title: Decision making, movement planning and statistical decision theory.
abstract: We discuss behavioral studies directed at understanding how probability information is represented in motor and economic tasks. By formulating the behavioral tasks in the language of statistical decision theory, we can compare performance in equivalent tasks in different domains. Subjects in traditional economic decision-making tasks often misrepresent the probability of rare events and typically fail to maximize expected gain. By contrast, subjects in mathematically equivalent movement tasks often choose movement strategies that come close to maximizing expected gain. We discuss the implications of these different outcomes, noting the evident differences between the source of uncertainty and how information about uncertainty is acquired in motor and economic tasks.
authors.affiliation: Giessen University, Department of Psychology, Otto-Behaghel-Str. 10F, 35394 Giessen, Germany. julia.trommershaeuser@psychol.uni-giessen.de
authors.forename: Julia
authors.initials: J
authors.lastname: Trommershäuser
authors.forename: Laurence T
authors.initials: LT
authors.lastname: Maloney
authors.forename: Michael S
authors.initials: MS
authors.lastname: Landy
mesh_terms: D003627:Data Interpretation, Statistical; D003657:Decision Making; D003662:Decision Theory; D006801:Humans; D009068:Movement; D012307:Risk Factors