Preprocessing fMRI Data: All data processing, analysis, and sharing will be done in accordance with the Organization for Human Brain Mapping’s (OHBM) best practices46. Functional imaging data will be processed and analyzed with FSL (FMRIB’s Software Library, www.fmrib.ox.ac.uk/fsl) using the standard processing stream from OpenfMRI (available here: https://github.com/poldrack/openfmri). BET will be used to extract the brain from the skull, and MCFLIRT will be used for motion correction. Participants will be excluded for movement greater than 3.0 mm in any direction. Individuals’ data will then be smoothed with a 6-mm full-width at half-maximum isotropic Gaussian filter. Confound motion parameter regressors will be created for TRs with a framewise displacement (FD) greater than 0.9. These FD-based motion regressors will be modeled along with the 6 motion parameters (from MCFLIRT), their squares, and the derivatives of each. A functional run for a subject will be excluded if more than 20% of all the volumes were tagged as high motion. Within-run parameters will be estimated at the first level using FILM, a fixed-effects model will estimate within-subject effects at the second level and group effects will be estimated using a mixed-effects model (FSL’s FLAME1) at the third level, which appropriately addresses the potential presence of differences in variance across groups. Spatial normalization will be performed using nonlinear registration with FSL’s FNIRT tool.