The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.
Neuron-type-specific signals for reward and punishment in the ventral tegmental area
Open accessAbstract
Dopamine has a central role in motivation and reward. Dopaminergic neurons in the ventral tegmental area (VTA) signal the discrepancy between expected and actual rewards (that is, reward prediction error), but how they compute such signals is unknown. We recorded the activity of VTA neurons while mice associated different odour cues with appetitive and aversive outcomes. We found three types of neuron based on responses to odours and outcomes: approximately half of the neurons (type I, 52%) showed phasic excitation after reward-predicting odours and rewards in a manner consistent with reward prediction error coding; the other half of neurons showed persistent activity during the delay between odour and outcome that was modulated positively (type II, 31%) or negatively (type III, 18%) by the value of outcomes. Whereas the activity of type I neurons was sensitive to actual outcomes (that is, when the reward was delivered as expected compared to when it was unexpectedly omitted), the activity of type II and type III neurons was determined predominantly by reward-predicting odours. We 'tagged' dopaminergic and GABAergic neurons with the light-sensitive protein channelrhodopsin-2 and identified them based on their responses to optical stimulation while recording. All identified dopaminergic neurons were of type I and all GABAergic neurons were of type II. These results show that VTA GABAergic neurons signal expected reward, a key variable for dopaminergic neurons to calculate 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
“one successful theoretical model posits that associative learning is driven by the activity of dopamine neurons in the midbrain, where spiking activity resembles the reward prediction error (RPE) signal in an RL algorithm called temporal difference (TD) learning [1][2][3][4].”
From Emergence of belief-like representations through reinforcement learning (2023) · cites this paper as [3]
In the citing paper
“Animal research indicates that dopaminergic neurons are strongly excited by acute stress and aversive stimuli during adulthood (Brischoux et al., 2009; Cohen et al., 2012; Wenzel et al., 2015; Zweifel et al., 2011).”
From The effects of psychosocial stress on dopaminergic function and the acute stress response (2019) · cites this paper as Cohen et al., 2012
In the citing paper
“they also respond to aversive events [21, 22]”
From The molecular and cellular mechanisms of depression: a focus on reward circuitry (2019) · cites this paper as [22]
In the citing paper
“these changes fail to occur with more-controlled arm, mouth and eye movements in a considerable range of studies2,5,9,13,151,152,154”
From Dopamine reward prediction-error signalling: A two-component response (2016) · cites this paper as [154]
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
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
Millisecond-timescale, genetically targeted optical control of neural activity
Boyden, E. S., Zhang, F., Bamberg, E., Nagel, G., & Deisseroth, K. A. (2005) · Nature Neuroscience · doi:10.1038/nn1525 · Cited by 5,015
Classical conditioning II: Current research and theory.
Black, A. H., & Prokasy, W. F. (1972) · Appleton-Century-Crofts eBooks · Cited by 4,449
Channelrhodopsin-2, a directly light-gated cation-selective membrane channel
