The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.
Temporally Extended Dopamine Responses to Perceptually Demanding Reward-Predictive Stimuli
Open accessAbstract
Midbrain dopamine neurons respond to reward-predictive stimuli. In the natural environment reward-predictive stimuli are often perceptually complicated. Thus, to discriminate one stimulus from another, elaborate sensory processing is necessary. Given that previous studies have used simpler types of reward-predictive stimuli, it has yet to be clear whether and, if so, how dopamine neurons obtain reward information from perceptually complicated stimuli. To investigate this, we recorded the activities of monkey dopamine neurons while they were performing discrimination between two coherent motion directions in random-dot motion stimuli. These coherent directions were paired with different magnitudes of reward. We found that dopamine neurons showed reward-predictive responses to random-dot motion stimuli. Moreover, dopamine neurons showed temporally extended activity correlated with changes in reward prediction (i.e., reward prediction error) from coarse to fine scales between initial motion detection and subsequent motion discrimination phases. Noticeably, dopamine reward-predictive responses became differential in a later phase than previously reported. This response pattern was consistent with the time course of processing required for the estimation of expected reward value that parallels the motion direction discrimination processing. The results demonstrate that dopamine neurons are able to reflect the reward value of perceptually complicated stimuli, and suggest that dopamine neurons use the moment-to-moment reward prediction associated with environmental stimuli to compute a reward prediction error.
Overview
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
Verification
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?
In the citing paper
“True to the notion that dopamine neurons are involved in temporal prediction-error coding, the initial activation is sensitive to the time of stimulus occurrence and thus codes a temporal-event prediction error33.”
From Dopamine reward prediction-error signalling: A two-component response (2016) · cites this paper as [33]
In the citing paper
“However, on closer inspection, dopamine responses in such elaborate tasks constitute standard reward prediction-error signals2,33,59,66,69,75,151–153.”
From Dopamine reward prediction-error signalling: A two-component response (2016) · cites this paper as [33]
In the citing paper
“Dopamine neurons in medial and lateral, or dorsal and ventral, midbrain positions do show graded differences in responses to rewarding and aversive stimuli2,23,24,26,33.”
From Dopamine reward prediction-error signalling: A two-component response (2016) · cites this paper as [33]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Press, W. H., Teukolsky, S. A., Vetterling, W. T., & Flannery, B. P. (1994) · Cited by 15,411
Predictive reward signal of dopamine neurons
Schultz, W. (1998) · Journal of Neurophysiology · doi:10.1152/jn.1998.80.1.1 · Cited by 4,564
Self-citationDopamine, learning and motivation.
Wise, R. A. (2004) · Nature Reviews Neuroscience · doi:10.1038/nrn1406 · Cited by 3,379 · cited 1×
“Dopamine plays a central role in reward information processing (Schultz, 1998; Wise, 2004).”
BackgroundThe psychometric function: I. Fitting, sampling, and goodness of fit
Wichmann, F. A., & Hill, N. J. (2001) · Perception & Psychophysics · doi:10.3758/bf03194544 · Cited by 2,359
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
Self-citationThe analysis of visual motion: a comparison of neuronal and psychophysical performance
Britten, K., Shadlen, M., Newsome, W., & Movshon, J. (1992) · The Journal of Neuroscience · doi:10.1523/jneurosci.12-12-04745.1992 · Cited by 1,958
Neural Basis of a Perceptual Decision in the Parietal Cortex (Area LIP) of the Rhesus Monkey
Shadlen, M. N., & Newsome, W. T. (2001) · Journal of Neurophysiology · doi:10.1152/jn.2001.86.4.1916 · Cited by 1,755
Newsome, W., & Pare, E. (1988) · The Journal of Neuroscience · doi:10.1523/jneurosci.08-06-02201.1988 · Cited by 1,615
Haber, S. N., Fudge, J. L., & McFarland, N. R. (2000) · The Journal of Neuroscience · doi:10.1523/jneurosci.20-06-02369.2000 · Cited by 1,610
Roitman, J. D., & Shadlen, M. N. (2002) · The Journal of Neuroscience · doi:10.1523/jneurosci.22-21-09475.2002 · Cited by 1,589 · cited 5×
“This is consistent with a time course in which neural discrimination begins at 200 ms after RDM onset in the LIP area (Roitman and Shadlen, 2002).”
