期刊
NEUROIMAGE
卷 76, 期 1, 页码 183-201出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2013.03.004
关键词
Head motion correction; Resting-state fMRI; Voxel-wise movement; Test retest reliability; Functional connectomics
资金
- National Institute of Mental Health [BRAINS R01MH094639, R01MH083246, R01MH081218, K23MH087770]
- Stavros Niarchos Foundation
- Leon Levy Foundation
- Ryan Licht Sang Bipolar Foundation
- Brain and Behavior Research Foundation
- Autism Speaks
- National Natural Science Foundation of China [81171409, 81220108014]
- Startup Foundation for Distinguished Research Professor of the Institute of Psychology [Y0CX492S03]
- Hundred Talents Program [Y2CX112006]
- Chinese Academy of Sciences [KSZD-EW-TZ-002]
- NATIONAL INSTITUTE OF MENTAL HEALTH [K23MH087770, R01MH083246, R01MH081218, R01MH094639] Funding Source: NIH RePORTER
Functional connectomics is one of the most rapidly expanding areas of neuroimaging research. Yet, concerns remain regarding the use of resting-state fMRI (R-fMRI) to characterize inter-individual variation in the functional connectome. In particular, recent findings that micro head movements can introduce artifactual inter-individual and group-related differences in R-fMRI metrics have raised concerns. Here, we first build on prior demonstrations of regional variation in the magnitude of framewise displacements associated with a given head movement, by providing a comprehensive voxel-based examination of the impact of motion on the BOLD signal (i.e., motion-BOLD relationships). Positive motion-BOLD relationships were detected in primary and supplementary motor areas, particularly in low motion datasets. Negative motion-BOLD relationships were most prominent in prefrontal regions, and expanded throughout the brain in high motion datasets (e.g., children). Scrubbing of volumes with FD > 0.2 effectively removed negative but not positive correlations; these findings suggest that positive relationships may reflect neural origins of motion while negative relationships are likely to originate from motion artifact. We also examined the ability of motion correction strategies to eliminate artifactual differences related to motion among individuals and between groups for a broad array of voxel-wise R-fMRI metrics. Residual relationships between motion and the examined R-fMRI metrics remained for all correction approaches, underscoring the need to covary motion effects at the group-level. Notably, global signal regression reduced relationships between motion and inter-individual differences in correlation-based R-fMRI metrics; Z-standardization (mean-centering and variance normalization) of subject-level maps for R-fMRI metrics prior to group-level analyses demonstrated similar advantages. Finally, our test-retest (TRT) analyses revealed significant motion effects on TRT reliability for R-fMRI metrics. Generally, motion compromised reliability of R-fMRI metrics, with the exception of those based on frequency characteristics particularly, amplitude of low frequency fluctuations (ALFF). The implications of our findings for decision-making regarding the assessment and correction of motion are discussed, as are insights into potential differences among volume-based metrics of motion. (C) 2013 Elsevier Inc. All rights reserved.
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