The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
The physics of optimal decision making: A formal analysis of models of performance in two-alternative forced-choice tasks.
Abstract
In this article, the authors consider optimal decision making in two-alternative forced-choice (TAFC) tasks. They begin by analyzing 6 models of TAFC decision making and show that all but one can be reduced to the drift diffusion model, implementing the statistically optimal algorithm (most accurate for a given speed or fastest for a given accuracy). They prove further that there is always an optimal trade-off between speed and accuracy that maximizes various reward functions, including reward rate (percentage of correct responses per unit time), as well as several other objective functions, including ones weighted for accuracy. They use these findings to address empirical data and make novel predictions about performance under optimality.
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Citations
Cites
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Self-citationConflict monitoring versus selection-for-action in anterior cingulate cortex
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Self-citationNeural Basis of a Perceptual Decision in the Parietal Cortex (Area LIP) of the Rhesus Monkey
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“Throughout, we restrict our formal presentation to the most important equations, and where possible we provide intuitive explanations.”
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Cited by
CIDEr: Consensus-based image description evaluation
Vedantam, R., Zitnick, C. L., & Parikh, D. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7299087 · Cited by 4,845
The Diffusion Decision Model: Theory and Data for Two-Choice Decision Tasks
Ratcliff, R., & McKoon, G. (2008) · Neural Computation · doi:10.1162/neco.2008.12-06-420 · Cited by 3,059
The expected value of control: an integrative theory of anterior cingulate cortex function
Shenhav, A., Botvinick, M. M., & Cohen, J. D. (2013) · Neuron · doi:10.1016/j.neuron.2013.07.007 · Cited by 2,321
Self-citationDecision making, the P3, and the locus coeruleus–norepinephrine system
Nieuwenhuis, S., Aston-Jones, G., & Cohen, J. D. (2005) · Psychological Bulletin · doi:10.1037/0033-2909.131.4.510 · Cited by 1,678
Self-citationDiffusion decision model: Current issues and history
Ratcliff, R., Smith, P. L., Brown, S. D., & McKoon, G. (2016) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2016.01.007 · Cited by 1,630
“A pure (Wiener) diffusion process, with no across-trial variability, can be viewed as a continuous-time log-likelihood ratio accumulator, and is optimal in the same sense [72,73].”
Background
Metadata
- Authors
- Bogacz, R., Brown, E., Moehlis, J., Holmes, P., & Cohen, J. D.
- Venue
- Psychological Review
- Published
- 2006
- Volume
- 113
- Issue
- 4
- Pages
- 700-765
- ISSN
- 0033-295X (ISSN-L)
- 1939-1471
- OpenAlex
- W2066931620
- Cited by
- 1,866
- References
- 20
- FWCI
- 17.04
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: The physics of optimal decision making: A formal analysis of models of performance in two-alternative forced-choice tasks. https://app.cochat.ai/papers/10.1037/0033-295x.113.4.700
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- Bogacz, R., Brown, E., Moehlis, J., Holmes, P., & Cohen, J. D. (2006). The physics of optimal decision making: A formal analysis of models of performance in two-alternative forced-choice tasks. Psychological Review. https://doi.org/10.1037/0033-295x.113.4.700
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
