UF scientists have designed a device that could someday be put into the brains of paralyzed patients and help them control mechanical devices with their thoughts.
A recent study found that the device, known as a brain-machine interface, could potentially lead paraplegic patients to mentally control prosthetic limbs.
The brain-machine interface would translate their thoughts directly to control communication devices such as a computer or a prosthetic and would even evolve with the brain as it learns, said Justin C. Sanchez, senior author of the study and an assistant professor of pediatric neurology at UF.
"We want to give people that are trapped in their bodies an alternative means to communicate and control things," Sanchez said.
Until recently, brain-machine interfaces had been designed as a one-way conversation between the computer and the brain, which sent all the commands while the computer simply followed them.
The new neural implant creates a two-way conversation between the computer and the brain, allowing the computer to be involved in the conversation as well, Sanchez said.
The brain-machine interfaces are surgically implanted in the body and would only be available for people who have lost complete control of their upper or lower body, such as paraplegic and quadriplegic patients, he said.
"This is the most debilitating scenario because people are what's called 'locked in' - all of their faculties are working in their brain, but they have no way of expressing it because their body is completely paralyzed," Sanchez said.
While brain-machine interfaces could help paralyzed patients, they could also benefit amputees, such as soldiers coming back from Iraq who have lost a limb during combat, he said.
It took 18 months and three rats as subjects for researchers to create this type of brain-machine interface.
Jack DiGiovanna, an engineering doctoral student who collaborated on the study, said this particular neural implant is only being tested on rats.
He said he hopes that it can someday be tried on humans, which has been the case with other brain-machine interfaces.
