title: The preference of probability over negative values in action selection.
abstract: It has previously been found that when participants are presented with a pair of motor prospects, they can select the prospect with the largest maximum expected gain (MEG). Many of those decisions, however, were trivial because of large differences in MEG between the prospects. The purpose of the present study was to explore participants' preferences when making non-trivial decisions between two motor prospects. Participants were presented with pairs of prospects that: 1) differed in MEG with either only the values or only the probabilities differing between the prospects; and 2) had similar MEG with one prospect having a larger probability of hitting the target and a higher penalty value and the other prospect a smaller probability of hitting the target but a lower penalty value. In different experiments, participants either had 400 ms or 2000 ms to decide between the prospects. It was found that participants chose the configuration with the larger MEG more often when the probability varied between prospects than when the value varied. In pairs with similar MEGs, participants preferred a larger probability of hitting the target over a smaller penalty value. These results indicate that participants prefer probability information over negative value information in a motor selection task.
authors.affiliation: a Centre for Motor Control, Faculty of Kinesiology and Physical Education , University of Toronto , Toronto , Canada.
authors.forename: Heather F
authors.initials: HF
authors.lastname: Neyedli
authors.forename: Timothy N
authors.initials: TN
authors.lastname: Welsh
mesh_terms: D000328:Adult; D003657:Decision Making / Q000502:physiology*; D030141:Feedback, Psychological; D005260:Female; D006801:Humans; D008297:Male; D010465:Perception / Q000502:physiology*; D010775:Photic Stimulation; D011336:Probability; D011597:Psychomotor Performance; D011678:Punishment; D011930:Reaction Time; D012306:Risk; D055815:Young Adult
keywords: Decision-making; Manual aiming; Optimality; Statistical decision theory