Distributed and Mixed Information in Monosynaptic Inputs to Dopamine Neurons
Open accessAbstract
Dopamine neurons encode the difference between actual and predicted reward, or reward prediction error (RPE). Although many models have been proposed to account for this computation, it has been difficult to test these models experimentally. Here we established an awake electrophysiological recording system, combined with rabies virus and optogenetic cell-type identification, to characterize the firing patterns of monosynaptic inputs to dopamine neurons while mice performed classical conditioning tasks. We found that each variable required to compute RPE, including actual and predicted reward, was distributed in input neurons in multiple brain areas. Further, many input neurons across brain areas signaled combinations of these variables. These results demonstrate that even simple arithmetic computations such as RPE are not localized in specific brain areas but, rather, distributed across multiple nodes in a brain-wide network. Our systematic method to examine both activity and connectivity revealed unexpected redundancy for a simple computation in the brain.
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The signed prediction error indicates whether an outcome is better or worse than expected and plays a crucial role in changing the value allocated to cues, thereby guiding future decisions.
“First, the signed prediction error indicates whether an outcome is better or worse than expected, and thereby plays a crucial role in changing the value allocated to cues, thereby guiding future decisions [14–21].”
From Precision weighting of cortical unsigned prediction error signals benefits learning, is mediated by dopamine, and is impaired in psychosis (2021) · cites this paper as [21]
The Introduction (page unavailable) defines reward prediction error as actual reward minus expected reward, supporting the claim that its sign indicates whether an outcome is better or worse than expected. The Results discuss reward-predictive cues, but the passages do not say that this error changes the value assigned to cues or thereby guides future decisions. (LLM, conf=0.82)
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- Authors
- Tian, J., Huang, R., Cohen, J. Y., Osakada, F., Kobak, D., Machens, C. K., Callaway, E. M., Uchida, N., & Watabe-Uchida, M.
- Affiliations
- Harvard University (US)
- Salk Institute for Biological Studies (US)
- Centro Champalimaud (PT)
- Corresponding author
- Uchida, Naoshige
- ORCID
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2016-09
- Volume
- 91
- Issue
- 6
- Pages
- 1374-1389
- ISSN
- 0896-6273 (ISSN-L)
- PMC
- PMC5033723
- OpenAlex
- W2518664057
- Cited by
- 224
- References
- 91
- Citations by year
- 2026: 9 · 2025: 22 · 2024: 16 · 2023: 26 · 2022: 20 · 2021: 17 · 2020: 35 · 2019: 29 · 2018: 29 · 2017: 14 · 2016: 6
- FWCI
- 14.63
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (vor, 385 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- Neuron (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Dr. Mortier and Theresa Sackler Foundation
- National Institute of Mental Health (R01MH095953, R01MH101207)
- NIH (MH063912)
- Japan Society for the Promotion of Science
- Japan Science and Technology Agency
- Bial Foundation (389/14)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- dopaminergic neurons, reward prediction error, monosynaptic input, distributed computing, mixed signals, classical conditioning, rabies virus tracing, neural redundancy, reward encoding
- MeSH terms
- Animals, Brain Mapping, Conditioning, Classical, Corpus Striatum, Male, Neural Pathways, Reward, Synapses, Mice, Dopaminergic Neurons
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.
What counts as a claim ›How we measure confidence ›How we check this ›
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