Brain-Machine Interfaces Based on Neuronal Ensemble Recordings

Brain-machine interfaces (BMIs) have experienced an explosive development during the last decade. Current state of the art BMIs convert neuronal ensemble activity recorded in nonhuman primates or human subjects into reaching and grasping movements performed by artificial actuators. BMIs that enact movements of lower extremeties are less explored. Additionally, most BMI implementations do not have somatosensory feedback from the actuator. I will review our recent experiments in which we (i) extracted bipedal locomotion patterns from monkey cortical activity and (ii) used spatiotemporal patterns of intracortical microstimulation to deliver information back to the brain. These results bring us closer to building clinical neuroprosthetic devices for restoration of both sensory and motor functions in paralyzed people.