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Can we predict real-time fMRI neurofeedback learning success from pretraining brain activity?, , , , , , , , , and 29 other author(s). Human Brain Mapping, 41 (14): 3839-3854 (July 2020)Predictors of real-time fMRI neurofeedback performance and improvement – A machine learning mega-analysis, , , , , , , , , and 38 other author(s). NeuroImage, (August 2021)Predicting intrinsic brain activity., , and . NeuroImage, (2013)Detecting stable individual differences in the functional organization of the human basal ganglia., , , , , , and . NeuroImage, (2018)Eliminating accidental deviations to minimize generalization error and maximize replicability: Applications in connectomics and genomics., , , , , , , , , and 6 other author(s). PLoS Comput. Biol., (2021)Individual differences in functional connectivity during naturalistic viewing conditions., , , , , and . NeuroImage, (2017)Standardizing the intrinsic brain: Towards robust measurement of inter-individual variation in 1000 functional connectomes., , , , and . NeuroImage, (2013)A comprehensive assessment of regional variation in the impact of head micromovements on functional connectomics., , , , , , , , , and . NeuroImage, (2013)Learning and comparing functional connectomes across subjects., and . NeuroImage, (2013)Multi-Modal Data Collection for Measuring Health, Behavior, and Living Environment of Large-Scale Participant Cohorts: Conceptual Framework and Findings from Deployments., , , , , , , , , and 3 other author(s). CoRR, (2020)