Artificial neural networks decode brain activity during performed and imagined movements
Filtering information for search engines, acting as an opponent during a board game or recognizing images: Artificial intelligence has far outpaced human intelligence in certain tasks. Several groups from the Freiburg excellence cluster BrainLinks-BrainTools led by neuroscientist private lecturer Dr. Tonio Ball are showing how ideas from computer science could revolutionize brain research. In the scientific journal Human Brain Mapping they illustrate how a self-learning algorithm decodes human brain signals that were measured by an electroencephalogram (EEG).
It included performed movements, but also hand and foot movements that were merely thought of, or an imaginary rotation of objects. Even though the algorithm was not given any characteristics ahead of time, it works as quickly and precisely as traditional systems that have been created to solve certain tasks based on predetermined brain signal characteristics, which are therefore not appropriate for every situation.