Ongoing, rational calibration of reward-driven perceptual biases
Abstract
Decision-making is often interpreted in terms of normative computations that maximize a particular reward function for stable, average behaviors. Aberrations from the reward-maximizing solutions, either across subjects or across different sessions for the same subject, are often interpreted as reflecting poor learning or physical limitations. Here we show that such aberrations may instead reflect the involvement of additional satisficing and heuristic principles. For an asymmetric-reward perceptual decision-making task, three monkeys produced adaptive biases in response to changes in reward asymmetries and perceptual sensitivity. Their choices and response times were consistent with a normative accumulate-to-bound process. However, their context-dependent adjustments to this process deviated slightly but systematically from the reward-maximizing solutions. These adjustments were instead consistent with a rational process to find satisficing solutions based on the gradient of each monkey's reward-rate function. These results suggest new dimensions for assessing the rational and idiosyncratic aspects of flexible decision-making.
Data availability
Raw data used during this study are included as the supporting files.
Article and author information
Author details
Funding
National Eye Institute (R01-EY022411)
- Joshua I Gold
- Long Ding
University of Pennsylvania (University Research Foundation Pilot Award)
- Long Ding
Hearst Foundations (Graduate student fellowship)
- Yunshu Fan
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: All training and experimental procedures were in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals and were approved by the University of Pennsylvania Institutional Animal Care and Use Committee (#804726).
Copyright
© 2018, Fan et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Further reading
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