The Influence of Physiological Noise Correction on Test–Retest Reliability of Resting-State Functional Connectivity

Abstract

The utility and success of resting-state functional connectivity MRI (rs-fcMRI) depend critically on the reliability of this technique and the extent to which it accurately reflects neuronal function. One challenge is that rs-fcMRI is influenced by various sources of noise, particularly cardiac-and respiratory-related signal variations. The goal of the current study was to evaluate the impact of various physiological noise correction techniques, specifically those that use independent cardiac and respiration measures, on the test-retest reliability of rs-fcMRI. A group of 25 subjects were each scanned at three time points-two within the same imaging session and another 2-3 months later. Physiological noise corrections accounted for significant variance, particularly in blood vessels, sagittal sinus, cerebrospinal fluid, and gray matter. The fraction of variance explained by each of these corrections was highly similar within subjects between sessions, but variable between subjects. Physiological corrections generally reduced intrasubject (between-session) variability, but also significantly reduced intersubject variability, and thus reduced the test-retest reliability of estimating individual differences in functional connectivity. However, based on known nonneuronal mechanisms by which cardiac pulsation and respiration can lead to MRI signal changes, and the observation that the physiological noise itself is highly stable within individuals, removal of this noise will likely increase the validity of measured connectivity differences. Furthermore, removal of these fluctuations will lead to better estimates of average or group maps of connectivity. It is therefore recommended that studies apply physiological noise corrections but also be mindful of potential correlations with measures of interest.

Characterizing Resting-State Brain Function Using Arterial Spin Labeling

“…However, as a general comment, we note that test-retest reliability alone may not be representative of accuracy in depicting underlying brain processes. As recently found (Birn et al, 2014), physiological noise processes such as respiration and cardiac pulsation can produce highly reproducible but spurious connectivity patterns in resting-state fMRI. Thus, the "true" reliability of CBF-based measurements of resting-state brain function without potential modulation of physiological signals remains to be explored.…”

“…The same principles should apply to ASL CBF data, but as for RETROICOR, RVHRCOR should be applied to tag and control time series independently. However, RVHRCOR has been shown to reduce the test-retest reproducibility of resting-state BOLD connectivity results (Birn et al, 2014) and mask drug effects on connectivity in pharmacological fMRI (Khalili-Mahani et al, 2013 ).…”

Building a Science of Individual Differences from fMRI

“…Interestingly, it has been found that many of these model-based corrections actually reduce test-retest reliability for functional connectivity analyses [102,103]. This has been interpreted to mean that a large fraction of functional connectivity reflects basic physiological signals [102] (another validity issue, e.g. [104]).…”

The association between cerebrovascular reactivity and resting-state fMRI functional connectivity in healthy adults: The influence of basal carbon dioxide

“…This technique has been referred to as "rsfcMRI" (Birn et al, 2014;Tak et al, 2015). This rs-fcMRI technique is widely used in neuroscience research, and has vast potential for studying patients and the elderly, for whom task performance in conventional fMRI may be difficult due to reduced cognitive and motor capacity.…”