BackgroundMethodResultInfluential
Cited by
Sorted by citations
Items 101–158 of 158
Comparing fMRI responses measured at 3 versus 7 Tesla across human cortex, striatum, and brainstemPreprint
Colizoli, O., de Gee, J. W., van der Zwaag, W., & Donner, T. H. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.05.12.090175 · Cited by 12
Funamizu, A. (2021) · iScience · doi:10.1016/j.isci.2021.102826 · Cited by 10
A plastic corticostriatal circuit model of adaptation in perceptual decision making
Hsiao, P.-Y. (2013) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2013.00178 · Cited by 10
Enomoto, K., Matsumoto, N., Inokawa, H., Kimura, M., & Yamada, H. (2020) · Scientific Reports · doi:10.1038/s41598-020-65914-0 · Cited by 9
Thirkettle, M., Walton, T., Shah, A., GURNEY, K. N., Redgrave, P., & Stafford, T. (2013) · Behavioural Brain Research · doi:10.1016/j.bbr.2013.01.023 · Cited by 10
de Lima, B. F. C., Ramos, D. C., Barbiero, J. K., Pulido, L. N., Redgrave, P., Robinson, D. L., Gómez‐A, A., & Cunha, C. D. (2017) · Neuroscience · doi:10.1016/j.neuroscience.2017.02.052 · Cited by 10
Electrophysiological Correlates of Reward Processing in Dopamine Neurons
Schultz, W. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-805308-9.00002-6 · Cited by 10
Self-citationThe causal role between phasic midbrain dopamine signals and learning
Aquili, L. (2014) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2014.00139 · Cited by 9
Asymmetric perceptual confounds between canonical lightings and materials
Zhang, F., de Ridder, H., & Pont, S. C. (2018) · Journal of Vision · doi:10.1167/18.11.11 · Cited by 9
The effect of effort on reward prediction error signals in midbrain dopamine neurons
Tanaka, S., Taylor, J. E., & Sakagami, M. (2021) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2021.07.004 · Cited by 8
Self-citationPerceptual decisions based on previously learned information are independent of dopaminergic tone
Perugini, A., & Basso, M. A. (2017) · Journal of Neurophysiology · doi:10.1152/jn.00761.2017 · Cited by 8
Saga, Y., Nakayama, Y., Inoue, K., Yamagata, T., Hashimoto, M., Tremblay, L., Takada, M., & Hoshi, E. (2016) · European Journal of Neuroscience · doi:10.1111/ejn.13421 · Cited by 7
Optimal policy for uncertainty estimation concurrent with decision making
Li, X., Su, R., Chen, Y., & Yang, T. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.112232 · Cited by 6
Dopaminergic computations for perceptual decisions
Garcia, S. L., Fritsche, M., & Lak, A. (2024) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2024.101458 · Cited by 6
Expectancy-related changes in firing of dopamine neurons depend on hippocampusPreprint
Takahashi, Y. K., Zhang, Z., Montesinos-Cartagena, M., Kahnt, T., Langdon, A., & Schoenbaum, G. M. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.07.19.549728 · Cited by 6
Zhang, A. Q., Ralph, M. R., & Stinchcombe, A. R. (2024) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1012082 · Cited by 5
Two tales of how expectation of reward modulates behavior
Ding, L., & Perkel, D. J. (2014) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2014.07.011 · Cited by 6
Phasic Dopamine Signaling in Action Selection and Reinforcement Learning
Redgrave, P., Vautrelle, N., Overton, P. G., & Reynolds, J. N. J. (2016) · Handbook of behavioral neuroscience · doi:10.1016/b978-0-12-802206-1.00034-9 · Cited by 5
Hill-Bowen, L. D., Riedel, M. C., Poudel, R., Salo, T., Flannery, J. S., Camilleri, J. A., Eickhoff, S. B., Laird, A. R., & Sutherland, M. T. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.02.26.966549 · Cited by 6
Context-dependent multiplexing by individual VTA dopamine neuronsPreprint
Kremer, Y., Flakowski, J., Rohner, C., & Lüscher, C. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/408062 · Cited by 5
