Key result
Respiratory measures (ENV, RV, RVT) are correlated but can all miss deep breaths, with RVT missing more deep breaths than ENV or RV, and all changing systematically over a 14.4-min scan.
Why the study?
Little is known about how derived respiratory measures compare to each other or how they perform beyond small initial studies when evaluating respiratory contributions to resting-state fMRI signals.
How do different respiratory measures (ENV, RV, RVT) compare in capturing respiratory fluctuations and deep breaths during resting-state fMRI in healthy young adults?
Observational
How do different respiratory measures (ENV, RV, RVT) compare in capturing respiratory fluctuations and deep breaths during resting-state fMRI in healthy young adults?
Different respiratory measures derived from abdominal belts during fMRI have varying sensitivities to deep breaths and change systematically over time, which has important implications for modeling respiratory influences on resting-state functional connectivity.
Abdominal belt respiratory measures miss deep breaths variably and drift over scans; leaves open optimal modeling for fMRI connectivity studies.
Breathing rate and depth influence the concentration of carbon dioxide in the blood, altering cerebral blood flow and thus functional magnetic resonance imaging (fMRI) signals. Such respiratory fluctuations can have substantial influence in studies of fMRI signal covariance in subjects at rest, the so-called "resting state functional connectivity" technique. If respiration is monitored during fMRI scanning, it is typically done using a belt about the subject's abdomen to record abdominal circumference. Several measures have been derived from these belt records, including the windowed envelope of the waveform (ENV), the windowed variance in the waveform (respiration variation, RV), and a measure of the amplitude of each breath divided by the cycle time of the breath (respiration volume per time, RVT). Any attempt to gauge respiratory contributions to fMRI signals requires a respiratory measure, but little is known about how these measures compare to each other, or how they perform beyond the small studies in which they were initially proposed. Here, we examine the properties of these measures in hundreds of healthy young adults scanned for an hour each at rest, a subset of the Human Connectome Project chosen for having high-quality physiological records. We find: 1) ENV, RV, and RVT are all correlated, and ENV and RV are more highly correlated to each other than to RVT; 2) respiratory events like deep breaths exhibit characteristic heart rate elevations, fMRI signal changes, head motions, and image quality abnormalities time-locked to large deflections in the belt traces; 3) all measures can "miss" deep breaths; 4) RVT "misses" deep breaths more than ENV or RV; 5) all respiratory measures change systematically over the course of a 14.4-min scan. We discuss the implications of these findings for the literature and ways to move forward in modeling respiratory influences on fMRI scans.
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Power et al. (2019) conducted an observational in Healthy. Respiratory measures (ENV, RV, RVT) was evaluated on Properties and correlation of respiratory measures (ENV, RV, RVT) and their ability to detect deep breaths. Respiratory measures (ENV, RV, RVT) are correlated but can all miss deep breaths, with RVT missing more deep breaths than ENV or RV, and all changing systematically over a 14.4-min scan.
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