Uncovering locomotor learning dynamics in people with Parkinson’s disease

Locomotor learning is important for improving gait and balance impairments in people with Parkinson’s disease (PD). While PD disrupts neural networks involved in motor learning, there is a limited understanding of how PD influences the time course of locomotor learning and retention. Here, we used a virtual obstacle negotiation task to investigate whether the early stages of PD affect the acquisition and retention of locomotor skills. On Day 1, 15 participants with PD (Hoehn and Yahr Stage 1–2) and 20 age-matched controls were instructed to achieve a specified level of foot clearance while repeatedly stepping over two different virtual obstacles on a treadmill. We assessed online performance improvement on Day 1 and overnight retention after at least 24 hours on Day 2. We used a hierarchical Bayesian state-space model to estimate the learning rate and the degree of interference between the two obstacles. There was a 93% probability that people with PD learned the locomotor skill faster than controls, but there was limited evidence of group differences in interference between the two heights of obstacles. Both groups improved their performance to a similar magnitude during skill acquisition and performed similarly during retention on Day 2. Notably, a slower learning rate was associated with greater online performance improvement, while lower interference was linked to better overnight retention, and this effect was strongest for the control group. These results highlight that people with early-stage PD retain the ability to use multisensory information to acquire and retain locomotor skills. In particular, our finding that people with early-stage PD learned faster than age-matched controls may reflect the emergence of compensatory motor learning strategies used to offset early motor impairments in people with PD.