Physical characteristics not psychological state or trait characteristics predict motion during resting state fMRI
Author:
Publisher
Springer Science and Business Media LLC
Subject
Multidisciplinary
Link
http://www.nature.com/articles/s41598-018-36699-0.pdf
Reference50 articles.
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3. Burgess, G. C. et al. Evaluation of Denoising Strategies to Address Motion-Correlated Artifacts in Resting-State Functional Magnetic Resonance Imaging Data from the Human Connectome Project. Brain Connect 6, 669–680, https://doi.org/10.1089/brain.2016.0435 (2016).
4. Satterthwaite, T. D. et al. An improved framework for confound regression and filtering for control of motion artifact in the preprocessing of resting-state functional connectivity data. Neuroimage 64, 240–256, https://doi.org/10.1016/j.neuroimage.2012.08.052 (2013).
5. Power, J. D., Barnes, K. A., Snyder, A. Z., Schlaggar, B. L. & Petersen, S. E. Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. Neuroimage 59, 2142–2154, https://doi.org/10.1016/j.neuroimage.2011.10.018 (2012).
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