Brain-machine interfaces could someday be used routinely to help paralyzed patients and amputees control prosthetic limbs with just their thoughts. Now, University of Florida researchers have devised a way for computerized devices not only to translate brain signals into movement, but also to evolve with the brain as it learns.
“The status quo of brain-machine interfaces that are out there have static and fixed decoding algorithms, which assume a person thinks one way for all time,” said Justin C. Sanchez, a UF assistant professor of pediatric neurology. Sanchez and his colleagues developed a system based on setting goals and giving rewards. Fitted with electrodes in their brains to capture signals for the computer to unravel, three rats were taught to move a robotic arm toward a target with just their thoughts. “We think this dialogue with a goal is how we can make these systems evolve over time,” Sanchez said.