Recovery of the default mode network after demanding neurofeedback training occurs in spatio-temporally segregated subnetworks. - Dimitri Van De Ville; Permi Jhooti; Tanja Haas; Rotem Kopel; Karl-Olof Lövblad; Klaus Scheffler; Sven Haller (NeuroImage, 2012)

Co-Registration of Intra-Operative Photographs and Pre-Operative MR Images. - Benjamin Berkels; Ivan Cabrilo; Sven Haller; Martin Rumpf; Carlo Schaller (Bildverarbeitung für die Medizin, 2013)

Cortical Surface Co-Registration based on MRI Images and Photos - Benjamin Berkels; Ivan Cabrilo; Sven Haller; Martin Rumpf; Carlo Schaller (CoRR, 2013)

Dynamic reconfiguration of human brain functional networks through neurofeedback. - Sven Haller; Rotem Kopel; Permi Jhooti; Tanja Haas; Frank Scharnowski; Karl-Olof Lövblad; Klaus Scheffler; Dimitri Van De Ville (NeuroImage, 2013)

Real-time fMRI neurofeedback: Progress and challenges. - James S. Sulzer; Sven Haller; Frank Scharnowski; Nikolaus Weiskopf; Niels Birbaumer; Maria Laura Blefari; Annette B. Brühl; Leonardo G. Cohen; R. Christopher DeCharms; Roger Gassert; Rainer Goebel; Uwe Herwig; et al. (NeuroImage, 2013)

Co-registration of intra-operative brain surface photographs and pre-operative MR images. - Benjamin Berkels; Ivan Cabrilo; Sven Haller; Martin Rumpf; Karl Schaller (Int. J. Comput. Assist. Radiol. Surg., 2014)

Decomposing dynamic functional connectivity onto phase-dependent eigenconnectivities using the Hilbert transform. - Maria Giulia Preti; Sven Haller; Panteleimon Giannakopoulos; Dimitri Van De Ville (ISBI, 2015)

Medical Image Retrieval Using Multi-graph Learning for MCI Diagnostic Assistance. - Yue Gao 002; Ehsan Adeli-Mosabbeb; Minjeong Kim; Panteleimon Giannakopoulos; Sven Haller; Dinggang Shen (MICCAI (2), 2015)

MCI Identification by Joint Learning on Multiple MRI Data. - Yue Gao 002; Chong-Yaw Wee; Minjeong Kim; Panteleimon Giannakopoulos; Marie-Louise Montandon; Sven Haller; Dinggang Shen (MICCAI (2), 2015)

Predicting individual scores from resting state fMRI using partial least squares regression. - Djalel Eddine Meskaldji; Maria Giulia Preti; Thomas Bolton 001; Marie-Louise Montandon; Cristelle Rodriguez; Stephan Morgenthaler; Panteleimon Giannakopoulos; Sven Haller; Dimitri Van De Ville (ISBI, 2016)

Meta-analysis of real-time fMRI neurofeedback studies using individual participant data: How is brain regulation mediated? - Kirsten Emmert; Rotem Kopel; James S. Sulzer; Annette B. Brühl; Brian D. Berman; David E. J. Linden; Silvina G. Horovitz; Markus Breimhorst; Andrea Caria; Sabine Frank; Stephen J. Johnston; Zhi-ying Long; et al. (NeuroImage, 2016)

Detecting Perfusion Pattern Based on the Background Low-Frequency Fluctuation in Resting-State Functional Magnetic Resonance Imaging Data and Its Influence on Resting-State Networks: An Iterative Postprocessing Approach. - Tianyi Qian; Davide Zanchi; Cristelle Rodriguez; Marine Ackermann; Panteleimon Giannakopoulos; Sven Haller (Brain Connect., 2017)

Distributed Patterns of Brain Activity Underlying Real-Time fMRI Neurofeedback Training. - Rotem Kopel; Kirsten Emmert; Frank Scharnowski; Sven Haller; Dimitri Van De Ville (IEEE Trans. Biomed. Eng., 2017)

Inter-Network High-Order Functional Connectivity (IN-HOFC) and its Alteration in Patients with Mild Cognitive Impairment. - Han Zhang 002; Panteleimon Giannakopoulos; Sven Haller; Seong-Whan Lee; Shijun Qiu; Dinggang Shen (Neuroinformatics, 2019)

Higher availability of α4β2 nicotinic receptors (nAChRs) in dorsal ACC is linked to more efficient interference control. - Swann Pichon; Valentina Garibotto; Michael Wissmeyer; Yann Seimbille; Lia Antico; Osman Ratib; Patrik Vuilleumier; Sven Haller; Fabienne Picard (NeuroImage, 2020)

Predictors of real-time fMRI neurofeedback performance and improvement - A machine learning mega-analysis. - Amelie Haugg; Fabian M. Renz; Andrew A. Nicholson; Cindy Lor; Sebastian J. Götzendorfer; Ronald Sladky; Stavros Skouras; Amalia McDonald; R. Cameron Craddock; Lydia Hellrung; Matthias Kirschner; Marcus Herdener; et al. (NeuroImage, 2021)