The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.
Cell-type-specific asynchronous modulation of PKA by dopamine in learning
Open accessAbstract
Reinforcement learning models postulate that neurons that release dopamine encode information about action and action outcome, and provide a teaching signal to striatal spiny projection neurons in the form of dopamine release 1. Dopamine is thought to guide learning via dynamic and differential modulation of protein kinase A (PKA) in each class of spiny projection neuron 2. However, the real-time relationship between dopamine and PKA in spiny projection neurons remains untested in behaving animals. Here we monitor the activity of dopamine-releasing neurons, extracellular levels of dopamine and net PKA activity in spiny projection neurons in the nucleus accumbens of mice during learning. We find positive and negative modulation of dopamine that evolves across training and is both necessary and sufficient to explain concurrent fluctuations in the PKA activity of spiny projection neurons. Modulations of PKA in spiny projection neurons that express type-1 and type-2 dopamine receptors are dichotomous, such that these neurons are selectively sensitive to increases and decreases, respectively, in dopamine that occur at different phases of learning. Thus, PKA-dependent pathways in each class of spiny projection neuron are asynchronously engaged by positive or negative dopamine signals during learning.
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
“Real-time monitoring of the kinase activity in behaving animals indicates that DA release, via regulation of intracellular cAMP production, controls the activity of protein kinase A (PKA) in SPNs over the timescale of tens of seconds, with differential effects on neurons that express type 1 or type 2 dopamine receptors.122”
From Synaptic and circuit functions of multitransmitter neurons in the mammalian brain (2023) · cites this paper as [122]
In the citing paper
“the dopamine, GABA, and glutamate released by DANs may elicit prolonged waves of postsynaptic effects, cascading from the millisecond changes in excitability triggered by ionotropic receptors, to the tens of seconds on biochemical signaling and excitability 109,115,122,123 (Figure 3A).”
From Synaptic and circuit functions of multitransmitter neurons in the mammalian brain (2023) · cites this paper as [122]
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
Glutamate neurotoxicity and diseases of the nervous system
Choi, D. W. (1988) · Neuron · doi:10.1016/0896-6273(88)90162-6 · Cited by 8,188
Ultrasensitive fluorescent proteins for imaging neuronal activity
Chen, T.-W., Wardill, T. J., Sun, Y., Pulver, S. R., Renninger, S. L., Baohan, A., Schreiter, E. R., Kerr, R. A., Orger, M. B., Jayaraman, V., et al. (2013) · Nature · doi:10.1038/nature12354 · Cited by 6,474
D 1 and D 2 Dopamine Receptor-regulated Gene Expression of Striatonigral and Striatopallidal Neurons
Gerfen, C. R., Engber, T. M., Mahan, L. C., Susel, Z., Chase, T. N., Monsma, F. J., & Sibley, D. R. (1990) · Science · doi:10.1126/science.2147780 · Cited by 2,967
Dopamine in motivational control: rewarding, aversive, and alerting
Bromberg-Martin, E. S., Matsumoto, M., & Hikosaka, O. (2010) · Neuron · doi:10.1016/j.neuron.2010.11.022 · Cited by 2,396
Independent optical excitation of distinct neural populations
Klapoetke, N. C., Murata, Y., Kim, S. S., Pulver, S. R., Birdsey-Benson, A., Cho, Y. K., Morimoto, T. K., Chuong, A. S., Carpenter, E. J., Tian, Z., et al. (2014) · Nature Methods · doi:10.1038/nmeth.2836 · Cited by 2,344
Modulation of Striatal Projection Systems by Dopamine