Nagel, G., Szellas, T., Huhn, W., Kateriya, S., Adeishvili, N., Berthold, P. R., Ollig, D., Hegemann, P., & Bamberg, E. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1936192100 · Cited by 2,730
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
Swanson, L. W. (1982) · Brain Research Bulletin · doi:10.1016/0361-9230(82)90145-9 · Cited by 1,718
Behavioral Theories and the Neurophysiology of Reward
Schultz, W. (2006) · Annual Review of Psychology · doi:10.1146/annurev.psych.56.091103.070229 · Cited by 1,637
Opioids excite dopamine neurons by hyperpolarization of local interneurons
Johnson, S., & North, R. (1992) · The Journal of Neuroscience · doi:10.1523/jneurosci.12-02-00483.1992 · Cited by 1,637
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
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
Flagged first, then by citations
Cited by
Sorted by citations
Items 701–800 of 1,000
Reward and value coding by dopamine neurons in non-human primates
Alikaya, A., Rack-Wildner, M., & Stauffer, W. R. (2017) · Journal of Neural Transmission · doi:10.1007/s00702-017-1793-9 · Cited by 20
Photoperiod Impacts Nucleus Accumbens Dopamine Dynamics
Jameson, A. N., Siemann, J. K., Melchior, J. R., Calipari, E. S., McMahon, D. G., & Grueter, B. A. (2023) · eNeuro · doi:10.1523/eneuro.0361-22.2023 · Cited by 20
Koyama, S., Mori, M., Kanamaru, S., Sazawa, T., Miyazaki, A., Terai, H., & Hirose, S. (2014) · Physiological Reports · doi:10.14814/phy2.12004 · Cited by 20
Chen, K., Vincis, R., & Fontanini, A. (2019) · Cerebral Cortex · doi:10.1093/cercor/bhz005 · Cited by 19
Signaling models for dopamine-dependent temporal contiguity in striatal synaptic plasticity
Urakubo, H., Yagishita, S., Kasai, H., & Ishii, S. (2020) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1008078 · Cited by 19
The Neural Correlates of Cued Reward Omission
Mollick, J., Chang, L. J., Krishnan, A., Hazy, T. E., Krueger, K. A., Frank, G., Wager, T. D., & O’Reilly, R. C. (2021) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2021.615313 · Cited by 19
Covey, D. P., Hernandez, E., Luján, M. Á., & Cheer, J. F. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.0285-21.2021 · Cited by 19
Zhou, H., Zhu, J., Jia, J., Xiang, W., Peng, H., Zhang, Y., Liu, B., Mu, Y., & Lu, Y. (2022) · Neurobiology of Stress · doi:10.1016/j.ynstr.2022.100492 · Cited by 19
Neural mechanisms underlying uninstructed orofacial movements during reward-based learning behaviors
Li, W., Nakano, T., Mizutani, K., Matsubara, T., Kawatani, M., Mukai, Y., Danjo, T., Ito, H., Aizawa, H., Yamanaka, A., et al. (2023) · Current Biology · doi:10.1016/j.cub.2023.07.013 · Cited by 20
Cho, K. K. A., & Sohal, V. S. (2014) · Human Molecular Genetics · doi:10.1093/hmg/ddu225 · Cited by 19
Computational Classification Approach to Profile Neuron Subtypes from Brain Activity Mapping Data
Li, M., Zhao, F., Lee, J., Wang, D., Kuang, H., & Tsien, J. Z. (2015) · Scientific Reports · doi:10.1038/srep12474 · Cited by 19
Berthet, P., Lindahl, M., Tully, P. J., Kotaleski, J. H., & Lansner, A. (2016) · Frontiers in Neural Circuits · doi:10.3389/fncir.2016.00053 · Cited by 19
Is the encoding of Reward Prediction Error reliable during development?
Keren, H., Chen, G., Benson, B. E., Ernst, M., Leibenluft, E., Fox, N. A., Pine, D. S., & Stringaris, A. K. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.05.039 · Cited by 19
Dopamine and relapse to drug seeking
Liu, Y., & McNally, G. P. (2021) · Journal of Neurochemistry · doi:10.1111/jnc.15309 · Cited by 19
Amissah, R. Q., Basha, D., Bukhtiyarova, O., Timofeeva, E., & Timofeev, I. (2021) · Physiology & Behavior · doi:10.1016/j.physbeh.2021.113604 · Cited by 18
