Adaptation to a cortex-controlled robot attached at the pelvis and engaged during locomotion in rats.

Brain-machine interfaces (BMIs) should ideally show robust adaptation of the BMI across different tasks and daily activities. Most BMIs have used overpracticed tasks. Little is known about BMIs in dynamic environments. How are mechanically body-coupled BMIs integrated into ongoing rhythmic dynamics, for example, in locomotion? To examine this, we designed a novel BMI using neural discharge in the hindlimb/trunk motor cortex in rats during locomotion to control a robot attached at the pelvis. We tested neural adaptation when rats experienced (1) control locomotion, (2) "simple elastic load" (a robot load on locomotion without any BMI neural control), and (3) "BMI with elastic load" (in which the robot loaded locomotion and a BMI neural control could counter this load). Rats significantly offset applied loads with the BMI while preserving more normal pelvic height compared with load alone. Adaptation occurred over ∼100-200 step cycles in a trial. Firing rates increased in both the loaded conditions compared with baseline. Mean phases of the discharge of cells in the step cycle shifted significantly between BMI and the simple load condition. Over time, more BMI cells became positively correlated with the external force and modulated more deeply, and the network correlations of neurons on a 100 ms timescale increased. Loading alone showed none of these effects. The BMI neural changes of rate and force correlations persisted or increased over repeated trials. Our results show that rats have the capacity to use motor adaptation and motor learning to fairly rapidly engage hindlimb/trunk-coupled BMIs in their locomotion.