title: Dynamic estimation of task-relevant variance in movement under risk.
abstract: Humans take into account their own movement variability as well as potential consequences of different movement outcomes in planning movement trajectories. When variability increases, planned movements are altered so as to optimize expected consequences of the movement. Past research has focused on the steady-state responses to changing conditions of movement under risk. Here, we study the dynamics of such strategy adjustment in a visuomotor decision task in which subjects reach toward a display with regions that lead to rewards and penalties, under conditions of changing uncertainty. In typical reinforcement learning tasks, subjects should base subsequent strategy by computing an estimate of the mean outcome (e.g., reward) in recent trials. In contrast, in our task, strategy should be based on a dynamic estimate of recent outcome uncertainty (i.e., squared error). We find that subjects respond to increased movement uncertainty by aiming movements more conservatively with respect to penalty regions, and that the estimate of uncertainty they use is well characterized by a weighted average of recent squared errors, with higher weights given to more recent trials.
authors.affiliation: Department of Psychology and Center for Neural Science, New York University, New York, New York 10003, USA. landy@nyu.edu
authors.forename: Michael S
authors.initials: MS
authors.lastname: Landy
authors.forename: Julia
authors.initials: J
authors.lastname: Trommershäuser
authors.forename: Nathaniel D
authors.initials: ND
authors.lastname: Daw
mesh_terms: D003463:Cues; D003657:Decision Making / Q000502:physiology*; D005260:Female; D006801:Humans; D007858:Learning / Q000502:physiology*; D008297:Male; D009068:Movement / Q000502:physiology*; D011597:Psychomotor Performance / Q000502:physiology*; D012309:Risk-Taking; D014796:Visual Perception / Q000502:physiology*; D055815:Young Adult