Abstract:
:Recent studies have illustrated that motion-related artifacts remain in resting-state fMRI (rs-fMRI) data even after common corrective processing procedures have been applied, but the extent to which head motion distorts the data may be modulated by the corrective approach taken. We compare two different methods for estimating nuisance signals from tissues not expected to exhibit BOLD fMRI signals of neuronal origin: 1) the more commonly used mean signal method and 2) the principal components analysis approach (aCompCor: Behzadi et al., 2007). Further, we investigate the added benefit of "scrubbing" (Power et al., 2012) following both methods. We demonstrate that the use of aCompCor removes motion artifacts more effectively than tissue-mean signal regression. In addition, inclusion of more components from anatomically defined regions of no interest better mitigates motion-related artifacts and improves the specificity of functional connectivity estimates. While scrubbing further attenuates motion-related artifacts when mean signals are used, scrubbing provides no additional benefit in terms of motion artifact reduction or connectivity specificity when using aCompCor.
journal_name
Neuroimagejournal_title
NeuroImageauthors
Muschelli J,Nebel MB,Caffo BS,Barber AD,Pekar JJ,Mostofsky SHdoi
10.1016/j.neuroimage.2014.03.028subject
Has Abstractpub_date
2014-08-01 00:00:00pages
22-35eissn
1053-8119issn
1095-9572pii
S1053-8119(14)00175-Xjournal_volume
96pub_type
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