The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.
Convergent Processing of Both Positive and Negative Motivational Signals by the VTA Dopamine Neuronal Populations
Open accessAbstract
Dopamine neurons in the ventral tegmental area (VTA) have been traditionally studied for their roles in reward-related motivation or drug addiction. Here we study how the VTA dopamine neuron population may process fearful and negative experiences as well as reward information in freely behaving mice. Using multi-tetrode recording, we find that up to 89% of the putative dopamine neurons in the VTA exhibit significant activation in response to the conditioned tone that predict food reward, while the same dopamine neuron population also respond to the fearful experiences such as free fall and shake events. The majority of these VTA putative dopamine neurons exhibit suppression and offset-rebound excitation, whereas ∼25% of the recorded putative dopamine neurons show excitation by the fearful events. Importantly, VTA putative dopamine neurons exhibit parametric encoding properties: their firing change durations are proportional to the fearful event durations. In addition, we demonstrate that the contextual information is crucial for these neurons to respectively elicit positive or negative motivational responses by the same conditioned tone. Taken together, our findings suggest that VTA dopamine neurons may employ the convergent encoding strategy for processing both positive and negative experiences, intimately integrating with cues and environmental context.
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
“Recent experiments also show that acute stressors are encoded by DA-releasing neurons in the VTA, cause DA sensitization in the NAC, and facilitate drug taking; demonstrating that mesolimbic DA release also encodes negative motivational states and stress responses (Miczek et al 2011; Wang and Tsien 2011).”
From The behavioral, anatomical and pharmacological parallels between social attachment, love and addiction (2012) · cites this paper as Wang and Tsien 2011
In the citing paper
“Some of the stress-related effects of CRF in the NAC shell may be DA-dependent; recall that DA is also modulated by acute and chronic stressors (Miczek et al 2011; Wang and Tsien 2011; Chen et al 2012b).”
From The behavioral, anatomical and pharmacological parallels between social attachment, love and addiction (2012) · cites this paper as Wang and Tsien 2011
In the citing paper
“Thus, although 89% of VTA dopaminergic neurons respond with activation to a conditioned reward, they also respond to fearful events, with the majority of the neurons showing suppression. Interestingly, 25% respond with excitation to both positive and fearful events [101].”
From A neoHebbian framework for episodic memory; role of dopamine-dependent late LTP (2011) · cites this paper as [101]
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
The Mouse Brain in Stereotaxic Coordinates
Paxinos, G. (2001) · Cited by 12,859
Di Chiara, G., & Imperato, A. (1988) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.85.14.5274 · Cited by 4,733
What is the role of dopamine in reward: hedonic impact, reward learning, or incentive salience?
Berridge, K. C., & Robinson, T. E. (1998) · Brain Research Reviews · doi:10.1016/s0165-0173(98)00019-8 · Cited by 4,127
Neural systems of reinforcement for drug addiction: from actions to habits to compulsion
Everitt, B. J., & Robbins, T. W. (2005) · Nature Neuroscience · doi:10.1038/nn1579 · Cited by 3,785
Dopamine, learning and motivation.
Wise, R. A. (2004) · Nature Reviews Neuroscience · doi:10.1038/nrn1406 · Cited by 3,379
NEURAL MECHANISMS OF ADDICTION: The Role of Reward-Related Learning and Memory
Hyman, S. E., Malenka, R. C., & Nestler, E. J. (2006) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.29.051605.113009 · Cited by 2,647
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
The hippocampal-VTA loop: controlling the entry of information into long-term memory
Lisman, J. E., & Grace, A. A. (2005) · Neuron · doi:10.1016/j.neuron.2005.05.002 · Cited by 1,983
An opponent-process theory of motivation. I. Temporal dynamics of affect
Solomon, R. L., & Corbit, J. D. (1974) · Psychological Review · doi:10.1037/h0036128 · Cited by 1,704
Ikemoto, S., & Panksepp, J. (1999) · Brain Research Reviews · doi:10.1016/s0165-0173(99)00023-5 · Cited by 1,450
Multiple dopamine functions at different time courses
Schultz, W. (2007) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.28.061604.135722 · Cited by 1,415
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
The control of firing pattern in nigral dopamine neurons: burst firing
Grace, A., & Bunney, B. (1984) · Journal of Neuroscience · doi:10.1523/jneurosci.04-11-02877.1984 · Cited by 1,346
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
Lateral habenula as a source of negative reward signals in dopamine neurons
Matsumoto, M., & Hikosaka, O. (2007) · Nature · doi:10.1038/nature05860 · Cited by 1,292
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 · cited 1×
“This is interesting in compare with of the finding that dopamine neurons exhibit different peak responses to different values of reward boluses [41].”
