Researchers at the German Primate Center (DPZ) – Leibniz Institute for Primate Research in Göttingen have discovered that the brain reorganizes itself extensively across several brain regions when it learns to perform movements in a virtual environment with the help of a brain-computer interface. The scientists were thus able to show how the brain adapts when controlling motor prostheses. The findings not only help to advance the development of brain-computer interfaces, but also improve our understanding of the fundamental neural processes underlying motor learning.
In order to perform precise movements, our brain's motor system must continuously recalibrate itself. If we want to shoot a basketball, this works well with a familiar basketball, but requires extra practice with a lighter or heavier ball. Our brain uses the deviations from the expected (throw) result as an error signal to learn better commands for the next throw. The brain must also perform this task when it wants to control a movement via a brain-computer interface (BCI), for example, that of a neuroprosthesis. Until now, it was unclear which regions of the brain reflect the expected result of the movement (the trajectory of the ball), which reflect the error signal, and which reflect the corrected movement command that aims to compensate for the previous error.