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Statistical decision theory and the selection of rapid, goal-directed movements
Abstract
We present two experiments that test the range of applicability of a movement planning model (MEGaMove) based on statistical decision theory. Subjects attempted to earn money by rapidly touching a green target region on a computer screen while avoiding nearby red penalty regions. In two experiments we varied the magnitudes of penalties, the degree of overlap of target and penalty regions, and the number of penalty regions. Overall, subjects acted so as to maximize gain in a wide variety of stimulus configurations, in good agreement with predictions of the model.
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Cited by
The Bayesian brain: The role of uncertainty in neural coding and computation
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Metadata
- Authors
- Trommershäuser, J., Maloney, L. T., & Landy, M. S.
- Venue
- Journal of the Optical Society of America A
- Publisher
- Optica Publishing Group
- Published
- 2003-07-01
- Volume
- 20
- Issue
- 7
- Pages
- 1419
- ISSN
- 1084-7529 (ISSN-L)
- 1520-8532
- OpenAlex
- W1971904523
- Cited by
- 283
- References
- 4
- FWCI
- 3.07
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- doi.org/10.1364/OA_License_v1#VOR (vor)
- opg.optica.org/policies/opg-tdm-policy.json (tdm)
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- Trommershäuser, J., Maloney, L. T., & Landy, M. S. (2003). Statistical decision theory and the selection of rapid, goal-directed movements. Journal of the Optical Society of America A. https://doi.org/10.1364/josaa.20.001419
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