The reward for placebos: mechanisms underpinning placebo-induced effects on motor performance
Brietzke, C., Cesario, J., Hettinga, F. J., & Pires, F. O. (2022) · European Journal of Applied Physiology · doi:10.1007/s00421-022-05029-8 · Cited by 18
Sex‐Specific Adaptations to VTA Circuits Following Subchronic Stress
Bouarab, C., Wynalda, M., Thompson, B. V., Khurana, A., Cody, C. R., Kisner, A., & Polter, A. M. (2025) · European Journal of Neuroscience · doi:10.1111/ejn.70153 · Cited by 18
Hamed, A., & Kursa, M. B. (2018) · Brain Structure and Function · doi:10.1007/s00429-018-1683-4 · Cited by 19
Kramar, C. P., Díaz, F. C., Gigante, E. D., Medina, J. H., & Barbano, M. F. (2020) · European Journal of Neuroscience · doi:10.1111/ejn.15076 · Cited by 18
Retrorubral field is a hub for diverse threat and aversive outcome signals
Moaddab, M., & McDannald, M. A. (2021) · Current Biology · doi:10.1016/j.cub.2021.02.055 · Cited by 18
A Whole-Brain Connectivity Map of VTA and SNc Glutamatergic and GABAergic Neurons in Mice
An, S., Li, X., Deng, L., Zhao, P., Ding, Z., Han, Y., Luo, Y., Liu, X., Li, A., Luo, Q., et al. (2021) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2021.818242 · Cited by 18
Pradel, K., Błasiak, T., & Solecki, W. (2017) · Neuroscience · doi:10.1016/j.neuroscience.2017.11.002 · Cited by 18
Decreases in Cued Reward Seeking After Reward-Paired Inhibition of Mesolimbic Dopamine
Fischbach-Weiss, S., & Janak, P. H. (2019) · Neuroscience · doi:10.1016/j.neuroscience.2019.04.035 · Cited by 18
Sleep and motivated behaviors, from physiology to pathology
Sotelo, M. I., Tyan, J., Dzera, J., & Eban-Rothschild, A. (2020) · Current Opinion in Physiology · doi:10.1016/j.cophys.2020.01.006 · Cited by 18
Proietti, R., Parr, T., Tessari, A., Friston, K. J., & Pezzulo, G. (2025) · Physics of Life Reviews · doi:10.1016/j.plrev.2025.05.008 · Cited by 17
Median Raphe Nonserotonergic Neurons Modulate Hippocampal Theta Oscillations
Huang, W., Ikemoto, S., & Wang, D. V. (2022) · Journal of Neuroscience · doi:10.1523/jneurosci.1536-21.2022 · Cited by 19
Tropical support vector machines: Evaluations and extension to function spaces
Yoshida, R., Takamori, M., Matsumoto, H., & Miura, K. (2022) · Neural Networks · doi:10.1016/j.neunet.2022.10.002 · Cited by 20
Jürgensen, A.-M., Sakagiannis, P., Schleyer, M., Gerber, B., & Nawrot, M. P. (2023) · iScience · doi:10.1016/j.isci.2023.108640 · Cited by 17
A chemogenetic approach for dopamine imaging with tunable sensitivity
Labouesse, M. A., Wilhelm, M., Kagiampaki, Z., Yee, A. G., Denis, R., Harada, M., Gresch, A., Marinescu, A., Otomo, K., Curreli, S., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-49442-3 · Cited by 19
Wood, J. T., Simon, N. W., Koerner, F. S., Kass, R. E., & Moghaddam, B. (2017) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2017.00140 · Cited by 17
Siemann, J. K., Grueter, B. A., & McMahon, D. G. (2020) · Neuroscience · doi:10.1016/j.neuroscience.2020.12.010 · Cited by 17
He, Z., Jiang, Y., Gu, S., Wu, D., Qin, D., Feng, G., Ma, X., Huang, J. H., & Wang, F. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.713762 · Cited by 17
The mesolimbic system and eating addiction: what sugar does and does not do
de Jong, J. W., Vanderschuren, L. J. M. J., & Adan, R. A. H. (2016) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2016.03.004 · Cited by 17
Srejic, L. R., Wood, K. M., Zeqja, A., Hashemi, P., & Hutchison, W. D. (2016) · Neurobiology of Disease · doi:10.1016/j.nbd.2016.06.009 · Cited by 17
