Prolonged dopamine signalling in striatum signals proximity and value of distant rewards
Open accessAbstract
Predictions about future rewarding events have a powerful influence on behaviour. The phasic spike activity of dopamine-containing neurons, and corresponding dopamine transients in the striatum, are thought to underlie these predictions, encoding positive and negative reward prediction errors. However, many behaviours are directed towards distant goals, for which transient signals may fail to provide sustained drive. Here we report an extended mode of reward-predictive dopamine signalling in the striatum that emerged as rats moved towards distant goals. These dopamine signals, which were detected with fast-scan cyclic voltammetry (FSCV), gradually increased or--in rare instances--decreased as the animals navigated mazes to reach remote rewards, rather than having phasic or steady tonic profiles. These dopamine increases (ramps) scaled flexibly with both the distance and size of the rewards. During learning, these dopamine signals showed spatial preferences for goals in different locations and readily changed in magnitude to reflect changing values of the distant rewards. Such prolonged dopamine signalling could provide sustained motivational drive, a control mechanism that may be important for normal behaviour and that can be impaired in a range of neurologic and neuropsychiatric disorders.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Voltammetric studies in rats show similarly slow striatal dopamine increases with movements towards cocaine levers and with reward proximity and value.
“Voltammetric studies in rats show similarly slow striatal dopamine increases with movements towards cocaine levers155 and with reward proximity and value156”
From Dopamine reward prediction-error signalling: A two-component response (2016) · cites this paper as [156]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
A neural substrate of prediction and reward
Schultz, W., Dayan, P., & Montague, P. R. (1997) · Science · doi:10.1126/science.275.5306.1593 · Cited by 9,388 · see citing works
Getting formal with dopamine and reward
Schultz, W. (2002) · Neuron · doi:10.1016/s0896-6273(02)00967-4 · Cited by 2,574 · see citing works
The debate over dopamine’s role in reward: the case for incentive salience
Berridge, K. C. (2007) · Psychopharmacology · doi:10.1007/s00213-006-0578-x · Cited by 2,347 · see citing works
Discrete coding of reward probability and uncertainty by dopamine neurons
Fiorillo, C. D., Tobler, P. N., & Schultz, W. (2003) · Science · doi:10.1126/science.1077349 · Cited by 2,085 · see citing works
The mysterious motivational functions of mesolimbic dopamine
Salamone, J. D., & Correa, M. (2012) · Neuron · doi:10.1016/j.neuron.2012.10.021 · Cited by 1,418 · see citing works
Two types of dopamine neuron distinctly convey positive and negative motivational signals
Matsumoto, M., & Hikosaka, O. (2009) · Nature · doi:10.1038/nature08028 · Cited by 1,378 · see citing works
Neuron-type-specific signals for reward and punishment in the ventral tegmental area
Cohen, J. Y., Haesler, S., Vong, L., Lowell, B. B., & Uchida, N. (2012) · Nature · doi:10.1038/nature10754 · Cited by 1,318 · see citing works
Midbrain dopamine neurons encode a quantitative reward prediction error signal
Bayer, H. M., & Glimcher, P. W. (2005) · Neuron · doi:10.1016/j.neuron.2005.05.020 · Cited by 1,304 · see citing works
Adaptive Coding of Reward Value by Dopamine Neurons
Tobler, P. N., Fiorillo, C. D., & Schultz, W. (2005) · Science · doi:10.1126/science.1105370 · Cited by 1,276 · see citing works
Tonic dopamine: Opportunity costs and the control of response vigor
Niv, Y., Daw, N. D., Joel, D., & Dayan, P. (2007) · Psychopharmacology · doi:10.1007/s00213-006-0502-4 · Cited by 1,133 · see citing works
Subsecond dopamine release promotes cocaine seeking
Phillips, P. E. M., Stuber, G. D., Heien, M. L. A. V., Wightman, R. M., & Carelli, R. M. (2003) · Nature · doi:10.1038/nature01476 · Cited by 1,113 · see citing works
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 1× · see citing works
“Transient dopaminergic responses to learned reward-predictive cues have been proposed to initiate motivated behaviours 25,26 , but with this mode of signalling alone, it is difficult to account for how dopamine acts to maintain and direct motivational resources during prolonged behaviours…”
Self-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 · see citing works
Effort-related functions of nucleus accumbens dopamine and associated forebrain circuits
Salamone, J. D., Correa, M., Farrar, A., & Mingote, S. M. (2007) · Psychopharmacology · doi:10.1007/s00213-006-0668-9 · Cited by 1,000 · see citing works
The short-latency dopamine signal: a role in discovering novel actions?