Expectancy-related changes in firing of dopamine neurons depend on hippocampus
Zhang, Z., Takahashi, Y. K., Montesinos-Cartagena, M., Kahnt, T., Langdon, A., & Schoenbaum, G. M. (2024) · Nature Communications · doi:10.1038/s41467-024-53308-z · Cited by 10
Neural Circuit Mechanisms of Value-Based Decision-Making and Reinforcement Learning
Soltani, A., Chaisangmongkon, W., & Wang, X.-J. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-805308-9.00013-0 · Cited by 5
Peters, K. Z., Young, A. M. J., & McCutcheon, J. E. (2021) · European Journal of Neuroscience · doi:10.1111/ejn.15108 · Cited by 3
VTA Dopamine Neurons Multiplex External with Internal Representations of Goal-Directed ActionPreprint
Kremer, Y., Flakowski, J., Rohner, C., & Lüscher, C. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3249465 · Cited by 4
de la Cuesta‐Ferrer, L., Koß, C., Starosta, S., Kasties, N., Lengersdorf, D., Jäkel, F., & Stüttgen, M. C. (2025) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1012636 · Cited by 3
Action Experience and Action Discovery in Medicated Individuals with Parkinson’s Disease
Bednark, J. G., Reynolds, J. N. J., Stafford, T., Redgrave, P., & Franz, E. A. (2016) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2016.00427 · Cited by 3
The biological and behavioral computations that influence dopamine responses
Stauffer, W. R. (2018) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2018.02.005 · Cited by 3
The dopamine reward prediction error signal
Schultz, W. (2025) · Handbook of behavioral neuroscience · doi:10.1016/b978-0-443-29867-7.00027-x · Cited by 6
Self-citationVersprille, L. J. F. W., McKenzie, C., Amorim, F. E., Yano, K., Dalley, J. W., & Robbins, T. W. (2026) · Journal of Neuroscience · doi:10.1523/jneurosci.1696-25.2026 · Cited by 2
A Positive Start: Backing a Horse Using Positive Reinforcement
Lethbridge, E. M. (2024) · Animal Behaviour and Welfare Cases · doi:10.1079/abwcases.2024.0011 · Cited by 2
Schultz, W. (2015) · Elsevier eBooks · doi:10.1016/b978-0-12-397025-1.00059-2 · Cited by 3
Self-citationWhite, T. L., Gonsalves, M. A., Zimmerman, C. S., Joyce, H., Cohen, R. A., Clark, U. S., Sweet, L. H., Lejuez, C. W., & Nitenson, A. Z. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1060877 · Cited by 2
Duncan, K. D., & Shohamy, D. (2024) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780190917982.013.24 · Cited by 2
Reward Contexts Extend Dopamine Signals to Unrewarded Stimuli
Kobayashi, S., & Schultz, W. (2014) · Current Biology · doi:10.1016/j.cub.2014.01.057 · Cited by 1
Self-citationJovanović, L., Chassignolle, M., Schmidt‐Mutter, C., Behr, G., Coull, J. T., & Giersch, A. (2023) · Scientific Reports · doi:10.1038/s41598-023-47843-w · Cited by 1
Consolidación de la Memoria y Sustrato Nervioso del Refuerzo
Redolar-Ripoll, E. (2012) · Revista Argentina de Ciencias del Comportamiento ( RACC ) · doi:10.32348/1852.4206.v4.n2.5174 · Cited by 1
A Neuroeconomic Theory of Attention- and Task-Switching with Implications for Autism and ADHDPreprint
Landry, P. (2016) · SSRN Electronic Journal · doi:10.2139/ssrn.2725953 · Cited by 1
Internal bias controls dopamine perceptual decision-related responsesPreprint
Sarno, S., Beirán, M., Vergara, J., Rossi-Pool, R., Romo, R., & Parga, N. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/431387 · Cited by 1
Sarno, S., Beirán, M., Falcó-Roget, J., Diaz-deLeon, G., Rossi-Pool, R., Romo, R., & Parga, N. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.05.01.071977 · Cited by 1
Avances y Desafíos en Neuropsicología
Godoy, J. C. (2012) · Redalyc (Universidad Autónoma del Estado de México) · doi:10.30882/1852.4206.v4.n2.5168
The dopamine signal in decision-making tasks with stimulus and timing uncertainty