Aversive stimuli bias corticothalamic responses to motivationally significant cues
Lucantonio, F., Kim, E., Su, Z., Chang, A. J., Bari, B. A., & Cohen, J. Y. (2021) · eLife · doi:10.7554/elife.57634 · Cited by 17
Self-citationDopamine modulates visual threat processing in the superior colliculus via D2 receptors
Montardy, Q., Zhou, Z., Li, L., Yang, Q., Lei, Z., Feng, X., Chen, S., Shi, Q., Zhang, H., Chen, S., et al. (2022) · iScience · doi:10.1016/j.isci.2022.104388 · Cited by 17
Hawkins, R. D. (2013) · Learning & Memory · doi:10.1101/lm.031237.113 · Cited by 17
Ma, X., Zheng, C. Y., Chen, Y., Pereira, F., & Li, Z. (2022) · Cerebral Cortex · doi:10.1093/cercor/bhac205 · Cited by 16
Asymmetric and adaptive reward coding via normalized reinforcement learning
Louie, K. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010350 · Cited by 16
Plasticity of neuronal dynamics in the lateral habenula for cue-punishment associative learning
Congiu, M., Mondoloni, S., Zouridis, I. S., Schmors, L., Lecca, S., Lalive, A. L., Ginggen, K., Deng, F., Berens, P., Paolicelli, R. C., et al. (2023) · Molecular Psychiatry · doi:10.1038/s41380-023-02155-3 · Cited by 16
Hamati, R., Ahrens, J., Shvetz, C., Holahan, M. R., & Tuominen, L. J. (2023) · European Journal of Neuroscience · doi:10.1111/ejn.16157 · Cited by 16
Harada, M., Capdevila, L. S., Wilhelm, M., Burdakov, D., & Patriarchi, T. (2023) · eLife · doi:10.7554/elife.90158 · Cited by 16
Synthetic surprise as the foundation of the psychedelic experience
Filippo, R. D., & Schmitz, D. (2024) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2024.105538 · Cited by 16
Cone, I., Clopath, C., & Shouval, H. Z. (2024) · Nature Communications · doi:10.1038/s41467-024-50205-3 · Cited by 16
Temporal regularities shape perceptual decisions and striatal dopamine signals
Fritsche, M., Majumdar, A., Strickland, L., Garcia, S. L., Bogacz, R., & Lak, A. (2024) · Nature Communications · doi:10.1038/s41467-024-51393-8 · Cited by 16
Hagena, H., & Manahan‐Vaughan, D. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2402356122 · Cited by 16
Werlen, E., & Jones, M. W. (2015) · Progress in brain research · doi:10.1016/bs.pbr.2015.03.002 · Cited by 16
Case, L. K., Adler-Neal, A. L., Wells, R. E., & Zeidan, F. Z. (2021) · Psychosomatic Medicine · doi:10.1097/psy.0000000000000908 · Cited by 16
A Dynamic Affective Core to Bind the Contents, Context, and Value of Conscious Experience
Kishida, K. T., & Sands, L. P. (2021) · Springer eBooks · doi:10.1007/978-3-030-82965-0_12 · Cited by 16
Neural Computation and Neuromodulation Underlying Social Behavior
Bergan, J. F. (2015) · Integrative and Comparative Biology · doi:10.1093/icb/icv061 · Cited by 16
What is a cognitive map? Organising knowledge for flexible behaviourPreprint
Behrens, T. E. J., Müller, T., Whittington, J. C. R., Mark, S., Baram, A. B., Stachenfeld, K., & Kurth-Nelson, Z. L. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/365593 · Cited by 16
Neuron Interaction Based Representation Composition for Neural Machine Translation
Li, J., Wang, X., Yang, B., Shi, S., Lyu, M. R.-T., & Tu, Z. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v34i05.6334 · Cited by 15
Sippy, T., Chaimowitz, C., Crochet, S., & Petersen, C. C. H. (2021) · Function · doi:10.1093/function/zqab049 · Cited by 13
A striatal SOM-driven ChAT-iMSN loop generates beta oscillations and produces motor deficits
Qian, D., Li, W., Xue, J., Wu, Y., Wang, Z., Shi, T., Li, S., Yang, J., Qiu, S., Wang, S., et al. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.111111 · Cited by 15
