Discounting future reward in an uncertain world
Creators
Abstract
Humans discount delayed relative to more immediate reward. A plausible explanation is that impatience arises partly from uncertainty, or risk, implicit in delayed reward. Existing theories of discounting-as-risk focus on a probability that delayed reward will not materialize. By contrast, we examine how uncertainty in the magnitude of delayed reward contributes to delay discounting. We propose a model wherein reward is discounted proportional to the rate of random change in its magnitude across time, termed volatility. We find evidence to support this model across three experiments (total N = 158). First, using a task where participants chose when to sell products, whose price dynamics they previously learned, we show discounting increases in line with price volatility. Second, we show that this effect pertains over naturalistic delays of up to 4 months. Using functional magnetic resonance imaging, we observe a volatility-dependent decrease in functional hippocampal–prefrontal coupling during intertemporal choice. Third, we replicate these effects in a larger online sample, finding that volatility discounting within each task correlates with baseline discounting outside of the task. We conclude that delay discounting partly reflects time-dependent uncertainty about reward magnitude, that is volatility. Our model captures how discounting adapts to volatility, thereby partly accounting for individual differences in impatience. Our imaging findings suggest a putative mechanism whereby uncertainty reduces prospective simulation of future outcomes.
Additional Information
© 2023 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0; http://creativecommons.org/licenses/by/4.0). This license permits copying and redistributing the work in any medium or format, as well as adapting the material for any purpose, even commercially. The authors would like to thank Peter Zeidman for his advice on the neuroimaging analyses. This work was supported by the Wellcome Trust (R. J. Dolan Investigator Award 098362/Z/12/Z) and the Max Planck Society. The Wellcome Trust Centre for Neuroimaging is supported by core funding from the Wellcome Trust 091593/Z/10/Z. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the article. Data from this study were presented as a poster at the 74th Annual Meeting of the Society of Biological Psychiatry, 2019. Behavioral data supporting the findings of this study are publicly available online in a third-party repository: https://doi.org/10.5061/dryad.47d7wm3k2 (G. Story, 2023). Imaging data are available from the corresponding author upon reasonable request. Computer codes that support the findings of this study are available from the corresponding author upon reasonable request.G. W. Story played a lead role in conceptualization, data curation, formal analysis, investigation, methodology, software, and writing–original draft. G. W. Story, Z. Kurth-Nelson, K. Iigaya, M. Moutoussis, I. Vlaev, and R. J. Dolan designed the experiments. G. W. Story coded the experimental protocols. G. W. Story, Z. Kurth-Nelson, M. Moutoussis, and G.-J. Will collected the data. G. W. Story analyzed the data and wrote a draft article. T. U. Hauser, Z. Kurth-Nelson, K. Iigaya, M. Moutoussis, I. Vlaev, and R. J. Dolan provided feedback and conceptual contributions to data analysis. B. Blain provided code for an adaptive intertemporal choice procedure. All authors edited the article.Attached Files
Supplemental Material - DEC-2022-0233_Supplemental_materials_dec0000219.docx
In Press - 2023-86785-001.pdf
Files
2023-86785-001.pdf
Additional details
Identifiers
- Eprint ID
- 122340
- Resolver ID
- CaltechAUTHORS:20230717-55915200.37
Related works
- Describes
- 10.5061/dryad.47d7wm3k2 (DOI)
Funding
- Wellcome Trust
- 098362/Z/12/Z
- Max Planck Society
- Wellcome Trust
- 091593/Z/10/Z
- University College London
Dates
- Created
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2023-07-18Created from EPrint's datestamp field
- Updated
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2023-10-23Created from EPrint's last_modified field