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Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion
Open accessAbstract
Here, we demonstrate that subject motion produces substantial changes in the timecourses of resting state functional connectivity MRI (rs-fcMRI) data despite compensatory spatial registration and regression of motion estimates from the data. These changes cause systematic but spurious correlation structures throughout the brain. Specifically, many long-distance correlations are decreased by subject motion, whereas many short-distance correlations are increased. These changes in rs-fcMRI correlations do not arise from, nor are they adequately countered by, some common functional connectivity processing steps. Two indices of data quality are proposed, and a simple method to reduce motion-related effects in rs-fcMRI analyses is demonstrated that should be flexibly implementable across a variety of software platforms. We demonstrate how application of this technique impacts our own data, modifying previous conclusions about brain development. These results suggest the need for greater care in dealing with subject motion, and the need to critically revisit previous rs-fcMRI work that may not have adequately controlled for effects of transient subject movements.
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“Strict motion correction procedures were applied to resting state functional maps, due to the sensitivity of RSFC data to head motion (Power et al., 2012, Satterthwaite et al., 2012, Van Dijk et al., 2012).”
From Developmental sex differences in resting state functional connectivity of amygdala sub-regions (2015) · cites this paper as Power et al., 2012
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In the citing paper
“Importantly, no group differences were observed in frame-wise displacement, a metric of relative head displacement between volumes (Power et al. 2012), suggesting the groups were well-matched for head motion (Table 2).”
From A novel resting-state functional magnetic resonance imaging signature of resilience to recurrent depression (2017) · cites this paper as Power et al. 2012
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In the citing paper
“To avoid spurious correlation due to motion55,56, we choose a priori a more conservative criterion by excluding all participants with more than 1 mm FD.”
From The relationship between resting-state functional connectivity, antidepressant discontinuation and depression relapse (2020) · cites this paper as [55]
The cited source says what the claim attributes to it.
In the citing paper
“Head motion during fMRI acquisitions was evaluated using the framewise displacement, which was calculated as the L1-norm of the realignment-derived parameters after converting angles to linear displacements (Power et al., 2012).”
From Perception is associated with the brain’s metabolic response to sensory stimulation (2022) · cites this paper as Power et al., 2012
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“Finally there were no significant effects of percent frames scrubbed using a threshold of 0.5 mm (Power et al. 2012) on group, condition, or interactions of group and condition (group:”
From Brain Activity and Functional Connectivity Associated with Hypnosis (2016) · cites this paper as Power et al. 2012
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In the citing paper
“Additionally we examined mean framewise displacement (Power et al. 2012) and found no main effect of group (F(1,40) = 0.01, P = 0.92), condition (F(3,40) = 1.01,P = 0.39), or group by condition interaction (F(3,40) = 1.49,P = 0.22).”
From Brain Activity and Functional Connectivity Associated with Hypnosis (2016) · cites this paper as Power et al. 2012
In the citing paper
“When processing techniques intended to remove motion artifact are applied, developmental effects of this type – both in terms of overall local versus distributed coupling and in terms of changing modular assignments – are substantially attenuated, though still present to a limited extent (Fair et al., 2012b; Power et al., 2012; Satterthwaite et al., 2012).”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Power et al., 2012
In the citing paper
“Indeed, there are now at least 3 reports that suggest the network structure in children as defined by community detection (see Figure 3) are largely similar to the adult (Fair et al., 2012b; Marek et al., 2015; Power et al., 2012).”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Power et al., 2012
In the citing paper
“it has been revealed that motion increases non-specific local coupling and decreases long-range coupling in ways that are similar to differences found between children and adults (Fair et al., 2012b; Power et al., 2012; Satterthwaite et al., 2012; Yan et al., 2013).”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Power et al., 2012
In the citing paper
“head motion has become a substantial concern since 2012 when a trio of papers pointed to systematic motion-related artifacts in rs-fcMRI (Power et al., 2012; Satterthwaite et al., 2012; Van Dijk et al., 2012).”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Power et al., 2012
In the citing paper
“head motion increases functional correlations between spatially proximal nodes and decreases correlations between distant nodes (Power et al., 2012).”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Power et al., 2012
In the citing paper
“researchers recently discovered that some functional connectivity analyses interpreted as demonstrating developmental increases in long-range connections during rest (i.e., independent from any task) were spurious effects of greater motion in younger participants [62,63], which were eliminated with appropriate controls for motion-induced artifacts.”