Dopamine Release in the Nucleus Accumbens Core Encodes the General Excitatory Components of Learning
Taira, M., Millard, S. J., Verghese, A., DiFazio, L. E., Hoang, I. B., Jia, R., Sias, A. C., Wikenheiser, A. M., & Sharpe, M. J. (2024) · Journal of Neuroscience · doi:10.1523/jneurosci.0120-24.2024 · Cited by 15
Xu, T., Zhang, L., Zhou, F., Fu, K., Gan, X., Chen, Z., Zhang, R., Lan, C., Wang, L., Kendrick, K. M., et al. (2025) · Communications Biology · doi:10.1038/s42003-025-07561-7 · Cited by 15
Zafiri, D., Salinas-Hernández, X. I., Biasi, E. S. D., Rebelo, L., & Duvarci, S. (2025) · Nature Communications · doi:10.1038/s41467-025-58382-5 · Cited by 15
Learning deficits in rats overexpressing the dopamine transporter
Bernhardt, N. R., Lieser, M. K., Hlusicka, E. B., Habelt, B., Wieske, F., Edemann-Callesen, H., Garthe, A., & Winter, C. (2018) · Scientific Reports · doi:10.1038/s41598-018-32608-7 · Cited by 15
Kim, H., Brünner, H., & Carlén, M. (2020) · Scientific Reports · doi:10.1038/s41598-020-68783-9 · Cited by 15
Involvement of the dopaminergic system in the reward-related behavior of pregabalin
Althobaiti, Y. S., Almutairi, F. M., Alshehri, F. S., Altowairqi, E., Marghalani, A. M., Alghorabi, A. A., Alsanie, W. F., Gaber, A., Alsaab, H. O., Almalki, A. H., et al. (2021) · Scientific Reports · doi:10.1038/s41598-021-88429-8 · Cited by 15
Clinical applicability of optogenetic gene regulation
Wichert, N., Witt, M., Blume, C. A., & Scheper, T. H. (2021) · Biotechnology and Bioengineering · doi:10.1002/bit.27895 · Cited by 15
Rahaman, S. M., Chowdhury, S., Mukai, Y., Ono, D., Yamaguchi, H., & Yamanaka, A. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.877054 · Cited by 15
Fredericksen, K. E., & Samuelsen, C. L. (2022) · Journal of Neuroscience · doi:10.1523/jneurosci.0674-22.2022 · Cited by 15
Lu, C., Zhu, X., Feng, Y., Ao, W., Li, J., Gao, Z., Luo, H., Chen, M., Cai, F., Zhan, S., et al. (2023) · Molecular Psychiatry · doi:10.1038/s41380-023-01982-8 · Cited by 15
Neural responses to reward valence and magnitude from pre- to early adolescence
Polack, R. G., Mollick, J., Keren, H., Joormann, J., & Watts, R. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120166 · Cited by 17
GABA Neurons in the Ventral Tegmental Area Responding to Peripheral Sensory Input
Liu, C., Gao, M., Jin, G.-Z., & Zhen, X. (2012) · PLoS ONE · doi:10.1371/journal.pone.0051507 · Cited by 15
NMDA receptor deletion on dopamine neurons disrupts visual discrimination and reversal learning
Radke, A. K., Zweifel, L. S., & Holmes, A. (2019) · Neuroscience Letters · doi:10.1016/j.neulet.2019.02.001 · Cited by 15
Doyon, W. M., Ostroumov, A., Ontiveros, T., Gonzales, R. A., & Dani, J. A. (2020) · Addiction Biology · doi:10.1111/adb.12899 · Cited by 15
Csikós, V., Varró, P., Bódi, V., Oláh, S., Világi, I., & Dobolyi, Á. (2020) · Archives of Toxicology · doi:10.1007/s00204-020-02791-6 · Cited by 15
Ruigrok, S. R., Kotah, J. M., Kuindersma, J. E., Speijer, E., van Irsen, A. A. S., la Fleur, S. E., & Kőrösi, A. (2021) · Neurobiology of Stress · doi:10.1016/j.ynstr.2021.100360 · Cited by 15
Social modulation of learned behavior by dopamine in the basal ganglia: Insights from songbirds
Leblois, A. (2012) · Journal of Physiology-Paris · doi:10.1016/j.jphysparis.2012.09.002 · Cited by 15
Obesity decreases excitability of putative ventral tegmental area GABAergic neurons
Koyama, S., Kawaharada, M., Terai, H., Ohkurano, M., Mori, M., Kanamaru, S., & Hirose, S. (2013) · Physiological Reports · doi:10.1002/phy2.126 · Cited by 15
