Scientists have completed the first-ever demonstration of a “plug and play” brain prosthesis controlled by a paralyzed person.
The system uses machine learning to help the individual control a computer interface with just their brain. Unlike most brain-computer interfaces (BCI), the AI worked without requiring extensive daily retraining.
Study senior author Karunesh Ganguly, an associate professor in the UC San Francisco Department of Neurology, described the breakthrough in a statement:
The BCI field has made great progress in recent years, but because existing systems have had to be reset and recalibrated each day, they haven’t been able to tap into the brain’s natural learning processes. It’s like asking someone to learn to ride a bike over and over again from scratch. Adapting an artificial learning system to work smoothly with the brain’s sophisticated long-term learning schemas is something that’s never been shown before in a paralyzed person.
The system uses an electrocorticography (ECoG ) array about the size of a Post-it note. The array is placed directly on the surface of the brain, where it monitors electrical activity from the cerebral cortex.