Redgrave, P., & Gurney, K. (2006) · Nature Reviews Neuroscience · doi:10.1038/nrn2022 · Cited by 762 · see citing works
Associative learning mediates dynamic shifts in dopamine signaling in the nucleus accumbens
Day, J. J., Roitman, M. F., Wightman, R. M., & Carelli, R. M. (2007) · Nature Neuroscience · doi:10.1038/nn1923 · Cited by 710 · see citing works
Activity of striatal neurons reflects dynamic encoding and recoding of procedural memories
Barnes, T. D., Kubota, Y., Hu, D., Jin, D. Z., & Graybiel, A. M. (2005) · Nature · doi:10.1038/nature04053 · Cited by 595 · see citing works
Self-citationHikosaka, O., Sakamoto, M., & Usui, S. (1989) · Journal of Neurophysiology · doi:10.1152/jn.1989.61.4.814 · Cited by 579 · see citing works
Zweifel, L. S., Parker, J. G., Lobb, C. J., Rainwater, A., Wall, V. Z., Fadok, J. P., Darvas, M., Kim, M. J., Mizumori, S. J. Y., Paladini, C. A., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0813415106 · Cited by 426 · see citing works
Self-citationChronic microsensors for longitudinal, subsecond dopamine detection in behaving animals
Clark, J. J., Sandberg, S. G., Wanat, M. J., Gan, J. O., Horne, E. A., Hart, A. S., Akers, C. A., Parker, J. G., Willuhn, I., Martinez, V., et al. (2010) · Nature Methods · doi:10.1038/nmeth.1412 · Cited by 378 · see citing works
Self-citationDissociable cost and benefit encoding of future rewards by mesolimbic dopamine
Gan, J. O., Walton, M. E., & Phillips, P. E. M. (2009) · Nature Neuroscience · doi:10.1038/nn.2460 · Cited by 235 · see citing works
Self-citationMultivariate concentration determination using principal component regression with residual analysis
Keithley, R. B., Wightman, R. M., & Heien, M. L. (2009) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2009.07.002 · Cited by 205 · see citing works
A manifold of spatial maps in the brain
Derdikman, D., & Moser, E. I. (2010) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2010.09.004 · Cited by 171 · see citing works
Phasic Nucleus Accumbens Dopamine Release Encodes Effort- and Delay-Related Costs
Day, J. J., Jones, J. L., Wightman, R. M., & Carelli, R. M. (2010) · Biological Psychiatry · doi:10.1016/j.biopsych.2010.03.026 · Cited by 160 · see citing works
Dopamine, uncertainty and TD learning
Niv, Y., Duff, M. O., & Dayan, P. (2005) · Behavioral and Brain Functions · doi:10.1186/1744-9081-1-6 · Cited by 153 · see citing works
Whishaw, I. Q., & Dunnett, S. B. (1985) · Behavioural Brain Research · doi:10.1016/0166-4328(85)90165-2 · Cited by 133 · see citing works
NMDA Receptors in Dopaminergic Neurons Are Crucial for Habit Learning
Wang, L. P., Li, F. R., Wang, D., Xie, K., Wang, D., Shen, X., & Tsien, J. Z. (2011) · Neuron · doi:10.1016/j.neuron.2011.10.019 · Cited by 122 · see citing works
Dorsal striatal dopamine depletion impairs both allocentric and egocentric navigation in rats
Braun, A. A., Graham, D. L., Schaefer, T. L., Vorhees, C. V., & Williams, M. T. (2012) · Neurobiology of Learning and Memory · doi:10.1016/j.nlm.2012.03.004 · Cited by 61 · see citing works
Keithley, R. B., Wightman, R. M., & Heien, M. L. (2009) · TrAC Trends in Analytical Chemistry · doi:10.1016/s0165-9936(09)00282-9 · Cited by 15 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Neuronal Reward and Decision Signals: From Theories to Data
Schultz, W. (2015) · Physiological Reviews · doi:10.1152/physrev.00023.2014 · Cited by 1,126 · see citing works
Dopamine reward prediction-error signalling: A two-component response