Remembering rewarding futures: A simulation‐selection model of the hippocampus
Jung, M. W., Lee, H., Jeong, Y., Lee, J. W., & Lee, I. (2018) · Hippocampus · doi:10.1002/hipo.23023 · Cited by 16
Vich, C., Dunovan, K., Verstynen, T., & Rubin, J. E. (2019) · Communications in Nonlinear Science and Numerical Simulation · doi:10.1016/j.cnsns.2019.105048 · Cited by 15
Functional MRI of large scale activity in behaving micePreprint
Fonseca, M. S., Bergomi, M. G., Mainen, Z. F., & Shemesh, N. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.04.16.044941 · Cited by 15
Madden, M. B., Schaefgen, C., Vedak, B., Kwon, J., Pedra, K. S. D., Sheats, S. H., Puché, A. C., Wolff, S. B. E., & Mathur, B. N. (2025) · Nature Communications · doi:10.1038/s41467-025-62980-8 · Cited by 14
Parvalbumin-expressing basal forebrain neurons mediate learning from negative experience
Hegedüs, P., Király, B., Schlingloff, D., Lyakhova, V., Velencei, A., Szabó, Í., Mayer, M. I., Zelenak, Z., Nyíri, G., & Hangya, B. (2024) · Nature Communications · doi:10.1038/s41467-024-48755-7 · Cited by 14
Kim, M. J., Gibson, D. J., Hu, D., Yoshida, T., Hueske, E., Matsushima, A., Mahar, A., Schofield, C. J., Sompolpong, P., Tran, K. T., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-53176-7 · Cited by 14
Ding, M., Tomsick, P. L., Young, R. A., & Jadhav, S. P. (2025) · Journal of Neuroscience · doi:10.1523/jneurosci.1670-24.2025 · Cited by 14
Lozano, D. D., Morona, R., González, A., & López, J. M. (2019) · Brain Behavior and Evolution · doi:10.1159/000503769 · Cited by 14
Cell-Type-Specific Optogenetic Techniques Reveal Neural Circuits Crucial for Episodic Memories
Yamamoto, N., Marks, W. D., & 北村, 貴. (2021) · Advances in experimental medicine and biology · doi:10.1007/978-981-15-8763-4_28 · Cited by 14
Stress Controllability Modulates Basal Activity of Dopamine Neurons in the Substantia Nigra Compacta
Li, Y., Li, Y., Diao, Z., Di, Y., Wu, M., Wei, C., Qian, Z., Liu, Z., Han, J., Fan, J., et al. (2021) · eNeuro · doi:10.1523/eneuro.0044-21.2021 · Cited by 14
Remote Optogenetics Using Up/Down-Conversion Phosphors
Matsubara, T., & Yamashita, T. (2021) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2021.771717 · Cited by 14
Tong, Y., Pfeiffer, L., Serchov, T., Coenen, V. A., & Döbrössy, M. D. (2022) · Journal of Neuroscience Research · doi:10.1002/jnr.25014 · Cited by 14
The dopamine circuit as a reward-taxis navigation system
Karin, O., & Alon, U. S. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010340 · Cited by 14
What Role Does Striatal Dopamine Play in Goal-directed Action?
Hart, G., Burton, T. J., & Balleine, B. W. (2024) · Neuroscience · doi:10.1016/j.neuroscience.2024.03.020 · Cited by 14
Fast transmission from the dopaminergic ventral midbrain to the sensory cortex of awake primates
Mylius, J., Happel, M. F. K., Gorkin, A. G., Huang, Y., Scheich, H., & Brosch, M. (2014) · Brain Structure and Function · doi:10.1007/s00429-014-0855-0 · Cited by 14
Dopamine and serotonin signals for reward across time scales
Cohen, J. Y. (2015) · Science · doi:10.1126/science.aad3003 · Cited by 14
Self-citationDer-Ghazarian, T. S., Charmchi, D., Noudali, S. N., Scott, S. N., Holter, M. C., Newbern, J. M., & Neisewander, J. L. (2019) · ACS Chemical Neuroscience · doi:10.1021/acschemneuro.8b00709 · Cited by 14
Layer- and Cell Type-Specific Response Properties of Gustatory Cortex Neurons in Awake Mice
Dikeçligil, G. N., Graham, D. M., Park, I. M., & Fontanini, A. (2020) · Journal of Neuroscience · doi:10.1523/jneurosci.1579-19.2020 · Cited by 14
