2013
The nuisance of nuisance regression: Spectral misspecification in a common approach to resting-state fMRI preprocessing reintroduces noise and obscures functional connectivity
Abstract: Recent resting-state functional connectivity fMRI (RS-fcMRI) research has demonstrated that head motion during fMRI acquisition systematically influences connectivity estimates despite bandpass filtering and nuisance regression, which are intended to reduce such nuisance variability. We provide evidence that the effects of head motion and other nuisance signals are poorly controlled when the fMRI time series are bandpass-filtered but the regressors are unfiltered, resulting in the inadvertent reintroduction of…
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Cited by 760 publications
(588 citation statements)
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“…Figure 4A illustrates how the relationship between FD and global DVARS changed using all three FC processing strategies, while Figure 4B illustrates the distributions of global FD/DVARS correlations post-scrubbing. Consistent with previous reports (Hallquist et al, 2013), we observed a strong correlation between FD and global DVARS in pre-FCP data (Figure 4A, red line; median: .805).…”
Section: Resultssupporting
confidence: 93%
“…Figure 4A illustrates how the relationship between FD and global DVARS changed using all three FC processing strategies, while Figure 4B illustrates the distributions of global FD/DVARS correlations post-scrubbing. Consistent with previous reports (Hallquist et al, 2013), we observed a strong correlation between FD and global DVARS in pre-FCP data (Figure 4A, red line; median: .805).…”
Section: Resultssupporting
confidence: 93%
“…Also consistent with published findings (Hallquist et al, 2013), we observed a significant reduction in the median correlation between FD and global DVARS after applying all three FCP approaches; however, MR signal modulation by head motion appeared to be differentially mitigated by the FCP strategies. Overall, the linear mixed effects model revealed a significant effect of FCP strategy on the global FD/DVARS correlation (χ 2 (2) = 288.7, p < .0001).…”
Section: Resultssupporting
confidence: 91%
“…In line with previous studies ( Hallquist et al, 2013 ; Muschelli et al, 2014 ), there was a significant reduction in the median correlation between FD and DVARS after denoising compared to before within all four rs-fMRI modalities, FDR-corrected. Plots of the distributions across subjects before and after denoising are provided in Supplementary Figure 2 .…”
Section: Resultssupporting
confidence: 91%
“…In removing regular nuisance effect, we demonstrated that regression of WM and CSF signals before temporal filtering is more effective (Supplementary Figure S1). This is consistent with the previous findings in human rs-fMRI studies that nuisance-related variability such as head motion and cardiac artifacts can be better controlled when covariate regression is applied before temporal filtering rather than after filtering in the preprocessing procedure (Hallquist et al, 2013). Further evaluation of the BS coupling effect on preprocessed images indicated that BS related global effect as indicated in Figure 1C cannot be fully eliminated by using either preprocessing procedure (Supplementary Figure S2).…”
Section: Discussionsupporting
confidence: 92%
