Home Business News APL developing non-invasive brain computer interfaces to control complex systems

APL developing non-invasive brain computer interfaces to control complex systems

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With a recent award from the Defense Advanced Research Projects Agency (DARPA), researchers from the Johns Hopkins University Applied Physics Laboratory (APL), in Laurel, will develop a brain-machine interface (BMI) that will enable the control of complex systems at the speed of thought.

Today’s most promising BMI systems rely on microelectrodes that are surgically implanted into the brain. These systems closely monitor single neurons and neural populations, extract features from neural signals that reflect the user’s intent, translate these features into actions – such as typing on a virtual keyboard, controlling a prosthetic limb or piloting a simulated aircraft – and send feedback to the brain through stimulation.

“Implanted BMIs are beginning to prove useful for clinical populations – where the risks of brain surgery may be justified – to improve mood, memory, pain, communication and mobility. But only nonsurgical approaches can scale to the wider population,” said APL Program Manager Michael Wolmetz, who has a doctorate in cognitive science. “Fundamental limitations in the physics and neuroscience behind today’s best nonsurgical methods tell us that major advances are needed to approach the spatial resolution, temporal resolution and signal quality of invasive BMIs in a noninvasive, portable system.”

To make those major advances, APL researchers have embarked on a four-year project as part of DARPA’s Next-Generation Nonsurgical Neurotechnology (or N3) program, with the ambitious goal of developing a completely noninvasive, bidirectional neural interface.

The APL team is using coherent optical approaches to measure changes in the properties of the light that occur during scattering from tissue during neural activity. This effort is based on one of the laboratory’s recent discoveries: a breakthrough in coherent imaging – the ability to detect both the magnitude and phase of the scattered light – that makes it possible to noninvasively record optical signatures of neural activity at high spatial and temporal resolutions that approach those achieved using invasive techniques.

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