System identification of brain-machine interface control using a cursor jump perturbation

Sergey D. Stavisky, Jonathan C. Kao, Jordan M. Sorokin, Stephen I. Ryu, Krishna V. Shenoy

Abstract: Inspired by control theoretic approaches to studying motor control, we experimentally measured how a brain-machine interface (BMI) user responds to an unexpected perturbation. We randomly applied a step cursor position offset while a monkey controlled a BMI cursor using decoded motor cortical spiking activity. The subject was able to rapidly correct for these perturbations and (re)acquire the target regardless of when in the trial this cursor jump occurred. We observed a corrective neural response in motor cortex starting 115 ms after the cursor jump. At no time did the neural response to detecting this externally-induced error manifest itself (through the decoder) as a deleterious velocity change pushing the cursor away from the target. These results show that a user of a high-performance BMI can make rapid, accurate corrections to errors and that, insofar as the neural computations needed to counteract the error may involve motor cortex, these computations do not appear to interfere with BMI cursor control.