Schultz, W. (2016) · Nature Reviews Neuroscience · doi:10.1038/nrn.2015.26 · Cited by 1,036 · see citing works
Motivation and cognitive control: from behavior to neural mechanism
Botvinick, M., & Braver, T. (2015) · Annual Review of Psychology · doi:10.1146/annurev-psych-010814-015044 · Cited by 909 · see citing works
Berke, J. D. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0152-y · Cited by 904 · see citing works
Specialized coding of sensory, motor and cognitive variables in VTA dopamine neurons
Engelhard, B., Finkelstein, J., Cox, J., Fleming, W., Jang, H. J., Ornelas, S., Koay, S. A., Thiberge, S. Y., Daw, N. D., Tank, D. W., et al. (2019) · Nature · doi:10.1038/s41586-019-1261-9 · Cited by 544 · see citing works
Prefrontal cortical regulation of brainwide circuit dynamics and reward-related behavior
Ferenczi, E. A., Zalocusky, K. A., Liston, C., Grosenick, L., Warden, M. R., Amatya, D., Katovich, K., Mehta, H., Patenaude, B., Ramakrishnan, C., et al. (2016) · Science · doi:10.1126/science.aac9698 · Cited by 535 · see citing works
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 · see citing works
The striatum: where skills and habits meet
Graybiel, A. M., & Grafton, S. T. (2015) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a021691 · Cited by 463 · see citing works
Nieh, E. H., Vander Weele, C. M., Matthews, G. A., Presbrey, K. N., Wichmann, R., Leppla, C. A., Izadmehr, E. M., & Tye, K. M. (2016) · Neuron · doi:10.1016/j.neuron.2016.04.035 · Cited by 387 · see citing works
The anatomy of apathy: a neurocognitive framework for amotivated behaviour
Le Heron, C., Apps., M. A. J., & Husain, M. (2018) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2017.07.003 · Cited by 380 · see citing works
Salamone, J. D., Yohn, S. E., López-Cruz, L., San Miguel, N., & Correa, M. (2016) · Brain · doi:10.1093/brain/aww050 · Cited by 350 · see citing works
Dopamine release in the nucleus accumbens core signals perceived saliency
Kutlu, M. G., Zachry, J. E., Melugin, P. R., Cajigas, S. A., Chevee, M. F., Kelly, S. J., Kutlu, B., Tian, L., Siciliano, C. A., & Calipari, E. S. (2021) · Current Biology · doi:10.1016/j.cub.2021.08.052 · Cited by 238 · see citing works
NOW vs LATER brain circuits: implications for obesity and addiction
Volkow, N. D., & Baler, R. D. (2015) · Trends in Neurosciences · doi:10.1016/j.tins.2015.04.002 · Cited by 237 · see citing works
Basal ganglia circuit loops, dopamine and motivation: a review and enquiry
Ikemoto, S., Yang, C., & Tan, A. (2015) · Behavioural Brain Research · doi:10.1016/j.bbr.2015.04.018 · Cited by 226 · see citing works
Fonteneau, C., Redoute, J., Haesebaert, F., Le Bars, D., Costes, N., Suaud-Chagny, M.-F., & Brunelin, J. (2018) · Cerebral Cortex · doi:10.1093/cercor/bhy093 · Cited by 198 · see citing works
Imaging neurotransmitter and neuromodulator dynamics in vivo with genetically encoded indicators
Sabatini, B. L., & Tian, L. (2020) · Neuron · doi:10.1016/j.neuron.2020.09.036 · Cited by 203 · see citing works
Cell-type-specific asynchronous modulation of PKA by dopamine in learning
Lee, S. J., Lodder, B., Chen, Y., Patriarchi, T., Tian, L., & Sabatini, B. L. (2021) · Nature · doi:10.1038/s41586-020-03050-5 · Cited by 160 · see citing works
Schlaepfer, T. E., Bewernick, B. H., Kayser, S., Hurlemann, R., & Coenen, V. A. (2014) · Neuropsychopharmacology · doi:10.1038/npp.2014.28 · Cited by 160 · see citing works
Dopamine, effort-based choice, and behavioral economics: basic and translational research.
