Reward-dependent modulation of movement variability.
Movement variability is often considered an unwanted byproduct of a noisy nervous system. However, variability can signal a form of implicit exploration, indicating that the nervous system is intentionally varying the motor commands in search of actions that yield the greatest success. Here, we investigated the role of the human basal ganglia in controlling reward-dependent motor variability as measured by trial-to-trial changes in performance during a reaching task. We designed an experiment in which the only performance feedback was success or failure and quantified how reach variability was modulated as a function of the probability of reward. In healthy controls, reach variability increased as the probability of reward decreased. Control of variability depended on the history of past rewards, with the largest trial-to-trial changes occurring immediately after an unrewarded trial. In contrast, in participants with Parkinson's disease, a known example of basal ganglia dysfunction, reward was a poor modulator of variability; that is, the patients showed an impaired ability to increase variability in response to decreases in the probability of reward. This was despite the fact that, after rewarded trials, reach variability in the patients was comparable to healthy controls. In summary, we found that movement variability is partially a form of exploration driven by the recent history of rewards. When the function of the human basal ganglia is compromised, the reward-dependent control of movement variability is impaired, particularly affecting the ability to increase variability after unsuccessful outcomes.
Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland 21205, and sep205@gmail.com.
Sarah E
SE
Pekny
Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland 21205, and Faculty of Engineering, Information and Systems, University of Tsukuba, Ibaraki 305-8573, Japan.
Jun
J
Izawa
Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland 21205, and.
Reza
R
Shadmehr
D000368:Aged; D000375:Aging / Q000523:psychology; D003213:Conditioning, Psychological / Q000502:physiology; D025461:Feedback, Physiological; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009068:Movement; D010300:Parkinson Disease / Q000503:physiopathology* / Q000523:psychology*; D011597:Psychomotor Performance / Q000502:physiology; D011930:Reaction Time; D012201:Reward; D013028:Space Perception
Parkinson's disease; computational models; motor control; reaching