The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
Adaptive Coding of Reward Value by Dopamine Neurons
Abstract
It is important for animals to estimate the value of rewards as accurately as possible. Because the number of potential reward values is very large, it is necessary that the brain's limited resources be allocated so as to discriminate better among more likely reward outcomes at the expense of less likely outcomes. We found that midbrain dopamine neurons rapidly adapted to the information provided by reward-predicting stimuli. Responses shifted relative to the expected reward value, and the gain adjusted to the variance of reward value. In this way, dopamine neurons maintained their reward sensitivity over a large range of reward values.
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In the citing paper
“Neurons in MBD nuclei are believed to encode reward prediction errors (RPEs).45”
From Two prefrontal-subcortical circuits estimate controllability and reflect its impact on learning (2026) · cites this paper as [45]
In the citing paper
“As is the case for dopamine neurons, 46 reward-related BOLD signals should maintain their sensitivity over a large range of reward values.”
From Increased neural responses to reward in adolescents and young adults with attention-deficit/hyperactivity disorder and their unaffected siblings (2015) · cites this paper as [46]
In the citing paper
“Indeed, reward-related responses adapt to the context in which a reward is presented 46, in the sense that they depend on a combination of the overall expected value and their variance rather than the absolute magnitude of reward value.”
From Increased neural responses to reward in adolescents and young adults with attention-deficit/hyperactivity disorder and their unaffected siblings (2015) · cites this paper as [46]
In the citing paper
“Yet, both reward magnitude and reward probability are coded relatively rather than absolutely. 46”
From Increased neural responses to reward in adolescents and young adults with attention-deficit/hyperactivity disorder and their unaffected siblings (2015) · cites this paper as [46]
In the citing paper
“Activity in individual neurons in both habenula and VTA reflects both the value of a stimulus in terms of the reward that it predicts58–60 as well as VoI21,22,27,61”
From Interpretable abstractions of artificial neural networks predict behavior and neural activity during human information gathering (2026) · cites this paper as [59]
In the citing paper
“For example, the gain of RPE signals produced by dopamine neurons in the ventral tegmental area is modulated by the variance of reward value.100,101”
From Serotonin neurons modulate learning rate through uncertainty (2022) · cites this paper as [101]
In the citing paper
“Consistent with a prediction error signal, spiking activity of dopamine neurons increases with both reward magnitude and probability (Fiorillo et al., 2003; Tobler et al., 2005; Roesch et al., 2007).”
From Decision Making in Recurrent Neuronal Circuits (2008) · cites this paper as Tobler et al., 2005
In the citing paper
“Research in non-human primates, confirmed in humans, indicates that differences the probability with which a cue predicts a reward produce a quantitative change in the engagement of dopaminergic systems.46,47”
From Striatal sensitivity during reward processing in attention-deficit/hyperactivity disorder (2012) · cites this paper as [46]
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Metadata
- Authors
- Tobler, P. N., Fiorillo, C. D., & Schultz, W.
- Affiliations
- University of Fribourg (CH)
- Corresponding author
- Fiorillo, Christopher D.
- Schultz, Wolfram
- Venue
- Science
- Published
- 2005-03-11
- Volume
- 307
- Issue
- 5715
- Pages
- 1642-1645
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2098534820
- Cited by
- 1,276
- References
- 24
- Citations by year
- 2026: 36 · 2025: 32 · 2024: 47 · 2023: 56 · 2022: 53 · 2021: 72 · 2020: 57 · 2019: 69 · 2018: 63 · 2017: 65 · 2016: 74 · 2015: 58 · 2014: 72 · 2013: 76 · 2012: 72
- FWCI
- 22.78
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Zurich Open Repository and Archive (University of Zurich) (acceptedVersion)
- reroDoc Digital Library (submittedVersion)
- Zurich Open Repository and Archive (University of Zurich) (submittedVersion)
- Funders
- Wellcome Trust (095495)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- dopaminergic neurons, adaptive coding, midbrain, reward prediction, gain modulation, variance, reward sensitivity, neural adaptation
- MeSH terms
- Adaptation, Physiological, Animals, Discrimination, Psychological, Dopamine, Electrophysiology, Female, Learning, Macaca fascicularis, Mesencephalon, Neurons, Photic Stimulation, Probability, Reward
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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