Optimal Compensation for Temporal Uncertainty in Movement Planning

• Published in: PLoS computational biology Vol. 4; no. 7; p. e1000130
• Main Authors: Hudson, Todd E., Maloney, Laurence T., Landy, Michael S.
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 01.07.2008; Public Library of Science (PLoS)
• Subjects: Arm; Biomechanical Phenomena; Compensation; Computational biology; Computational Biology/Computational Neuroscience; Costs; Decision theory; Feedback, Psychological - physiology; Fines & penalties; Hand; Human mechanics; Human subjects; Humans; Mathematical models; Models, Biological; Motor ability; Motor Activity - physiology; Movement - physiology; Neuroscience/Behavioral Neuroscience; Neuroscience/Motor Systems; Neuroscience/Sensory Systems; Neuroscience/Theoretical Neuroscience; Orientation - physiology; Physiological aspects; Probability; Proprioception - physiology; Psychomotor Performance - physiology; Reaction Time - physiology; Reference Values; Reward; Standard deviation; Studies; Time Factors; United States; Psychomotor Performance; Movement; Proprioception; Humans; Reaction Time; Reference Values; Motor Activity; Orientation; Feedback, Psychological; Hand; Biomechanical Phenomena; Time Factors; Models, Biological; Reward; Arm
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1000130

Motor control requires the generation of a precise temporal sequence of control signals sent to the skeletal musculature. We describe an experiment that, for good performance, requires human subjects to plan movements taking into account uncertainty in their movement duration and the increase in that uncertainty with increasing movement duration. We do this by rewarding movements performed within a specified time window, and penalizing slower movements in some conditions and faster movements in others. Our results indicate that subjects compensated for their natural duration-dependent temporal uncertainty as well as an overall increase in temporal uncertainty that was imposed experimentally. Their compensation for temporal uncertainty, both the natural duration-dependent and imposed overall components, was nearly optimal in the sense of maximizing expected gain in the task. The motor system is able to model its temporal uncertainty and compensate for that uncertainty so as to optimize the consequences of movement.