2013
DOI: 10.1073/pnas.1301725110
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Abstract: Functional connectivity analysis of resting state blood oxygen level-dependent (BOLD) functional MRI is widely used for noninvasively studying brain functional networks. Recent findings have indicated, however, that even small (≤1 mm) amounts of head movement during scanning can disproportionately bias connectivity estimates, despite various preprocessing efforts. Further complications for interregional connectivity estimation from time domain signals include the unaccounted reduction in BOLD degrees of freedo… Show more

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Cited by 339 publications
(456 citation statements)
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“…Although these analyses were performed on movement-scrubbed data, it may be possible that micromovements still remain (33), which studies using faster acquisition (34) could address. Relatedly, a recent rigorous movement-related investigation (35) suggests that motion artifacts can spatially propagate as complex waveforms in the BOLD signal across multiple frames.…”
Section: Discussionmentioning
confidence: 99%
“…Although these analyses were performed on movement-scrubbed data, it may be possible that micromovements still remain (33), which studies using faster acquisition (34) could address. Relatedly, a recent rigorous movement-related investigation (35) suggests that motion artifacts can spatially propagate as complex waveforms in the BOLD signal across multiple frames.…”
Section: Discussionmentioning
confidence: 99%
“…motion artifact (28) or separating the artifact component from the neural component based on fMRI data acquired using multiple echo times (TEs) (29), could eventually improve the specificity of biomarkers. Second, our analyses were based on a specific type of connectivity measure, distant connectivity, and therefore the results should not be extrapolated to all types of connectivity measures without careful examination.…”
Section: Discussionmentioning
confidence: 99%
“…While it is possible to prevent some in-scanner motion through the use of new MRI pulse sequences (Bright and Murphy, 2013;Brown et al, 2010;Kundu et al, 2013;Kuperman et al, 2011;Maclaren et al, 2013;Ooi et al, 2011;White et al, 2010), training on MRI simulators before scanning (Lueken et al, 2012;Raschle et al, 2009), or even the use of head restraints and other bite bars, most data collection either do not or cannot make use of these techniques and motion artifacts are still detectable in these rs-fMRI data.…”
mentioning
confidence: 99%