Data preparation and preprocessing
aCompCor
REGRESSION
For all post-hoc analyses, fMRI data will be preprocessed using the most up-to-date stable version of standardized analysis pipelines (fMRIPrep or HCP minimal pipeline) at the time of analysis. Current pipelines include skull-stripping, realignment, registration, normalization, susceptibility distortion correction, automated tissue segmentation, and confound regressor generation [Preprocessed data and confounds will be further processed for nuisance regression and functional connectivity analysis. As best practices for nuisance regression are still evolving over time, we will adhere to current standards of nuisance regression at the time of analysis. Given current recommendations, however, we anticipate including nuisance regressors for head motion (12; 3 translation, 3 rotation, and first derivatives), aCompCor (top 5 PCA components from white matter and cerebrospinal fluid [Functional connectivity will be calculated as the product-moment correlation between the average timecourses of primary analysis DMN regions of interest (ROIs) from rsfMRI runs co-registered to the MNI152Lin2009cAsym template (the standard fMRIPrep brain template). Primary ROIs for this study will be the mPFC and PCC voxels, respectively, within participant-specific masks used for real-time neurofeedback. In the case that any participant-specific mPFC or PCC regions contain < 200 voxels, the template mask (defined via the Yeo17 DefaultA parcellation) for that region will be used instead (