ResultUnique properties of mesoprefrontal neurons within a dual mesocorticolimbic dopamine system
Lammel, S., Hetzel, A., Häckel, O., Jones, I., Liss, B., & Roeper, J. (2008) · Neuron · doi:10.1016/j.neuron.2008.01.022 · Cited by 976
Carr, D. B., & Sesack, S. R. (2000) · Journal of Neuroscience · doi:10.1523/jneurosci.20-10-03864.2000 · Cited by 880
Preferential activation of midbrain dopamine neurons by appetitive rather than aversive stimuli
Mirenowicz, J., & Schultz, W. (1996) · Nature · doi:10.1038/379449a0 · Cited by 829
Phasic excitation of dopamine neurons in ventral VTA by noxious stimuli
Brischoux, F., Chakraborty, S., Brierley, D. I., & Ungless, M. A. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0811507106 · Cited by 801
Jhou, T. C., Fields, H. L., Baxter, M. G., Saper, C. B., & Holland, P. C. (2009) · Neuron · doi:10.1016/j.neuron.2009.02.001 · Cited by 696
Ventral Tegmental Area Neurons in Learned Appetitive Behavior and Positive Reinforcement
Fields, H. L., Hjelmstad, G. O., Margolis, E. B., & Nicola, S. M. (2007) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.30.051606.094341 · Cited by 632
Roesch, M. R., Calu, D. J., & Schoenbaum, G. (2007) · Nature Neuroscience · doi:10.1038/nn2013 · Cited by 597
Baliki, M. N., Geha, P., Fields, H. L., & Apkarian, A. V. (2010) · Neuron · doi:10.1016/j.neuron.2010.03.002 · Cited by 572
Mesolimbic dopaminergic pathways in fear conditioning
Pezze, M. A., & Feldon, J. (2004) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2004.09.004 · Cited by 519
Jhou, T. C., Geisler, S., Marinelli, M., Degarmo, B. A., & Zahm, D. S. (2009) · Journal of Comparative Neurology · doi:10.1002/cne.21891 · Cited by 503
Firing modes of midbrain dopamine cells in the freely moving rat
Hyland, B. I., Reynolds, J. N. J., HAY, J. G., Perk, C. G., & Miller, R. (2002) · Neuroscience · doi:10.1016/s0306-4522(02)00267-1 · Cited by 487
An Opponent-Process Theory of Motivation
Solomon, R. L., & Corbit, J. D. (2008) · Cited by 461
Opponent appetitive-aversive neural processes underlie predictive learning of pain relief
Seymour, B., O'Doherty, J. P., Koltzenburg, M., Wiech, K., Frackowiak, R., Friston, K., & Dolan, R. (2005) · Nature Neuroscience · doi:10.1038/nn1527 · Cited by 439
Pan, W.-X., Schmidt, R., Wickens, J. R., & Hyland, B. I. (2005) · The Journal of Neuroscience · doi:10.1523/jneurosci.1478-05.2005 · Cited by 429
Ji, H., & Shepard, P. D. (2007) · Journal of Neuroscience · doi:10.1523/jneurosci.0958-07.2007 · Cited by 388
Karreman, M., & Moghaddam, B. (1996) · Journal of Neurochemistry · doi:10.1046/j.1471-4159.1996.66020589.x · Cited by 357
Real-time chemical responses in the nucleus accumbens differentiate rewarding and aversive stimuli
Roitman, M. F., Wheeler, R. A., Wightman, R. M., & Carelli, R. M. (2008) · Nature Neuroscience · doi:10.1038/nn.2219 · Cited by 343
Diana, M., Pistis, M., Carboni, S., Gessa, G. L., & Rossetti, Z. L. (1993) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.90.17.7966 · Cited by 309
L-DOPA Disrupts Activity in the Nucleus Accumbens during Reversal Learning in Parkinson's Disease
Cools, R., Lewis, S. J. G., Clark, L., Barker, R. A., & Robbins, T. W. (2006) · Neuropsychopharmacology · doi:10.1038/sj.npp.1301153 · Cited by 296
Dopamine Neurons Can Represent Context-Dependent Prediction Error
Nakahara, H., Itoh, H., Kawagoe, R., Takikawa, Y., & Hikosaka, O. (2004) · Neuron · doi:10.1016/s0896-6273(03)00869-9 · Cited by 276
Joshua, M., Adler, A., Mitelman, R., Vaadia, E., & Bergman, H. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.3839-08.2008 · Cited by 273
Miller, J. D., Farber, J., Gatz, P., Roffwarg, H. P., & German, D. C. (1983) · Brain Research · doi:10.1016/0006-8993(83)91101-0 · Cited by 269
Coupled Oscillator Model of the Dopaminergic Neuron of the Substantia Nigra
Wilson, C. J., & Callaway, J. C. (2000) · Journal of Neurophysiology · doi:10.1152/jn.2000.83.5.3084 · Cited by 261
Margolis, E. B., Mitchell, J., Ishikawa, J., Hjelmstad, G. O., & Fields, H. L. (2008) · Journal of Neuroscience · doi:10.1523/jneurosci.1526-08.2008 · Cited by 239
Depaulis, A., Keay, K. A., & Bandler, R. J. (1992) · Experimental Brain Research · doi:10.1007/bf00227243 · Cited by 212
Guarraci, F. A., & Kapp, B. S. (1999) · Behavioural Brain Research · doi:10.1016/s0166-4328(98)00102-8 · Cited by 201
Ventura, R., Morrone, C., & Puglisi‐Allegra, S. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0610178104 · Cited by 190