Aroni, S., Marino, R. A. M., Girven, K. S., Irving, J. M., Cheer, J. F., & Sparta, D. R. (2021) · Neuropharmacology · doi:10.1016/j.neuropharm.2021.108527 · Cited by 14
Neural Integration of Audiovisual Sensory Inputs in Macaque Amygdala and Adjacent Regions
Shan, L., Liu, Y. M., Zhang, B., Ma, J., Xu, X. L., Gu, F., Jiang, Y., & Dai, J. (2023) · Neuroscience Bulletin · doi:10.1007/s12264-023-01043-8 · Cited by 13
Stocke, S., & Samuelsen, C. L. (2024) · Journal of Neuroscience · doi:10.1523/jneurosci.0071-24.2024 · Cited by 13
Contextual cues facilitate dynamic value encoding in the mesolimbic dopamine system
Fraser, K. M., Collins, V. L., Wolff, A. R., Ottenheimer, D. J., Bornhoft, K. N., Pat, F., Chen, B. J., Janak, P. H., & Saunders, B. T. (2025) · Current Biology · doi:10.1016/j.cub.2024.12.031 · Cited by 15
A Causal Role for the Pedunculopontine Nucleus in Human Instrumental Learning
Skvortsova, V., Palminteri, S., Buot, A., Karachi, C., Welter, M., Grabli, D., & Pessiglione, M. (2020) · Current Biology · doi:10.1016/j.cub.2020.11.042 · Cited by 13
Characterizing and TRAPing a Social Stress-Activated Neuronal Ensemble in the Ventral Tegmental Area
Koutlas, I., Linders, L. E., van der Starre, S. E., Wolterink‐Donselaar, I. G., Adan, R. A. H., & Meye, F. J. (2022) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2022.936087 · Cited by 13
Involvement of the GABAergic Septo-Hippocampal Pathway in Brain Stimulation Reward
Vega‐Flores, G., Gruart, A., & Delgado-Garcia, J. M. (2014) · PLoS ONE · doi:10.1371/journal.pone.0113787 · Cited by 13
Response Patterns of GABAergic Neurons in the Anterior Piriform Cortex of Awake Mice
Hu, R. K., Zhang, J.-E., Luo, M., & Hu, J. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw175 · Cited by 13
Rosales, J.-H., Zamarripa, M. S., Ramos, F., & Ramos, M. A. (2017) · Biologically Inspired Cognitive Architectures · doi:10.1016/j.bica.2017.09.003 · Cited by 13
Fuller, J., Burrell, M., Yee, A. G., Liyanagama, K., Lipski, J., Wickens, J. R., & Hyland, B. I. (2019) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2019.101681 · Cited by 13
Metadata
- Authors
- Cohen, J. Y., Haesler, S., Vong, L., Lowell, B. B., & Uchida, N.
- Affiliations
- Harvard University (US)
- Beth Israel Deaconess Medical Center (US)
- Corresponding author
- Uchida, Naoshige
- Venue
- Nature
- Published
- 2012-01-18
- Volume
- 482
- Issue
- 7383
- Pages
- 85-88
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC3271183
- OpenAlex
- W2022561563
- Cited by
- 1,318
- References
- 39
- Citations by year
- 2026: 52 · 2025: 115 · 2024: 90 · 2023: 78 · 2022: 99 · 2021: 116 · 2020: 113 · 2019: 106 · 2018: 100 · 2017: 83 · 2016: 88 · 2015: 102 · 2014: 69 · 2013: 63 · 2012: 43
- FWCI
- 36.51
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Howard Hughes Medical Institute
- National Institute of Mental Health (R01MH095953)
- National Institute of Diabetes and Digestive and Kidney Diseases (P30DK057521, R01DK075632, R01DK089044, P30DK046200, F32DK078478)
- 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 › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Keywords
- ventral tegmental area, dopaminergic neurons, GABAergic neurons, reward prediction error, reward anticipation, aversive stimuli, dopamine, channelrhodopsin-2
- MeSH terms
- Channelrhodopsins, Animals, Cues, Dopamine, gamma-Aminobutyric Acid, Male, Mice, Inbred C57BL, Odorants, Punishment, Reward, Ventral Tegmental Area, Principal Component Analysis, Mice, Dopaminergic Neurons, GABAergic 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
