A new machine-learning algorithm can successfully determine which specific behaviors--like walking and breathing--belong to which specific brain signal, and it has the potential to help the military maintain a more ready force. At any given time, people perform a myriad of tasks. All of the brain and behavioral signals associated with these tasks mix together to form a complicated web. Until now, this web has been difficult to untangle and translate. But researchers funded by the U.S. Army developed a machine-learning algorithm that can model and decode these signals, according to a Nov. 12 press release.

A machine learning algorithm has shown the ability to link specific behaviors, such as walking and breathing, to their related brain signals – a first step to developing brain-machine interfaces. The algorithm, funded by the US Army, was tested on two monkeys that made various arm and eye movements. The technology successfully isolated the neural patterns in each of the animal's brain signals and determined which control these specific movements. The brain decoding algorithm could be designed to restore lost functions in those suffering with neurological and mental disorders. Although the algorithm is still in the development phase, the team sees it being used in brain-machine interfaces.