Filip Niemann

This study identifies reliable and functionally relevant brain regions for tDCS to enhance novel-word learning and assesses test-retest reliability of behavioral and imaging outcomes.

This study evaluates the test-retest reliability of fMRI BOLD signals during sequential decision making using a three-stage Markov decision task and finds moderate to good reliability in key brain regions.

The paper introduces a multimodal fMRI framework to guide tDCS target selection by integrating intrinsic connectivity and task-evoked activity patterns.

This study identifies functional brain networks involved in object-location learning using fMRI and shows how connectivity within these networks changes with learning performance.

The paper develops a deep learning model to automate electrode detection in tDCS-fMRI studies, outperforming manual and semi-automated methods in precision and reducing human bias.

This study shows that tDCS improves word-finding speed in older adults with poor baseline performance, but only when applied to the left inferior frontal gyrus.