"Motor cortical control of movement speed with implications for brain-machine interface control"
Journal of Neurophysiology, 112:411-429
Mouse over here for a brief summary or click to open article in a new tab.We analyzed the extent to which movement-related information could be extracted from single-trial motor cortical activity recorded while monkeys performed center-out reaching, and found that single units carry relatively little speed-related information compared with direction-related information. This result is not mitigated at the population level: simultaneously recorded population activity predicted speed with significantly lower accuracy relative to direction predictions. These results inspired the design of a new brain-machine interface (BMI) decoding algorithm called the speed-dampening Kalman filter (SDKF) that automatically slows the cursor upon detecting changes in decoded movement direction. SDKF improved success rates by a factor of 1.7 relative to a standard Kalman filter in a closed-loop BMI task requiring stable stops at targets.