Functional MRI Preprocessing Pipeline

Functional images were preprocessed using the CONNv17 FC toolbox (43 (link)), implemented in MatlabR2017a (The MathWorks Inc., Natick, Massachusetts, USA). The preprocessing pipeline included realignment, denoising of motion artifacts, and head motion (aCompCor (44 (link)), segmentation, coregistration to each participant's anatomical scan, normalization to an age-specific T1 template for pediatric studies (45 (link)), re-sliced to a 2-mm isotropic resolution in MNI space, and smoothing using a Gaussian kernel of 6 mm full-width at half-maximum [FWHM]). Additional steps after denoising included band-pass filtering of the BOLD time series (between 0.008 and 0.09 Hz) and linear detrending. After the motion artifacts and head motion detection, 34 children were excluded for excessive motion (which is to say, those with <4 min of data were excluded) (42 (link)).