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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)Towards understanding rTMS mechanism of action: Stimulation of the DLPFC causes network-specific increase in functional connectivity., , , , , , , , , and 1 other author(s). NeuroImage, (2017)No time for drifting: Comparing performance and applicability of signal detrending algorithms for real-time fMRI., , , , , , , , , and . NeuroImage, (2019)Slice-timing effects and their correction in functional MRI., , , , , and . NeuroImage, 58 (2): 588-594 (2011)Predictors of real-time fMRI neurofeedback performance and improvement – A machine learning mega-analysis, , , , , , , , , and 38 other author(s). NeuroImage, (August 2021)OpenNFT: An open-source Python/Matlab framework for real-time fMRI neurofeedback training based on activity, connectivity and multivariate pattern analysis., , , , , , , , and . NeuroImage, (2017)Voxel-based morphometry at ultra-high fields. A comparison of 7 T and 3 T MRI data., , , , , , , , , and 1 other author(s). NeuroImage, (2015)Modulations in resting state networks of subcortical structures linked to creativity., , , , , , , , and . NeuroImage, (2019)Gender transition affects neural correlates of empathy: A resting state functional connectivity study with ultra high-field 7T MR imaging., , , , , , , , , and 4 other author(s). NeuroImage, (2016)Predictors of real-time fMRI neurofeedback performance and improvement - A machine learning mega-analysis., , , , , , , , , and 38 other author(s). NeuroImage, (2021)