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Value certainty in drift-diffusion models of preferential choice
1Division of the Humanities and Social Sciences.
Psychological Review
|October 25, 2021
Summary
The drift-diffusion model (DDM) was extended to account for varying certainty in value estimates across options. This enhanced DDM better explains choice consistency and response times in decision-making.
Area of Science:
- Cognitive Psychology
- Computational Neuroscience
- Decision Science
Background:
- The drift-diffusion model (DDM) is a prominent framework for understanding binary choices and response times.
- The standard DDM assumes uniform precision in value representations across options, which contradicts empirical observations of varying certainty.
Purpose of the Study:
- To extend the DDM by incorporating option-specific value certainty.
- To validate these extended DDM versions against empirical data from previous decision-making studies.
Main Methods:
- Developed several extensions of the DDM to include option-specific value certainty.
- Validated the proposed DDM variants using empirical data from four distinct studies.
Main Results:
- The data best supported a DDM version where evidence accumulation (drift) is based on a signal-to-noise ratio of option values.
- This enhanced DDM variant successfully accounts for the influence of value certainty on choice consistency and response times.
Conclusions:
- The inclusion of option-specific value certainty significantly improves the DDM's ability to model decision-making.
- The signal-to-noise ratio approach offers a more accurate representation of evidence accumulation in the presence of varying value precision.
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