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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)Pseudo-real fMRI data generation and its utility toward quantitative evaluation of analytical methods., and . SMC, page 1095-1099. IEEE, (2012)Predictors of real-time fMRI neurofeedback performance and improvement - A machine learning mega-analysis., , , , , , , , , and 38 other author(s). NeuroImage, (2021)Predictors of real-time fMRI neurofeedback performance and improvement – A machine learning mega-analysis, , , , , , , , , and 38 other author(s). NeuroImage, (August 2021)Hub of functional network changes from real-time fMRI neurofeedback on heavy smokers., and . BCI, page 1-2. IEEE, (2015)Mediation analysis of triple networks revealed functional feature of mindfulness from real-time fMRI neurofeedback., , , , , , , , , and . NeuroImage, (2019)The Inclusion of Functional Connectivity Information into fMRI-based Neurofeedback Improves Its Efficacy in the Reduction of Cigarette Cravings., , , , and . J. Cogn. Neurosci., 27 (8): 1552-1572 (2015)Are there brain regions related to speech perception? Evidence from a functional MRI study., , and . SMC, page 1100-1102. IEEE, (2012)Modulated Neuronal Activity and Connectivity of Smoking Resist Using Real-Time fMRI Neurofeedback., and . ICONIP (3), volume 8228 of Lecture Notes in Computer Science, page 9-16. Springer, (2013)