Gerfen, C. R., & Surmeier, D. J. (2011) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-061010-113641 · Cited by 1,700
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
Phasic Firing in Dopaminergic Neurons Is Sufficient for Behavioral Conditioning
Tsai, H.-C., Zhang, F., Adamantidis, A., Stuber, G. D., Bonci, A., de Lecea, L., & Deisseroth, K. (2009) · Science · doi:10.1126/science.1168878 · Cited by 1,266
Dichotomous dopaminergic control of striatal synaptic plasticity
Shen, W., Flajolet, M., Greengard, P., & Surmeier, D. J. (2008) · Science · doi:10.1126/science.1160575 · Cited by 1,190
Cited by
Sorted by citations
Pushing the frontiers: tools for monitoring neurotransmitters and neuromodulators
Wu, Z., Lin, D., & Li, Y. (2022) · Nature reviews. Neuroscience · doi:10.1038/s41583-022-00577-6 · Cited by 225
Spine dynamics in the brain, mental disorders and artificial neural networks
Kasai, H., Ziv, N. E., Okazaki, H., Yagishita, S., & Toyoizumi, T. (2021) · Nature reviews. Neuroscience · doi:10.1038/s41583-021-00467-3 · Cited by 184
Unique functional responses differentially map onto genetic subtypes of dopamine neurons
Azcorra, M., Gaertner, Z. A., Davidson, C., He, Q., Kim, H., Nagappan, S., Hayes, C. K., Ramakrishnan, C., Fenno, L. E., Kim, Y. S., et al. (2023) · Nature Neuroscience · doi:10.1038/s41593-023-01401-9 · Cited by 172
Dopamine, Updated: Reward Prediction Error and Beyond
Lerner, T. N., Holloway, A. L., & Seiler, J. L. (2020) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2020.10.012 · Cited by 195
Lights, fiber, action! A primer on in vivo fiber photometry
Simpson, E. H., Akam, T., Patriarchi, T., Blanco-Pozo, M., Burgeno, L. M., Mohebi, A., Cragg, S. J., & Walton, M. E. (2023) · Neuron · doi:10.1016/j.neuron.2023.11.016 · Cited by 170
Self-citationImproved green and red GRAB sensors for monitoring dopaminergic activity in vivo
Zhuo, Y., Luo, B., Yi, X., Dong, H., Miao, X., Wan, J., Williams, J. T., Campbell, M. G., Cai, R., Qian, T., et al. (2023) · Nature Methods · doi:10.1038/s41592-023-02100-w · Cited by 174
Spatiotemporally heterogeneous coordination of cholinergic and neocortical activity
Lohani, S., Moberly, A. H., Benisty, H., Landa, B., Jing, M., Li, Y., Higley, M. J., & Cardin, J. A. (2022) · Nature Neuroscience · doi:10.1038/s41593-022-01202-6 · Cited by 150
Dopamine and glutamate regulate striatal acetylcholine in decision-making
Chantranupong, L., Beron, C. C., Zimmer, J. A., Wen, M. J., Wang, W., & Sabatini, B. L. (2023) · Nature · doi:10.1038/s41586-023-06492-9 · Cited by 153
Self-citationHypothalamic dopamine neurons motivate mating through persistent cAMP signalling
Zhang, S. X., Lutas, A., Yang, S., Diaz, A., Fluhr, H., Nagel, G., Gao, S., & Andermann, M. L. (2021) · Nature · doi:10.1038/s41586-021-03845-0 · Cited by 128
Habitual daily intake of a sweet and fatty snack modulates reward processing in humans
Thanarajah, S. E., DiFeliceantonio, A. G., Albus, K., Kuzmanovic, B., Rigoux, L., Iglesias, S., Hanßen, R., Schlamann, M., Cornely, O. A., Brüning, J. C., et al. (2023) · Cell Metabolism · doi:10.1016/j.cmet.2023.02.015 · Cited by 131
A high-performance genetically encoded fluorescent indicator for in vivo cAMP imaging
Wang, L., Wu, C., Peng, W., Zhou, Z., Zeng, J., Li, X., Yang, Y., Yu, S., Zou, Y., Huang, M. S., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-32994-7 · Cited by 104
Self-citationDong, C., Zheng, Y., Long-Iyer, K., Wright, E. C., Li, Y., & Tian, L. (2022) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-110520-031137 · Cited by 99
Self-citationExplaining dopamine through prediction errors and beyond
