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Perceptual decisions under risk in a motion extrapolation paradigm
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Shah, Shalin. Perceptual decisions under risk in a motion extrapolation paradigm. Retrieved from https://doi.org/doi:10.7282/T3X0677S

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TitlePerceptual decisions under risk in a motion extrapolation paradigm
NameShah, Shalin (author); Singh, Manish (chair); Kowler, Eileen (internal member); Feldman, Jacob (internal member); Rutgers University; Graduate School - New Brunswick
Date Created
Other Date2008-10 (degree)
SubjectPsychology, Decision making--Psychological aspects
Extentiii, 50 p. : ill.
DescriptionClassical work on decision-making has demonstrated systematic deviations from normative behavior. Recent experiments on movement planning, however, have shown that subjects can be indistinguishable from optimality in their visuo-motor decisions (Trommershaeuser et al., 2003a, 2003b). Unlike the classical case, the uncertainty in the visuo-motor case is internal to the subjects; it arises from their motor
variability—variability in executing a motor action.
We asked whether observers can also combine the intrinsic variability in their perceptual representation with externally-specified reward-and-penalty structure to make optimal decisions. We extended a paradigm used to study the visual extrapolation of static contour geometry (Singh & Fulvio, 2005), to examine observers’ decisions under risk in extrapolating curved motion trajectories.
Observers viewed a dot moving along a parabolic trajectory disappear behind the straight-edge of a half-disk occluder. Their task was to “catch” the dot from the opposite curved side, by adjusting the angular position of an arc or “mitt”. In the risky conditions, a double-mitt was used, comprising a green reward region and a red penalty region, with partial overlap.
Observers’ gains/losses were determined by the part of the double-mitt that “caught” the dot. Variables manipulated were: trajectory curvature, penalty value, and mitt overlap.
Observers’ performance in the baseline condition was used to estimate individual bias and variability. Based on these, predictions of optimal shift and optimal score were computed, using maximization of expected gain.
We found that observed shifts were well predicted by optimal shifts. Moreover, observer efficiency (observed/optimal score) was high (80% - 114%). The results indicate that observers are implicitly aware of the instrinsic variability in their perceptual representation, and can combine it with externally-specified reward-and-penalty structure to make near-
optimal decisions.
NoteM.S.
NoteIncludes bibliographical references (p. 49-50)
Noteby Shalin Shah
Genretheses, ETD graduate
Persistent URLhttps://doi.org/doi:10.7282/T3X0677S
Languageeng
CollectionGraduate School - New Brunswick Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
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