Resting-state fMRI data were preprocessed with FSL 5.1 (https://www.fmrib.ox.ac.uk/fsl) [15]. The fMRI was skull stripped and preprocessed with signal despiking, removal of physiological artifacts from respiration and heartbeat, and correction for slice timing. Preprocessed images were then corrected for motion, followed by spatially smoothing with a Gaussian kernel of 0.8 mm FWHM and high-pass filtering with a cutoff of 100 seconds. Volumes from functional images were registered to a standard space with a three-step process. Images were first aligned with the individual's low-resolution anatomical image, followed by alignment with the individual's high-resolution anatomical image, and then coregistered to a standard space. Average time courses from all of the voxels inside white matter (WM) and cerebrospinal fluid (CSF) were extracted. Confounding regressors that modeled WM and CSF signals and six motion parameters, including translations and rotations, were removed from the images through linear regression.

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