Jana Zweerings

This paper introduces a subject-level searchlight optimization framework combining univariate and multivariate analyses to identify condition-sensitive voxels for emotional state decoding in fMRI.

This study explores using real-time representational similarity analysis in fMRI neurofeedback to navigate emotional states, showing feasibility and improved performance with repeated sessions.

This paper analyzes fMRI neurofeedback data to identify brain regions and networks involved in feedback processing and regulation recalibration during training.

The paper finds that right putamen gray matter volume predicts success in real-time fMRI neurofeedback training across different paradigms and target regions.

This study identifies common and substance-specific neural alterations in substance use disorders through coordinate-based meta-analyses of fMRI studies.