The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.
The Drift Diffusion Model can account for the accuracy and reaction time of value-based choices under high and low time pressure
Open accessAbstract
An important open problem is how values are compared to make simple choices. A natural hypothesis is that the brain carries out the computations associated with the value comparisons in a manner consistent with the Drift Diffusion Model (DDM), since this model has been able to account for a large amount of data in other domains. We investigated the ability of four different versions of the DDM to explain the data in a real binary food choice task under conditions of high and low time pressure. We found that a seven-parameter version of the DDM can account for the choice and reaction time data with high-accuracy, in both the high and low time pressure conditions. The changes associated with the introduction of time pressure could be traced to changes in two key model parameters: the barrier height and the noise in the slope of the drift process.
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Heitz, R. P. (2014) · Frontiers in Neuroscience · doi:10.3389/fnins.2014.00150 · Cited by 938
Rats and Humans Can Optimally Accumulate Evidence for Decision-Making
Brunton, B. W., Botvinick, M. M., & Brody, C. D. (2013) · Science · doi:10.1126/science.1233912 · Cited by 620
Mechanisms underlying cortical activity during value-guided choice
Hunt, L. T., Kolling, N., Soltani, A., Woolrich, M. W., Rushworth, M. F. S., & Behrens, T. E. J. (2012) · Nature Neuroscience · doi:10.1038/nn.3017 · Cited by 454
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Metadata
- Authors
- Milosavljevic, M., Malmaud, J., Huth, A., Koch, C., & Rangel, A.
- Venue
- Judgment and Decision Making
- Publisher
- Cambridge University Press (CUP)
- Published
- 2010-10
- Volume
- 5
- Issue
- 6
- Pages
- 437-449
- ISSN
- 1930-2975 (ISSN-L)
- OpenAlex
- W3124291092
- Cited by
- 319
- References
- 53
- FWCI
- 6.70
- Type
- journal article
- Language
- en
- Open access
- gold
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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