The influence of head motion on intrinsic functional connectivity MRI
Open accessAbstract
Functional connectivity MRI (fcMRI) has been widely applied to explore group and individual differences. A confounding factor is head motion. Children move more than adults, older adults more than younger adults, and patients more than controls. Head motion varies considerably among individuals within the same population. Here we explored the influence of head motion on fcMRI estimates. Mean head displacement, maximum head displacement, the number of micro movements (>0.1 mm), and head rotation were estimated in 1000 healthy, young adult subjects each scanned for two resting-state runs on matched 3T scanners. The majority of fcMRI variation across subjects was not linked to head motion. However, head motion had significant, systematic effects on fcMRI network measures. Head motion was associated with decreased functional coupling in the default and frontoparietal control networks--two networks characterized by coupling among distributed regions of association cortex. Other network measures increased with motion including estimates of local functional coupling and coupling between left and right motor regions--a region pair sometimes used as a control in studies to establish specificity. Comparisons between groups of individuals with subtly different levels of head motion yielded difference maps that could be mistaken for neuronal effects in other contexts. These effects are important to consider when interpreting variation between groups and across individuals.
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Head motion has become a substantial concern since 2012, when a trio of papers pointed to systematic motion-related artifacts in rs-fcMRI.
“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 Van Dijk et al., 2012
Some resting-state connectivity findings of age-related growth in long-range connections were artifacts of greater motion in younger participants and disappeared with proper motion correction.
“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 [63]
Resting-state functional connectivity data are sensitive to head motion.
“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 Van Dijk et al., 2012
Head motion, even of submillimeter magnitude, is a nonphysiological source of spurious variance in resting-state fMRI data.
“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 Van Dijk et al. 2012
The strength of long-range functional connectivity is underestimated in cases of increased head motion.
“The strength of long-range functional connectivity is underestimated in cases of increased head motion (Van Dijk et al., 2012)”
From Investigating functional brain network integrity using a traditional and novel categorical scheme for neurodevelopmental disorders (2019) · cites this paper as Van Dijk et al., 2012
One important source of artifactual variation in functional MRI is head motion.
“One important source of artifactual variation in functional MRI is head motion (47).”
From Understanding heterogeneity in clinical cohorts using normative models: Beyond case-control studies (2016) · cites this paper as [47]
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- Authors
- Van Dijk, K. R. A., Sabuncu, M. R., & Buckner, R. L.
- Affiliations
- Massachusetts General Hospital (US)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Buckner, Randy L.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2012-01
- Volume
- 59
- Issue
- 1
- Pages
- 431-438
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC3683830
- OpenAlex
- W2132175842
- Cited by
- 2,344
- References
- 47
- Citations by year
- 2026: 59 · 2025: 80 · 2024: 85 · 2023: 107 · 2022: 126 · 2021: 141 · 2020: 174 · 2019: 234 · 2018: 184 · 2017: 191 · 2016: 214 · 2015: 238 · 2014: 206 · 2013: 203 · 2012: 92
- FWCI
- 82.44
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- NIA (AG021910, P41RR14074, K08MH067966)
- Howard Hughes Medical Institute
- Simons Foundation
- NIH (1KL2RR025757)
- Harvard University
- 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
- head movement, functional connectivity, resting-state fMRI, default mode network, frontoparietal network, functional coupling, micromotion, head rotation, interindividual variability, confounding
- MeSH terms
- Adolescent, Adult, Brain, Brain Mapping, Female, Head, Humans, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Male, Motion, Movement, Neural Pathways, Young Adult
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