BCI senses expectations for more natural prosthetics

The BCI is said to examine the interactions between single-neuron activities and the information flowing to these neurons. The work from the University of Houston is reported in eNeuro.

Joe France, a Professor of biomedical engineering, reports that 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 programmed.

The results have potential applications for robotic prosthetics, which would sense what a user wants to do and then does it. The university claims the work represents a significant step forward for prosthetics that perform more naturally.

"This will help prosthetics work the way the user wants them to," said Francis. "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."

Francis said that information drives scientists' abilities to predict reward outcome to 97 per cent, up from the mid-70s. To understand the effects of reward on the brain's primary motor cortex activity, Francis 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.