The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Phasic Dopamine Release in the Rat Nucleus Accumbens Symmetrically Encodes a Reward Prediction Error Term
Open accessAbstract
Making predictions about the rewards associated with environmental stimuli and updating those predictions through feedback is an essential aspect of adaptive behavior. Theorists have argued that dopamine encodes a reward prediction error (RPE) signal that is used in such a reinforcement learning process. Recent work with fMRI has demonstrated that the BOLD signal in dopaminergic target areas meets both necessary and sufficient conditions of an axiomatic model of the RPE hypothesis. However, there has been no direct evidence that dopamine release itself also meets necessary and sufficient criteria for encoding an RPE signal. Further, the fact that dopamine neurons have low tonic firing rates that yield a limited dynamic range for encoding negative RPEs has led to significant debate about whether positive and negative prediction errors are encoded on a similar scale. To address both of these issues, we used fast-scan cyclic voltammetry to measure reward-evoked dopamine release at carbon fiber electrodes chronically implanted in the nucleus accumbens core of rats trained on a probabilistic decision-making task. We demonstrate that dopamine concentrations transmit a bidirectional RPE signal with symmetrical encoding of positive and negative RPEs. Our findings strengthen the case that changes in dopamine concentration alone are sufficient to encode the full range of RPEs necessary for reinforcement learning.
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Cites
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Sutton, R. S. (1988) · Machine Learning · doi:10.1007/bf00115009 · Cited by 5,148
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A framework for mesencephalic dopamine systems based on predictive Hebbian learning
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Midbrain dopamine neurons encode a quantitative reward prediction error signal
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Self-citationA selective role for dopamine in stimulus-reward learning
Flagel, S. B., Clark, J. J., Robinson, T. E., Mayo, L., Czuj, A., Willuhn, I., Akers, C. A., Clinton, S. M., Phillips, P. E. M., & Akil, H. (2011) · Nature · doi:10.1038/nature09588 · Cited by 1,026 · cited 2×
“A large number of studies have now correlated dopaminergic neural activity with the reward prediction error (RPE) term in temporal difference models of learning (Sutton, 1988, Montague et al., 1996, Schultz et al., 1997, Waelti et al., 2001, Flagel et al., 2011, Steinberg et al., 2013).”
BackgroundResultSelf-citationDopamine responses comply with basic assumptions of formal learning theory
Waelti, P., Dickinson, A., & Schultz, W. (2001) · Nature · doi:10.1038/35083500 · Cited by 1,018
Responses of monkey dopamine neurons during learning of behavioral reactions
Ljungberg, T., Apicella, P., & Schultz, W. (1992) · Journal of Neurophysiology · doi:10.1152/jn.1992.67.1.145 · Cited by 987
Understanding dopamine and reinforcement learning: the dopamine reward prediction error hypothesis
Glimcher, P. W. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1014269108 · Cited by 955
Self-citationMidbrain dopamine neurons encode decisions for future action
Morris, G., Nevet, A., Arkadir, D., Vaadia, E., & Bergman, H. (2006) · Nature Neuroscience · doi:10.1038/nn1743 · Cited by 503
Cited by
Neuronal Reward and Decision Signals: From Theories to Data
Schultz, W. (2015) · Physiological Reviews · doi:10.1152/physrev.00023.2014 · Cited by 1,126
Berke, J. D. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0152-y · Cited by 904
Reinforcement learning and episodic memory in humans and animals: an integrative framework
Gershman, S. J., & Daw, N. D. (2017) · Annual Review of Psychology · doi:10.1146/annurev-psych-122414-033625 · Cited by 446
Neural Circuitry of Reward Prediction Error
Watabe-Uchida, M., Eshel, N., & Uchida, N. (2017) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-072116-031109 · Cited by 437
A computational and neural model of momentary subjective well-being
Rutledge, R. B., Skandali, N., Dayan, P., & Dolan, R. J. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1407535111 · Cited by 444
Self-citation
Metadata
- Authors
- Hart, A. S., Rutledge, R. B., Glimcher, P. W., & Phillips, P. E. M.
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2014-01-15
- Volume
- 34
- Issue
- 3
- Pages
- 698-704
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- OpenAlex
- W2073602092
- Cited by
- 293
- References
- 11
- FWCI
- 13.96
- Type
- journal article
- Language
- en
- Open access
- hybrid
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