Ultra-low power brain implants find meaningful signal in grey matter noise

By | July 28, 2020
Concept illustration of a brain and neural network.
(Public Domain)

Drastically reducing the power and computation needed to identify our intentions, researchers open up a future of advanced therapies and machines enabled by our thoughts.

By tuning into a subset of brain waves, University of Michigan researchers have dramatically reduced the power requirements of neural interfaces while improving their accuracy—a discovery that could lead to long-lasting brain implants that can both treat neurological diseases and enable mind-controlled prosthetics and machines.