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Potential pitfalls when denoising resting state fMRI data using nuisance regression

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Figure

Fig. 1. Schematic demonstrating how bandpassdependent on the duration of the scan, whereas the proportion of degrees of freedomremaining in theduration of the scan
Fig. 2. Simulated toy examples demonstrating the eunacross the shifts was recorded. Histograms of the resulting maximum correlation values are plotted for di10TR)
Fig. 3. R< 0.05, uncorrected for multiple comparisons). Maps were generated using a General Linear Model without pre-whitening (AFNI 3dDeconvolve) or with pre-whitening steps (AFNI3dREML2 maps estimating the percentage of variance removed by the total nois
Fig. 4. Optimisation of the temporal shift applied to the Pvoxels is plotted as a function of the temporal shift, ranging fromregressor (blue) and ten simulated phase-randomised regressors (cyan) are presented
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