Velocity neurons improve performance more than goal or position neurons do in a simulated closed-loop BCI arm-reaching task.

ABSTRACT: Brain-Computer Interfaces (BCIs) that convert brain-recorded neural signals into intended movement commands could eventually be combined with Functional Electrical Stimulation to allow individuals with Spinal Cord Injury to regain effective and intuitive control of their paralyzed limbs. To accelerate the development of such an approach, we developed a model of closed-loop BCI control of arm movements that (1) generates realistic arm movements (based on experimentally measured, visually-guided movements with real-time error correction), (2) simulates cortical neurons with firing properties consistent with literature reports, and (3) decodes intended movements from the noisy neural ensemble. With this model we explored (1) the relative utility of neurons tuned for different movement paramet

SUBMITTER: Liao JY 

PROVIDER: S-EPMC4500927 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature