Army-Funded Algorithm Decodes Brain Signals
The algorithm is part of an effort to eventually establish a machine-brain interface.
By Mila Jasper
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. The research, which used standard brain datasets for analysis, was recently published in the journal Nature Neuroscience.
“Our algorithm can, for the first time, dissociate the dynamic patterns in brain signals that relate to specific behaviors and is much better at decoding these behaviors,” Dr. Maryam Shanechi, the engineering professor at the University of Southern California who led the research, said in a statement.
Dr. Hamid Krim, a program manager at the Army Research Office, part of the U.S. Army Combat Capabilities Development Command’s Army Research Laboratory, told Nextgov Shanechi and her team used the algorithm to separate what they call behaviorally relevant brain signals from behaviorally irrelevant brain signals.
“This presents a potential way of reliably measuring, for instance, the mental overload of an individual, of a soldier,” Krim said.