ArticleCurrent opinion in behavioral sciences2021
What do Reinforcement Learning Models Measure? Interpreting Model Parameters in Cognition and Neuroscience.
Article in Current opinion in behavioral sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.
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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.
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Who cites it
45 citing papers in PubMed.
- Representations of the intrinsic value of information in mouse orbitofrontal cortex.Nature neuroscience · 2026Article
- Feasible cognition requires latent state.Biological cybernetics · 2026Article
- The recoverability, reliability, and generalizability of reward processing parameters and relation to mental health symptoms.Psychological medicine · 2026Article
- Longitudinal analysis of decision-making deficits in binge-eating disorders using drift diffusion modeling.Appetite · 2026Article
- Reward-specific learning parameters change across normative adolescent development and are blunted in youth with high risk for depression.Journal of child psychology and psychiatry, and allied disciplines · 2026Article
- AI-Discovered Cognitive Models Reveal Novel Insights into Human and Animal Learning.bioRxiv : the preprint server for biology · 2026Article
- Modulation of feature attention by reward prediction error explains value learning behavior.bioRxiv : the preprint server for biology · 2026Article
- The role of dorsal anterior cingulate cortex in dynamic attitude changes in naturalistic settings.Communications biology · 2026Article
- Threading the Needle: Practical Considerations for Merging Theory-Driven Computational Psychiatry With Data-Driven Analytics to Enhance Precision Health at Scale.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2026Review
- A habit and working memory model as an alternative account of human reward-based learning.Nature human behaviour · 2026Article
- Anhedonic Traits Do Not Impair Performance in a 3-Arm Bandit Task.Computational psychiatry (Cambridge, Mass.) · 2026Article
- The distinct functions of working memory and intelligence in model-based and model-free reinforcement learning.NPJ science of learning · 2025Article
- An Information-Theoretic Framework for Understanding Learning and Choice Under Uncertainty.Entropy (Basel, Switzerland) · 2025Article
- Dual process impairments in reinforcement learning and working memory systems underlie learning deficits in physiological anxiety.PLoS computational biology · 2025Article
- Data-driven equation discovery reveals nonlinear reinforcement learning in humans.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- A Foraging-Theory-Based Model Captures the Spectrum of Human Behavioral Diversity in Sequential Decision Making.bioRxiv : the preprint server for biology · 2025Article
- Genetic changes linked to two different syndromic forms of autism enhance reinforcement learning in early adolescent male but not female mice.bioRxiv : the preprint server for biology · 2025Article
- Using an algorithmic approach to shape human decision-making through attraction to patterns.Nature communications · 2025Article
- A shared temporal window of integration across cognitive control and reinforcement learning paradigms: A correlational study.Memory & cognition · 2025Article
- Understanding learning through uncertainty and bias.Communications psychology · 2025Review
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Reinforcement learning (RL) is a concept that has been invaluable to fields including machine learning, neuroscience, and cognitive science. However, what RL entails differs between fields, leading to difficulties when interpreting and translating findings. After laying out these differences, this paper focuses on cognitive (neuro)science to discuss how we as a field might over-interpret RL modeling results. We too often assume-implicitly-that modeling results
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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.