Salamone, J. D., Correa, M., Yang, J.-H., Rotolo, R., & Presby, R. (2018) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2018.00052 · Cited by 142 · see citing works
Cerebellar Neurodynamics Predict Decision Timing and Outcome on the Single-Trial Level
Lin, Q., Manley, J., Helmreich, M., Schlumm, F., Li, J. M., Robson, D. N., Engert, F., Schier, A., Nöbauer, T., & Vaziri, A. (2020) · Cell · doi:10.1016/j.cell.2019.12.018 · Cited by 122 · see citing works
The medial forebrain bundle as a target for deep brain stimulation for obsessive-compulsive disorder
Coenen, V. A., Schlaepfer, T. E., Goll, P., Reinacher, P. C., Voderholzer, U., Tebartz van Elst, L., Urbach, H., & Freyer, T. (2017) · CNS Spectrums · doi:10.1017/s1092852916000286 · Cited by 128 · see citing works
The neural system of metacognition accompanying decision-making in the prefrontal cortex
Qiu, L., Su, J., Ni, Y., Bai, Y., Zhang, X., Li, X., & Wan, X. (2018) · PLOS Biology · doi:10.1371/journal.pbio.2004037 · Cited by 125 · see citing works
Influences of dopaminergic system dysfunction on late-life depression
Taylor, W. D., Zald, D. H., Felger, J. C., Christman, S., Claassen, D. O., Horga, G., Miller, J. M., Gifford, K., Rogers, B., Szymkowicz, S. M., et al. (2022) · Molecular Psychiatry · doi:10.1038/s41380-021-01265-0 · Cited by 89 · see citing works
Cartier, E., Hamilton, P. J., Belovich, A. N., Shekar, A., Campbell, N. G., Saunders, C., Andreassen, T. F., Gether, U., Veenstra-Vanderweele, J., Sutcliffe, J. S., et al. (2015) · EBioMedicine · doi:10.1016/j.ebiom.2015.01.007 · Cited by 74 · see citing works
Marsden, K. E., Ma, W. J., Deci, E. L., Ryan, R. M., & Chiu, P. H. (2015) · Cognitive, Affective, & Behavioral Neuroscience · doi:10.3758/s13415-014-0324-5 · Cited by 75 · see citing works
Cholinergic modulation of dopamine pathways through nicotinic acetylcholine receptors
de Kloet, S. F., Mansvelder, H. D., & De Vries, T. J. (2015) · Biochemical Pharmacology · doi:10.1016/j.bcp.2015.07.014 · Cited by 69 · see citing works
Geometric transformation of cognitive maps for generalization across hippocampal-prefrontal circuits
Tang, W., Shin, J. D., & Jadhav, S. P. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.112246 · Cited by 59 · see citing works
Insular neural system controls decision-making in healthy and methamphetamine-treated rats
Mizoguchi, H., Katahira, K., Inutsuka, A., Fukumoto, K., Nakamura, A., Wang, T., Nagai, T., Sato, J., Sawada, M., Ohira, H., et al. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1418014112 · Cited by 49 · see citing works
Failure of standard training sets in the analysis of fast-scan cyclic voltammetry data
Johnson, J. A., Rodeberg, N. T., & Wightman, R. M. (2016) · ACS Chemical Neuroscience · doi:10.1021/acschemneuro.5b00302 · Cited by 48 · see citing works
Corticostriatal foundations of habits
Seger, C. A. (2018) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2018.01.006 · Cited by 38 · see citing works
Bulaj, G. (2014) · Frontiers in Neurology · doi:10.3389/fneur.2014.00126 · Cited by 29 · see citing works
Klanker, M., Feenstra, M., Willuhn, I., & Denys, D. (2017) · Neuroscience · doi:10.1016/j.neuroscience.2017.09.012 · Cited by 25 · see citing works
Goedhoop, J., Arbab, T., & Willuhn, I. (2023) · The Journal of Neuroscience · doi:10.1523/jneurosci.1527-22.2023 · Cited by 24 · see citing works
Development of a genetically-encoded oxytocin sensor
Mignocchi, N., Krüssel, S., Jung, K., Lee, D., & Kwon, H.-B. (2020) · doi:10.1101/2020.07.14.202598 · Cited by 22 · see citing works
Addressing altered anticipation as a transdiagnostic target through computational psychiatry
Sepúlveda, P., Aitsahalia, I., Kumar, K., Atkin, T., & Iigaya, K. (2025) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2025.02.014 · Cited by 3 · see citing works
- Authors
- Howe, M. W., Tierney, P. L., Sandberg, S. G., Phillips, P. E. M., & Graybiel, A. M.
- Affiliations
- McGovern Institute for Brain Research (US)
- University of Washington (US)
- Corresponding author
- Graybiel, Ann M.
- Venue
- Nature
- Published
- 2013-08-04
- Volume
- 500
- Issue
- 7464
- Pages
- 575-579
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC3927840
- OpenAlex
- W2147538742
- Cited by
- 565
- References
- 29
- Citations by year
- 2026: 30 · 2025: 50 · 2024: 64 · 2023: 43 · 2022: 45 · 2021: 50 · 2020: 46 · 2019: 37 · 2018: 42 · 2017: 37 · 2016: 48 · 2015: 32 · 2014: 36 · 2013: 5
- FWCI
- 19.79
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
- PMC
- Funders
- National Institute on Aging (R01AG044839)
- National Institute of Mental Health (R01MH079292, R01MH060379)
- National Institute on Drug Abuse (R01DA027858)
- 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 › Memory and Neural Mechanisms
- Keywords
- dopamine signalling, striatum, reward prediction, reward value, goal-directed behavior, motivational drive, reward prediction error, spatial learning, rats
- MeSH terms
- Action Potentials, Animals, Dopamine, Goals, Male, Models, Neurological, Models, Psychological, Motivation, Reward, Time Factors, Signal Transduction, Neostriatum, Maze Learning, Rats, Long-Evans, Rats, 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 ›
Are you an author, or do you see a problem with this page? Request a review
