ArticlePLoS computational biology2019
Improving the reliability of model-based decision-making estimates in the two-stage decision task with reaction-times and drift-diffusion modeling.
Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 81 papers.
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Who cites it
81 citing papers in PubMed.
- The catecholamine precursor Tyrosine reduces autonomic arousal and decreases decision thresholds in reinforcement learning and temporal discounting.PLoS computational biology · 2022Trial
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- Modeling decision dynamics disentangles working memory, cognitive control and reinforcement learning and reveals clinical differences.PLoS computational biology · 2026Article
- Probing biomarkers and clinical utility of reward learning across species using the Probabilistic Reward Task: 20 years of findings.Nature. Mental health · 2026Article
- Domain-specific contexts promote model-based decision making for basketball players.Scientific reports · 2026Article
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- Deciding for others diminishes model-based decision-making but depends on individual prosociality.NPJ science of learning · 2026Article
- Attenuated learning rates for negative outcomes in substance use disorders: A replication and extension of prior longitudinal computational modeling results.Drug and alcohol dependence · 2026Article
- JOINT MODELING FOR LEARNING DECISION-MAKING DYNAMICS IN BEHAVIORAL EXPERIMENTS.The annals of applied statistics · 2025Article
- Attentional Mechanisms for Learning Feature Combinations.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Higher motivation and pleasure scores predict more reliance on model-free decision making.Cognitive, affective & behavioral neuroscience · 2025Article
- Joint models reveal human subcortical underpinnings of choice and learning behavior.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Better Than Maximum Likelihood Estimation of Model-based and Model-free Learning Styles.Basic and clinical neuroscience · 2025Article
- A task-invariant prior explains trial-by-trial active avoidance behaviour across gain and loss tasks.Communications psychology · 2025Article
- Day-to-day fluctuations in motivation drive effort-based decision-making.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Improving the Reliability of the Pavlovian Go/No-Go Task for Computational Psychiatry Research.Computational psychiatry (Cambridge, Mass.) · 2025Article
- Computational Mechanisms of Approach-Avoidance Conflict Predictively Differentiate Between Affective and Substance Use Disorders.Computational psychiatry (Cambridge, Mass.) · 2025Article
- Bayesian Workflow for Generative Modeling in Computational Psychiatry.Computational psychiatry (Cambridge, Mass.) · 2025Article
- Signatures of Perseveration and Heuristic-Based Directed Exploration in Two-Step Sequential Decision Task Behaviour.Computational psychiatry (Cambridge, Mass.) · 2025Article
- Cardiac-Sympathetic Contractility and Neural Alpha-Band Power: Cross-Modal Collaboration during Approach-Avoidance Conflict.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
21 more citing papers are in PubMed but not listed here.
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Authors and funding
7 authors.
Funding
Abstract
A well-established notion in cognitive neuroscience proposes that multiple brain systems contribute to choice behaviour. These include: (1) a model-free system that uses values cached from the outcome history of alternative actions, and (2) a model-based system that considers action outcomes and the transition structure of the environment. The widespread use of this distinction, across a range of applications, renders it important to index their distinct influences with high reliability. Here we consider the two-stage task, widely considered as a gold standard measure for the contribution of model-based and model-free systems to human choice. We tested the internal/temporal stability of measures from this task, including those estimated via an established computational model, as well as an extended model using drift-diffusion. Drift-diffusion modeling suggested that both choice in the first stage, and RTs in the second stage, are directly affected by a model-based/free trade-off parameter. Both parameter recovery and the stability of model-based estimates were poor but improved substantially when both choice and RT were used (compared to choice only), and when more trials (than conventionally used in research practice) were included in our analysis. The findings have implications for interpretation of past and future studies based on the use of the two-stage task, as well as for characterising the contribution of model-based processes to choice behaviour.
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