Direct Cortical Control of 3D Neuroprosthetic Devices

• Published in: Science (American Association for the Advancement of Science) Vol. 296; no. 5574; pp. 1829 - 1832
• Main Authors: Taylor, Dawn M., Stephen I. Helms Tillery, Schwartz, Andrew B.
• Format: Journal Article
• Language: English
• Published: Washington, DC American Society for the Advancement of Science 07.06.2002; American Association for the Advancement of Science; The American Association for the Advancement of Science
• Subjects: Algorithms; Analysis; Animals; Arm - physiology; Biological and medical sciences; Brain; Cell lines; Computer Simulation; Control theory; Cosine function; Error Correction; Eyes & eyesight; Feedback; Free energy; Fundamental and applied biological sciences. Psychology; Hand - physiology; Higher nervous activity; Humans; Implants, Artificial; Learning; Macaca mulatta; Mathematics; Medical research; Medicine, Experimental; Motor control and motor pathways. Reflexes. Control centers of vegetative functions. Vestibular system and equilibration; Motor Cortex - cytology; Motor Cortex - physiology; Motor Neurons - physiology; Movement; Neurology; Neurons; Product development; Prostheses and Implants; Prosthesis; Prosthetics; Real time; Real time systems; Research Article; Sensory perception; T tests; Thermodynamic equilibrium; Thermodynamics; Trajectories; User-Computer Interface; Vertebrates: nervous system and sense organs; Visual Perception; United States; Motor pathway; Central nervous system; Monkey; Goal directed movement; Feedback regulation; Three dimensional space; Neuroprosthesis; Algorithm; Motor control; Vertebrata; Mammalia; Motor cortex; Body movement; Primates; Upper limb; Visuomotor control; Brain (vertebrata)
• ISSN: 0036-8075; 1095-9203
• DOI: 10.1126/science.1070291

Three-dimensional (3D) movement of neuroprosthetic devices can be controlled by the activity of cortical neurons when appropriate algorithms are used to decode intended movement in real time. Previous studies assumed that neurons maintain fixed tuning properties, and the studies used subjects who were unaware of the movements predicted by their recorded units. In this study, subjects had real-time visual feedback of their brain-controlled trajectories. Cell tuning properties changed when used for brain-controlled movements. By using control algorithms that track these changes, subjects made long sequences of 3D movements using far fewer cortical units than expected. Daily practice improved movement accuracy and the directional tuning of these units.