Till M. Berger
Papers
1
Total Citations
6
H-Index
1
About
Till M. Berger is a researcher at the intersection of computational neuroscience and human motor control, with a focus on how non-invasive brain stimulation alters movement. His work centers on applying probabilistic movement primitives—a machine learning framework—to decode subtle changes in human motion, particularly under transcranial current stimulation. Berger’s most-cited study, “Using Probabilistic Movement Primitives in Analyzing Human Motion Differences Under Transcranial Current Stimulation” (2021), demonstrates a novel approach that moves beyond traditional, user-defined features like movement onset times or peak velocities. Instead, his method captures the full probabilistic structure of motion, offering a more sensitive and objective tool for analyzing how brain stimulation affects motor behavior. This work, with 6 citations, has laid groundwork for computer-aided clinical assessments, promising to enhance the precision of rehabilitation and neuroprosthetic design. Berger’s contributions are notable for bridging machine learning and neuroscience, providing a data-driven lens to study neural modulation. His research is particularly relevant for students and researchers interested in motor control, brain-computer interfaces, and the computational analysis of human movement.
Research Focus
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Top Papers
- 1