Resting cerebral oxygen metabolism exhibits archetypal network features

Authors

Nicholas A. Hubbard, Massachusetts Institute of TechnologyFollow
Monroe P. Turner, University of Texas at Dallas
Kevin R. Sitek, Massachusetts Institute of Technology
Kathryn L. West, University of Texas at Dallas
Jakub R. Kaczmarzyk, Massachusetts Institute of Technology
Lyndahl Himes, University of Texas at Dallas
Binu P. Thomas, University of Texas at Dallas
Hanzhang Lu, John's Hopkins University School of Medicine
Bart Rypma, University of Texas at Dallas

ORCID IDs

Nicholas A. Hubbard

Document Type

Article

Date of this Version

1-12-2021

Citation

Hubbard NA, Turner MP, Sitek KR, et al. Resting cerebral oxygen metabolism exhibits archetypal network features. Hum Brain Mapp. 2021;42:1952–1968. https://doi.org/10.1002/hbm.25352

Comments

OPEN ACCESS

Abstract

Standard magnetic resonance imaging approaches offer high-resolution but indirect measures of neural activity, limiting understanding of the physiological processes associated with imaging findings. Here, we used calibrated functional magnetic resonance imaging during the resting state to recover low-frequency fluctuations of the cerebral metabolic rate of oxygen (CMRO2). We tested whether functional connections derived from these fluctuations exhibited organization properties similar to those established by previous standard functional and anatomical connectivity studies. Seventeen participants underwent 20 min of resting imaging during dual-echo, pseudocontinuous arterial spin labeling, and blood-oxygen-level dependent (BOLD) signal acquisition. Participants also underwent a 10 min normocapnic and hypercapnic procedure. Brain-wide, CMRO2 low-frequency fluctuations were subjected to graph-based and voxel-wise functional connectivity analyses. Results demonstrated that connections derived from resting CMRO2 fluctuations exhibited complex, small-world topological properties (i.e., high integration and segregation, cost efficiency) consistent with those observed in previous studies using functional and anatomical connectivity approaches. Voxel-wise CMRO2 connectivity also exhibited spatial patterns consistent with four targeted resting-state subnetworks: two association (i.e., frontoparietal and default mode) and two perceptual (i.e., auditory and occipital-visual). These are the first findings to support the use of calibration-derived CMRO2 low-frequency fluctuations for detecting brain-wide organizational properties typical of healthy participants. We discuss interpretations, advantages, and challenges in using calibration-derived oxygen metabolism signals for examining the intrinsic organization of the human brain.