A team of engineers at the University of Houston (UH) have reported that a brain-computer interface (BCI) can sense when its user is expecting a reward by examining the interactions between single-neuron activities and the information flowing to these neurons, called the local field potential.
Joe Francis, PhD, professor of biomedical engineering at the UH Cullen College of Engineering, reports his team’s findings allow for the development of an autonomously updating BCI that improves on its own, learning about its subject without having to be programed.
The findings potentially have applications for robotic prostheses, which would sense what a user wants to do such as pick up a glass and do it, the researchers found. The work represents a significant step forward for prostheses that perform more naturally, Francis said. “This will help prosthetics work the way the user wants them to,” he said. “The BCI quickly interprets what you’re going to do and what you expect as far as whether the outcome will be good or bad.”
To understand the effects of reward on the brain’s primary motor cortex activity, Francis and his team used implanted electrodes to investigate brainwaves and spikes in brain activity while tasks were performed to see how interactions are modulated by conditioned reward expectations.
“We assume intention is in there, and we decode that information by an algorithm and have it control either a computer cursor, for example, or a robotic arm,” said Francis, who also reported that even when the task called for no movement, passively observing an activity for example, the BCI was able to determine intention because the pattern of neural activity resembled that during movement.
“This is important because we are going to have to extract this information and brain activity out of people who cannot actually move, so this is our way of showing we can still get the information even if there is no movement,” he said.
The study was published online in eNeuro.
Editor’s note: This story was adapted from materials provided by University of Houston
