Learning and consolidation of visuo-motor adaptation in Parkinson's disease.
ABSTRACT We have previously shown in normal subjects that motor adaptation to imposed visual rotation is significantly enhanced when tested few days later. This occurs through a process of sleep-dependent memory consolidation. Here we ascertained whether patients with Parkinson's disease (PD) learn, improve, and retain new motor skills in the same way as normal subjects. We tested 16 patients in early stages of PD and 21 control subjects over two days. All subjects performed reaching movements on a digitizing tablet. Vision of the limb was precluded with an opaque screen; hand paths were shown on the screen with the targets' position. Unbeknownst to the subjects, the hand path on the screen was rotated by 30 degrees . In experiment 1, patients taking dopaminergic treatment and controls adapted to rotation with targets appearing in an unpredictable order. In experiment 2, drug-naïve patients and controls adapted to rotation in a less challenging task where target's appearance was predictable. Patients and controls made similar movements and adapted to rotation in the same way. However, when tested again over the following days, controls' performance significantly improved compared to training, while patients' performance did not. This lack of consolidation, which is present in the early stages of the disease and is independent from therapy, may be due to abnormal homeostatic processes that occur during sleep.
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ABSTRACT: Voluntary motor commands produce two kinds of consequences. Initially, a sensory consequence is observed in terms of activity in our primary sensory organs (e.g., vision, proprioception). Subsequently, the brain evaluates the sensory feedback and produces a subjective measure of utility or usefulness of the motor commands (e.g., reward). As a result, comparisons between predicted and observed consequences of motor commands produce two forms of prediction error. How do these errors contribute to changes in motor commands? Here, we considered a reach adaptation protocol and found that when high quality sensory feedback was available, adaptation of motor commands was driven almost exclusively by sensory prediction errors. This form of learning had a distinct signature: as motor commands adapted, the subjects altered their predictions regarding sensory consequences of motor commands, and generalized this learning broadly to neighboring motor commands. In contrast, as the quality of the sensory feedback degraded, adaptation of motor commands became more dependent on reward prediction errors. Reward prediction errors produced comparable changes in the motor commands, but produced no change in the predicted sensory consequences of motor commands, and generalized only locally. Because we found that there was a within subject correlation between generalization patterns and sensory remapping, it is plausible that during adaptation an individual's relative reliance on sensory vs. reward prediction errors could be inferred. We suggest that while motor commands change because of sensory and reward prediction errors, only sensory prediction errors produce a change in the neural system that predicts sensory consequences of motor commands.PLoS Computational Biology 03/2011; 7(3):e1002012. · 5.22 Impact Factor