Sarno, S., de Lafuente, V., Romo, R., & Parga, N. (2014) · BMC Neuroscience · doi:10.1186/1471-2202-15-s1-p71
The Neuronal Base of Perceptual Learning and Skill Acquisition
Greenlee, M. W. (2014) · Springer international handbooks of education · doi:10.1007/978-94-017-8902-8_12
Multiple Neural Circuits in Value-Based Decision-Making
Sakagami, M. (2013) · Springer eBooks · doi:10.1007/978-94-007-4792-0_55
Self-citationDopamine Prediction Errors and the Relativity of Value
Sakagami, M., & Tanaka, S. (2016) · Advances in cognitive neurodynamics · doi:10.1007/978-981-10-0207-6_9
Self-citationBaranger, D. A. A. (2018) · Open Scholarship Institutional Repository (Washington University in St. Louis) · doi:10.7936/2npp-kp25
Hidden State Inference in the Midbrain Dopamine System
Starkweather, C. K. (2018) · Digital Access to Scholarship at Harvard (DASH) (Harvard University)
Gil-Lievana, E., Ramírez-Mejía, G., Urrego-Morales, O., Luis-Islas, J., Gutiérrez, R., & Bermúdez‐Rattoni, F. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.11.19.469297
Frank, M. J. (2010) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.7340957.7601055
Schultz, W. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.727374683.793565153
Self-citationSchultz, W. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.727392887.793565155
Self-citationFan, Y., Doi, T., Gold, J. I., & Ding, L. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.09.12.507621
(2022) · Society for Neuroscience eBooks · doi:10.1523/hon.012012
Gharesi, N., Kalaska, J. F., & Baillet, S. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.01.23.701339
Flexibility in value-based decision-making
Jahn, C. I. (2018) · theses.fr (ABES) · doi:10.70675/24ffd7ecz04aez45dez9bfdzff312b4881a8
Spatio-temporal contribution of Dopamine in the execution of Goal-directed movement in rats
Gauthier, S. (2022) · theses.fr (ABES) · doi:10.70675/2e9049f3z7a59z4660z8820z667ebc97130e
Activity of dopaminergic neurons during skilled reaching in head-fixed rats
Besserer, C. (2023) · theses.fr (ABES) · doi:10.70675/89acd7a2z37aaz434fzb34dz3b04859d2fa0
Macaque Area LIP Reflects Confidence-Dependent Changes in Decision Policy
Tu, M. S., Vivar-Lazo, M., & Fetsch, C. R. (2026) · Journal of Neuroscience · doi:10.64898/2026.04.27.721150
Metadata
- Authors
- Nomoto, K., Schultz, W., Watanabe, T., & Sakagami, M.
- Affiliations
- Tamagawa University (JP)
- Boston University (US)
- Corresponding author
- Sakagami, Masamichi
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2010-08-11
- Volume
- 30
- Issue
- 32
- Pages
- 10692-10702
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- PMC
- PMC3297489
- OpenAlex
- W2120222754
- Cited by
- 158
- References
- 41
- Citations by year
- 2026: 3 · 2025: 2 · 2024: 7 · 2023: 9 · 2022: 7 · 2021: 11 · 2020: 11 · 2019: 10 · 2018: 14 · 2017: 16 · 2016: 14 · 2015: 5 · 2014: 16 · 2013: 13 · 2012: 10
- FWCI
- 4.26
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Neuroscience (publishedVersion, cc-by-nc-sa)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Wellcome Trust (095495)
- National Institutes of Health
- National Eye Institute (R01EY015980, R01EY019466)
- 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, reward prediction error, reward prediction, random dot motion, motion direction discrimination, midbrain dopamine
- MeSH terms
- Acoustic Stimulation, Analysis of Variance, Animals, Behavior, Animal, Conditioning, Operant, Discrimination, Psychological, Dopamine, Functional Laterality, Macaca fascicularis, Magnetic Resonance Imaging, Male, Mesencephalon, Motion Perception, Neurons, Orientation, Photic Stimulation, Predictive Value of Tests, Reward, Saccades, Time Factors, Tyrosine 3-Monooxygenase, Feedback, Physiological
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
