title: Human representation of visuo-motor uncertainty as mixtures of orthogonal basis distributions.
abstract: In many laboratory visuo-motor decision tasks, subjects compensate for their own visuo-motor error, earning close to the maximum reward possible. To do so, they must combine information about the distribution of possible error with values associated with different movement outcomes. The optimal solution is a potentially difficult computation that presupposes knowledge of the probability density function (pdf) of visuo-motor error associated with each possible planned movement. It is unclear how the brain represents such pdfs or computes with them. In three experiments, we used a forced-choice method to reveal subjects' internal representations of their spatial visuo-motor error in a speeded reaching movement. Although subjects' objective distributions were unimodal, close to Gaussian, their estimated internal pdfs were typically multimodal and were better described as mixtures of a small number of distributions differing only in location and scale. Mixtures of a small number of uniform distributions outperformed other mixture distributions, including mixtures of Gaussians.
authors.affiliation: 1] Department of Psychology and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China. [2] PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China. [3] Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China. [4] Department of Psychology, New York University, New York, New York, USA. [5] Center for Neural Science, New York University, New York, New York, USA. [6] Institute for the Interdisciplinary Study of Decision Making, New York University, New York, New York, USA.
authors.forename: Hang
authors.initials: H
authors.lastname: Zhang
authors.affiliation: 1] Department of Psychology, New York University, New York, New York, USA. [2] Center for Neural Science, New York University, New York, New York, USA. [3] Institute for the Interdisciplinary Study of Decision Making, New York University, New York, New York, USA.
authors.forename: Nathaniel D
authors.initials: ND
authors.lastname: Daw
authors.affiliation: 1] Department of Psychology, New York University, New York, New York, USA. [2] Center for Neural Science, New York University, New York, New York, USA. [3] Institute for the Interdisciplinary Study of Decision Making, New York University, New York, New York, USA.
authors.forename: Laurence T
authors.initials: LT
authors.lastname: Maloney
mesh_terms: D000293:Adolescent; D000328:Adult; D001499:Bayes Theorem; D002755:Choice Behavior / Q000502:physiology; D003657:Decision Making / Q000502:physiology*; D005260:Female; D006801:Humans; D008297:Male; D016011:Normal Distribution; D011597:Psychomotor Performance / Q000502:physiology*; D016008:Statistical Distributions; D035501:Uncertainty; D055815:Young Adult