Impact of in-scanner head motion on multiple measures of functional connectivity: Relevance for studies of neurodevelopment in youth☆
Highlights
► In children and adolescents, motion and age are highly related. ► Motion impacts multiple common measures of functional connectivity. ► Failure to account for motion may inflate estimates of the effect of age.
Introduction
Resting state functional MRI (fcMRI) has been developed as a powerful tool to assess connectivity in large-scale brain networks (Biswal et al., 1995, Fox and Raichle, 2007), and has been used to explore both individual and between-group differences in brain connectivity (Satterthwaite et al., 2010, van den Heuvel et al., 2009, Wolf et al., 2007). However, an important recent study (Van Dijk et al., 2011) has demonstrated that head motion has a confounding effect on fcMRI, whereby increased motion is associated with diminished connectivity between distant nodes while simultaneously increasingly local coupling.
This finding is of particular relevance to imaging studies of neurodevelopment in youth. While it has not been formally examined, it is intuitive that a child's age may be highly related to the ability to stay very still during scanning. Furthermore, past studies have reported that neurodevelopment in youth is associated with increased distant connectivity and reduced local connectivity (Dosenbach et al., 2010, Fair et al., 2007, Fair et al., 2008, Fair et al., 2009). It is noteworthy that this pattern of connectivity change is the inverse of the effect of in-scanner head motion, suggesting that uncontrolled motion might influence estimates of neurodevelopmental trajectories of connectivity. However, several of the most prominent studies of neurodevelopmental connectivity have rigorously matched motion and age, thus reducing the likelihood that reported effects were an artifact of motion (Dosenbach et al., 2010, Fair et al., 2007, Fair et al., 2008). Two other recent studies took a different approach and included a summary measure of subject motion as a confounding variable in the group-level regression (Zuo et al., 2010a, Zuo et al., 2010b, Zuo et al., 2010c, Zuo et al., 2011). Nonetheless, the relationship between motion and connectivity in youth has not been previously examined directly. In addition, while Van Dijk et al. demonstrated the effect of motion on seed-based connectivity analyses, it is not known how motion affects other common measures of connectivity including graphical measures of network modularity (Rubinov and Sporns, 2010), independent components analysis (ICA; Beckmann et al., 2005) and power spectrum-based measures such the amplitude of low frequency fluctuation (ALFF; Zang et al., 2007) and the fractional amplitude of low frequency fluctuation (fALFF; Zou et al., 2008).
Our goals in this paper were three-fold. First, we aimed to replicate the results reported by Van Dijk et al. in a completely independent dataset. Second, we extend the analyses presented by Van Dijk et al., and investigate how generalizable the effects of motion are to other analyses of resting-state BOLD data. Specifically, we examine how inter-node distance modulates the effects of motion, and then evaluate the impact of in-scanner head motion on network modularity, network connectivity as measured with dual-regression ICA, and power-spectrum based measures such as ALFF and fALFF. Third and finally, we demonstrate that subject age and motion are highly related, and show the importance of accounting for motion in studies of youth by comparing estimates of the effect of subject age in sub-samples where age and motion are unrelated, related, or when motion is accounted for using regression. As revealed below, motion had marked effects on all measures of connectivity, and had a substantial impact on estimates of connectivity change in youth.
Section snippets
Subjects
The present study is a collaboration between the Center for Applied Genomics (CAG) at Children's Hospital of Philadelphia (CHOP) and the Brain Behavior Laboratory at the University of Pennsylvania (Penn). Study procedures were reviewed and approved by the Institutional Review Board of both CHOP and Penn. The target population-based sample is of 10,000 youths who presented to the CHOP network for a pediatric visit and volunteered to participate in genomic studies of complex pediatric disorders.
Replication of the effect of motion on within-network connectivity
In the age/motion-unrelated sample, we replicated the findings of Van Dijk et al.: motion diminished average within-network connectivity for both the default mode network and the frontoparietal control network. Specifically, mean relative displacement was negatively correlated with average connectivity in the default mode network (r = − 0.12, p = 0.01). The effect of motion on the average connectivity within the frontoparietal control network was similar (r = − 0.11, p = 0.02). No significant nonlinear
Discussion
In this study we examined the effect of in-scanner head motion on measures of functional connectivity in a large sample of children and adolescents. After replicating the findings of Van Dijk et al., we conducted additional analyses and demonstrated that in-scanner motion influences multiple measures of connectivity beyond seed analyses. Additionally, we demonstrated that motion is highly related to subject age, and that motion can impact estimates of the relationship between connectivity and
Disclosures
Drs. Gur report investigator-initiated grants from Pfizer and AstraZeneca. All other authors report no disclosures.
Acknowledgments
Thanks to Monica Calkins, Jan Richard, and Rosetta Chiavacci for assistance with assessment and recruitment.
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Financial support: Supported by RC2 grants from the National Institute of Mental Health MH089983 and MH089924. Dr. Satterthwaite was supported by NIMH T32 MH019112, APIRE, and NARSAD through the Marc Rapport Family Investigator Grant. Dr. Wolf was supported by NIMH MH085096, APIRE, and NARSAD through the Sidney R. Baer, Jr. Foundation.