Lin, L., Osan, R. M., Shoham, S., Jin, W., Zuo, W., & Tsien, J. Z. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0408233102 · Cited by 118
Self-citationThe dynamics of dopamine in control of motor behavior
Joshua, M., Adler, A., & Bergman, H. (2009) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2009.10.001 · Cited by 117
Lee, R., Steffensen, S. C., & Henriksen, S. J. (2001) · Journal of Neuroscience · doi:10.1523/jneurosci.21-05-01757.2001 · Cited by 109
Large-scale neural ensemble recording in the brains of freely behaving mice
Lin, L., Chen, G., Xie, K., Zaia, K. A., Zhang, S., & Tsien, J. Z. (2006) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2005.12.032 · Cited by 108
Self-citationKiyatkin, E. A., & Rebec, G. V. (1998) · Neuroscience · doi:10.1016/s0306-4522(98)00054-2 · Cited by 107
Synchronization of Midbrain Dopaminergic Neurons Is Enhanced by Rewarding Events
Joshua, M., Adler, A., Prut, Y., Vaadia, E., Wickens, J. R., & Bergman, H. (2009) · Neuron · doi:10.1016/j.neuron.2009.04.026 · Cited by 91
Nucleus accumbens dopamine and learned fear revisited: a review and some new findings
Levita, L., Dalley, J. W., & Robbins, T. W. (2002) · Behavioural Brain Research · doi:10.1016/s0166-4328(02)00287-5 · Cited by 82
Methods for Studying Functional Interactions Among Neuronal Populations
Narayanan, N. S., & Laubach, M. (2008) · Methods in molecular biology · doi:10.1007/978-1-59745-543-5_7 · Cited by 55
Electrical Coupling Between Model Midbrain Dopamine Neurons: Effects on Firing Pattern and Synchrony
Komendantov, A. O., & Canavier, C. C. (2002) · Journal of Neurophysiology · doi:10.1152/jn.00255.2001 · Cited by 42
Do Substantia Nigra Dopaminergic Neurons Differentiate Between Reward and Punishment?
Frank, M., & Surmeier, D. J. (2009) · Journal of Molecular Cell Biology · doi:10.1093/jmcb/mjp010 · Cited by 11
Flagged first, then by citations
Cited by
Sorted by citations
Updating dopamine reward signals
Schultz, W. (2013) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2012.11.012 · Cited by 651
A neoHebbian framework for episodic memory; role of dopamine-dependent late LTP
Lisman, J., Grace, A. A., & Duzel, E. (2011) · Trends in Neurosciences · doi:10.1016/j.tins.2011.07.006 · Cited by 465
Are you or aren’t you? Challenges associated with physiologically identifying dopamine neurons
Ungless, M. A., & Grace, A. A. (2012) · Trends in Neurosciences · doi:10.1016/j.tins.2012.02.003 · Cited by 450
Burkett, J. P., & Young, L. J. (2012) · Psychopharmacology · doi:10.1007/s00213-012-2794-x · Cited by 307
“experiments also show that acute stressors are encoded by DA-releasing neurons in the ventral tegmental area (VTA), cause DA sensitization in the NAC, and facilitate drug taking, demonstrating that mesolimbic DA release also encodes negative motivational states and stress responses (Miczek et al. 2011; Wang and Tsien…”
InfluentialNeuronal circuits underlying acute morphine action on dopamine neurons
Jalabert, M., Bourdy, R., Courtin, J., Veinante, P., Manzoni, O. J., Barrot, M., & Georges, F. E. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1105418108 · Cited by 302
Metadata
- Authors
- Wang, D. V., & Tsien, J. Z.
- Affiliations
- East China Normal University (CN)
- Corresponding author
- Tsien, Joe Z.
- ORCID
- Wang, Dong V.
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2011-02-15
- Volume
- 6
- Issue
- 2
- Pages
- e17047
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC3039659
- OpenAlex
- W2083000736
- Cited by
- 116
- References
- 53
- Citations by year
- 2026: 2 · 2025: 8 · 2024: 5 · 2023: 1 · 2022: 4 · 2021: 4 · 2020: 6 · 2019: 6 · 2018: 6 · 2017: 5 · 2016: 8 · 2015: 7 · 2014: 17 · 2013: 13 · 2012: 17
- FWCI
- 7.15
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS ONE (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Funders
- Georgia Research Alliance
- National Institute on Aging (AG025918, R01AG034663, AG024022, R01AG025918, AG034663, R01AG024022)
- National Institute of Mental Health (MH060236, R01MH060236)
- 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 and Behavioral Psychology Studies
- Keywords
- ventral tegmental area, dopaminergic neurons, fear, reward, contextual modulation, free fall, mice
- MeSH terms
- Animals, Fear, Male, Mice, Inbred C57BL, Motivation, Time Factors, Ventral Tegmental Area, 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 ›
Are you an author, or do you see a problem with this page? Request a review