From Arrested development? Reconsidering dual-systems models of brain function in adolescence and disorders (2012) · cites this paper as [62]
In the citing paper
“Recent work has suggested that small movements may have a greater impact on resting-state analyses than previously considered (Power et al, 2012).”
From Resting-state cortico-thalamic-striatal connectivity predicts response to dorsomedial prefrontal rTMS in major depressive disorder (2014) · cites this paper as Power et al, 2012
In the citing paper
“Head motion, even of submillimeter magnitude, has been identified as a nonphysiological source of spurious variance in resting-state fMRI data (Power et al. 2012; Van Dijk et al. 2012; Satterthwaite et al. 2013).”
From Joint attention and brain functional connectivity in infants and toddlers (2017) · cites this paper as Power et al. 2012
In the citing paper
“Diagnostic groups did not differ in age, sex, handedness, FSIQ, or head motion (mean framewise displacement [FD (Power et al., 2012)], translational and rotational motion, Table 2).”
From Investigating functional brain network integrity using a traditional and novel categorical scheme for neurodevelopmental disorders (2019) · cites this paper as Power et al., 2012
In the citing paper
“Given the known problems of motion for connectivity analyses (90), we used ArtRepair software to correct for excessive movement (91).”
From Adolescent impatience decreases with increased frontostriatal connectivity (2015) · cites this paper as [90]
In the citing paper
“we elected to exclude participants where for either visit, the participant had one or more of the following: movement in any dimension ≥4 mm, and/or ≥25% of volumes identified as outliers according to the DVARS metric72 such that only participants who displayed acceptable amounts of motion under both the OT and PLC visits were included in analysis.”
From Intranasal oxytocin enhances connectivity in the neural circuitry supporting social motivation and social perception in children with autism (2016) · cites this paper as [72]
In the citing paper
“Following standard Statistical Parametric Mapping (SPM12; https://www.fil.ion.ucl.ac.uk/spm12 ) pre-processing steps, additional motion correction was applied in the form of censoring, i.e. identifying outliers based on framewise displacement and regressing them from the fMRI timeseries ( Power et al., 2012 , Power et al., 2014 ) (see Supplementary Methods), to compensate for using fairly lenient”
From Self-blame-selective hyper-connectivity between anterior temporal and subgenual cortices predicts prognosis in major depressive disorder (2023) · cites this paper as Power et al., 2012
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Metadata
- Authors
- Power, J. D., Barnes, K. A., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E.
- Affiliations
- Washington University in St. Louis (US)
- Corresponding author
- Power, Jonathan D.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2012-02
- Volume
- 59
- Issue
- 3
- Pages
- 2142-2154
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC3254728
- OpenAlex
- W1990134753
- Cited by
- 7,429
- References
- 42
- Citations by year
- 2026: 404 · 2025: 506 · 2024: 475 · 2023: 525 · 2022: 604 · 2021: 671 · 2020: 696 · 2019: 647 · 2018: 604 · 2017: 587 · 2016: 504 · 2015: 439 · 2014: 357 · 2013: 294 · 2012: 104
- FWCI
- 123.02
- Type
- journal article
- Language
- en
- Update notices
- erratum (2012-11-01)
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (5p60dk020579-35, 5u54mh091657-05)
- National Institute of Mental Health (P50MH071616, U54-MH091657, P50MH71616)
- National Institute on Deafness and Other Communication Disorders (K23DC006638)
- National Institute of Diabetes and Digestive and Kidney Diseases (P60 DK020579-31)
- National Institute of Neurological Disorders and Stroke (R01NS32979, R01NS032979, R21NS061144)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD057076)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- subject motion, resting-state functional connectivity, spurious correlations, motion correction, spatial registration, brain development
- MeSH terms
- Algorithms, Brain, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Motion, Oxygen, Software, Cohort Studies, Artifacts, Head Movements
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