ArticleDevelopmental cognitive neuroscience2017
Cognitive components underpinning the development of model-based learning.
Article in Developmental cognitive neuroscience, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 30 papers, 1 of them a synthesis that pooled it.
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Who cites it
30 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Spatial migration of human reward processing with functional development: Evidence from quantitative meta-analyses.Human brain mapping · 2020Pooled it
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- Data-driven equation discovery reveals nonlinear reinforcement learning in humans.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Characterizing age-related change in learning the value of cognitive effort.Journal of experimental psychology. General · 2025Article
- Disentangling the Component Processes in Complex Planning Impairments Following Ventromedial Prefrontal Lesions.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Maturation of striatal dopamine supports the development of habitual behavior through adolescence.bioRxiv : the preprint server for biology · 2025Article
- Decrease in decision noise from adolescence into adulthood mediates an increase in more sophisticated choice behaviors and performance gain.PLoS biology · 2024Article
- Sensitivity to the Instrumental Value of Choice Increases Across Development.Psychological science · 2024Article
- Goal-directed learning in adolescence: neurocognitive development and contextual influences.Nature reviews. Neuroscience · 2024Review
- Adolescents flexibly adapt action selection based on controllability inferences.Learning & memory (Cold Spring Harbor, N.Y.) · 2024Article
- Latent-state and model-based learning in PTSD.Trends in neurosciences · 2024Review
- Computational Mechanisms of Addiction and Anxiety: A Developmental Perspective.Biological psychiatry · 2023Review
- Cortical Grey Matter Mediates Increases in Model-Based Control and Learning from Positive Feedback from Adolescence to Adulthood.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- Article
- Developmental shifts in computations used to detect environmental controllability.PLoS computational biology · 2022Article
- Valence biases in reinforcement learning shift across adolescence and modulate subsequent memory.eLife · 2022Article
- How to capture developmental brain dynamics: gaps and solutions.NPJ science of learning · 2021Article
- The Straw That Broke the Camel's Back: Natural Variations in 17β-Estradiol and COMT-Val158Met Genotype Interact in the Modulation of Model-Free and Model-Based Control.Frontiers in behavioral neuroscience · 2021Article
- Adolescents exhibit reduced Pavlovian biases on instrumental learning.Scientific reports · 2020Article
Corrections and comments
- Erratum issuedErratum.2020
Authors and funding
3 authors.
Funding
Abstract
Reinforcement learning theory distinguishes "model-free" learning, which fosters reflexive repetition of previously rewarded actions, from "model-based" learning, which recruits a mental model of the environment to flexibly select goal-directed actions. Whereas model-free learning is evident across development, recruitment of model-based learning appears to increase with age. However, the cognitive processes underlying the development of model-based learning remain poorly characterized. Here, we examined whether age-related differences in cognitive processes underlying the construction and flexible recruitment of mental models predict developmental increases in model-based choice. In a cohort of participants aged 9-25, we examined whether the abilities to infer sequential regularities in the environment ("statistical learning"), maintain information in an active state ("working memory") and integrate distant concepts to solve problems ("fluid reasoning") predicted age-related improvements in model-based choice. We found that age-related improvements in statistical learning performance did not mediate the relationship between age and model-based choice. Ceiling performance on our working memory assay prevented examination of its contribution to model-based learning. However, age-related improvements in fluid reasoning statistically mediated the developmental increase in the recruitment of a model-based strategy. These findings suggest that gradual development of fluid reasoning may be a critical component process underlying the emergence of model-based learning.
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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.