July 2012

Major advances over the past few years in brain:machine interfaces (BMIs) have shown that cortical signals in physically able, nonhuman primates can be translated into movement of a robotic arm, and BMIs can enable people with long-standing tetraplegia to move and click a computer cursor and to control physical devices. In this study, Hochberg and colleagues demonstrate the ability of two people with long-standing tetraplegia (ages 58 years and 66 years, both with paralysis from brainstem strokes) to use BMI-based control of a robotic arm to perform three-dimensional reach and grasp movements. Participants controlled the arm and hand over a broad space without explicit training, using signals decoded from a small, local population of motor cortex neurons recorded from a 96-channel microelectrode array. One of the study participants, implanted with the BMI 5 years earlier, also used a robotic arm to drink coffee from a bottle. Although robotic reach and grasp actions were not as fast or accurate as those of an ablebodied person, these results demonstrate the feasibility for people with tetraplegia, years after injury to the central nervous system, and with BMIs that have been implanted for years, to recreate useful multidimensional control of complex devices directly from a small sample of neural signals (Nature 2012;485:372–375).