ArticleeLife2021
Value signals guide abstraction during learning.
Article in eLife, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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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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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.
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Who cites it
11 citing papers in PubMed.
- Orbitofrontal-sensory cortical interactions in learning and adaptive decision-making.Trends in cognitive sciences · 2026Review
- Neurocomputational modeling of rule abstraction and memorization during probabilistic stimulus-reward learning.iScience · 2026Article
- Emergence of Categorical Representations in Parietal and Ventromedial Prefrontal Cortex across Extended Training.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Contributions of Attention to Learning in Multidimensional Reward Environments.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Autoencoder-based phenotyping of ophthalmic images highlights genetic loci influencing retinal morphology and provides informative biomarkers.Bioinformatics (Oxford, England) · 2024Article
- Functional specialization of medial and lateral orbitofrontal cortex in inferential decision-making.iScience · 2024Article
- Naturalistic reinforcement learning.Trends in cognitive sciences · 2024Review
- From learned value to sustained bias: how reward conditioning changes attentional priority.Frontiers in human neuroscience · 2024Article
- Computationally Informed Interventions for Targeting Compulsive Behaviors.Biological psychiatry · 2023Review
- Humans combine value learning and hypothesis testing strategically in multi-dimensional probabilistic reward learning.PLoS computational biology · 2022Article
- From internal models toward metacognitive AI.Biological cybernetics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
The human brain excels at constructing and using abstractions, such as rules, or concepts. Here, in two fMRI experiments, we demonstrate a mechanism of abstraction built upon the valuation of sensory features. Human volunteers learned novel association rules based on simple visual features. Reinforcement-learning algorithms revealed that, with learning, high-value abstract representations increasingly guided participant behaviour, resulting in better choices and higher subjective confidence. We also found that the brain area computing value signals - the ventromedial prefrontal cortex - prioritised and selected latent task elements during abstraction, both locally and through its connection to the visual cortex. Such a coding scheme predicts a causal role for valuation. Hence, in a second experiment, we used multivoxel neural reinforcement to test for the causality of feature valuation in the sensory cortex, as a mechanism of abstraction. Tagging the neural representation of a task feature with rewards evoked abstraction-based decisions. Together, these findings provide a novel interpretation of value as a goal-dependent, key factor in forging abstract representations.
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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.