Optimization of rs-fMRI preprocessing for signal-Noise separation, test-retest reliability, group discrimination

We focus our analyses on the effects of common preprocessing steps, such as global signal regression (GS) (Weissenbacher et al., 2009 and Shirer et al., 2012); removal of cerebrospinal fluid (CSF) and white matter (WM) confounds (Shirer et al., 2012); noise regression of motion parameters estimated during motion correction (Friston et al., 1996, Power et al., 2012, Power et al., 2013, Satterthwaite et al., 2013 and Yan et al., 2013a); and temporal filtering at various frequency bands reported in the literature (Achard et al., 2006, Ko et al., 2011 and Guo et al., 2012).