (FDG-PET/fMRI) provides the capacity to image 2 sources of energetic dynamics in the brain—glucose metabolism and the hemodynamic response. fMRI connectivity has been enormously useful for characterizing interactions between distributed brain networks in humans. Metabolic connectivity based on static FDG-PET has been proposed as a biomarker for neurological disease, but FDG-sPET cannot be used to estimate subject-level measures of “connectivity,” only across-subject “covariance.” Here, we applied high-temporal resolution constant infusion functional positron emission tomography (fPET) to measure subject-level metabolic connectivity simultaneously with fMRI connectivity. fPET metabolic connectivity was characterized by frontoparietal connectivity within and between hemispheres. fPET metabolic connectivity showed moderate similarity with fMRI primarily in superior cortex and frontoparietal regions. Significantly, fPET metabolic connectivity showed little similarity with FDG-sPET metabolic covariance, indicating that metabolic brain connectivity is a nonergodic process whereby individual brain connectivity cannot be inferred from group-level metabolic covariance. Our results highlight the complementary strengths of fPET and fMRI in measuring the intrinsic connectivity of the brain and open up the opportunity for novel fundamental studies of human brain connectivity as well as multimodality biomarkers of neurological diseases.