ArticleScience advances2021
Two sides of the same coin: Beneficial and detrimental consequences of range adaptation in human reinforcement learning.
Article in Science advances, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
25 citing papers in PubMed, 61 citations in OpenAlex.
- Article
- Attention modulates value normalization in human reinforcement learning by shaping reward encoding.Nature communications · 2026Article
- Reference-point dependent reinforcement learning in humans and rats.Nature communications · 2026Article
- Context induces distortions in value representations across multiple elicitation methods and learning modalities.Nature communications · 2026Article
- Article
- Feedback-induced attitudinal changes in risk preferences.Nature communications · 2026Article
- Action repetition biases choice in context-dependent decision-making.Communications psychology · 2025Article
- Social inequity disrupts reward-based learning.Communications psychology · 2025Article
- Estimation-uncertainty affects decisions with and without learning opportunities.Nature communications · 2025Article
- The timescale and direction of influence of a third inferior alternative in human value-learning.Communications psychology · 2025Article
- Relative Value Encoding in Large Language Models: A Multi-Task, Multi-Model Investigation.Open mind : discoveries in cognitive science · 2025Article
- Human reinforcement learning processes and biases: computational characterization and possible applications to behavioral public policy.Mind & society · 2025Article
- Comparing experience- and description-based economic preferences across 11 countries.Nature human behaviour · 2024Article
- Recent Opioid Use Impedes Range Adaptation in Reinforcement Learning in Human Addiction.Biological psychiatry · 2024Article
- Foraging in a non-foraging task: Fitness maximization explains human risk preference dynamics under changing environment.PLoS computational biology · 2024Article
- The Future of Decisions From Experience: Connecting Real-World Decision Problems to Cognitive Processes.Perspectives on psychological science : a journal of the Association for Psychological Science · 2024Article
- Article
- Article
- Context-independent scaling of neural responses to task difficulty in the multiple-demand network.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- Experiential values are underweighted in decisions involving symbolic options.Nature human behaviour · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Evidence suggests that economic values are rescaled as a function of the range of the available options. Although locally adaptive, range adaptation has been shown to lead to suboptimal choices, particularly notable in reinforcement learning (RL) situations when options are extrapolated from their original context to a new one. Range adaptation can be seen as the result of an adaptive coding process aiming at increasing the signal-to-noise ratio. However, this hypothesis leads to a counterintuitive prediction: Decreasing task difficulty should increase range adaptation and, consequently, extrapolation errors. Here, we tested the paradoxical relation between range adaptation and performance in a large sample of participants performing variants of an RL task, where we manipulated task difficulty. Results confirmed that range adaptation induces systematic extrapolation errors and is stronger when decreasing task difficulty. Last, we propose a range-adapting model and show that it is able to parsimoniously capture all the behavioral results.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.