Gershman, S. J., Assad, J. A., Datta, S. R., Linderman, S. W., Sabatini, B. L., Uchida, N., & Wilbrecht, L. (2024) · Nature Neuroscience · doi:10.1038/s41593-024-01705-4 · Cited by 110
Self-citationStriatal indirect pathway mediates exploration via collicular competition
Lee, J., & Sabatini, B. L. (2021) · Nature · doi:10.1038/s41586-021-04055-4 · Cited by 73
Self-citationHedonic eating is controlled by dopamine neurons that oppose GLP-1R satiety
Zhu, Z., Gong, R., Rodriguez, V., Quach, K. T., Chen, X., & Sternson, S. M. (2025) · Science · doi:10.1126/science.adt0773 · Cited by 85
Locomotion activates PKA through dopamine and adenosine in striatal neurons
Ma, L., Day‐Cooney, J., Jáidar, O., Muniak, M. A., Qin, M., Ding, J., Mao, T., & Zhong, H. (2022) · Nature · doi:10.1038/s41586-022-05407-4 · Cited by 73
Defect engineering of PdMo metallene for sensitive electrochemical detection of dopamine
Zhang, Y., Wang, H., Jiao, L., Wu, N., Xu, W., Wu, Z., Wu, Y., Hu, P., Gu, W., & Zhu, C. (2023) · Chemical Engineering Journal · doi:10.1016/j.cej.2023.143075 · Cited by 71
The nucleus accumbens in reward and aversion processing: insights and implications
Xu, Y., Lin, Y., Yu, M., & Zhou, K. (2024) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2024.1420028 · Cited by 86
Unraveling the dynamics of dopamine release and its actions on target cells
Sippy, T., & Tritsch, N. X. (2023) · Trends in Neurosciences · doi:10.1016/j.tins.2022.12.005 · Cited by 77
Local modulation by presynaptic receptors controls neuronal communication and behaviour
Lovinger, D. M., Mateo, Y., Johnson, K. A., Engi, S. A., Antonazzo, M., & Cheer, J. F. (2022) · Nature reviews. Neuroscience · doi:10.1038/s41583-022-00561-0 · Cited by 69
Dopamine activates astrocytes in prefrontal cortex via α1-adrenergic receptors
Pittolo, S., Yokoyama, S., Willoughby, D. D., Taylor, C. R., Reitman, M. E., Tse, V., Wu, Z., Etchenique, R., Li, Y., & Poskanzer, K. E. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.111426 · Cited by 70
Dopamine in the tail of the striatum facilitates avoidance in threat–reward conflicts
Tsutsui‐Kimura, I., Tian, Z. M., Amo, R., Zhuo, Y., Li, Y., Campbell, M. G., Uchida, N., & Watabe‐Uchida, M. (2025) · Nature Neuroscience · doi:10.1038/s41593-025-01902-9 · Cited by 69
Soares‐Cunha, C., Domingues, A. V., Correia, R. G., Coimbra, B., Vieitas‐Gaspar, N., de Vasconcelos, N. A. P., Pinto, L., Sousa, N., & Rodrigues, A. J. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.110380 · Cited by 57
Action suppression reveals opponent parallel control via striatal circuits
Cruz, B. F., Guiomar, G., Soares, S., Motiwala, A., Machens, C. K., & Paton, J. J. (2022) · Nature · doi:10.1038/s41586-022-04894-9 · Cited by 73
In vivo multiplex imaging of dynamic neurochemical networks with designed far-red dopamine sensors
Zheng, Y. R., Cai, R., Wang, K., Zhang, J., Zhuo, Y., Dong, H., Zhang, Y., Wang, Y., Deng, F., Ji, E., et al. (2025) · Science · doi:10.1126/science.adt7705 · Cited by 69
GPCR-Based Dopamine Sensors—A Detailed Guide to Inform Sensor Choice for In Vivo Imaging
Labouesse, M. A., Cola, R. B., & Patriarchi, T. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21218048 · Cited by 63
Self-citationA versatile GPCR toolkit to track in vivo neuromodulation: not a one-size-fits-all sensor
Labouesse, M. A., & Patriarchi, T. (2021) · Neuropsychopharmacology · doi:10.1038/s41386-021-00982-y · Cited by 60
Self-citationSynaptic and circuit functions of multitransmitter neurons in the mammalian brain
Wallace, M. L., & Sabatini, B. L. (2023) · Neuron · doi:10.1016/j.neuron.2023.06.003 · Cited by 59
Self-citationMaltese, M., March, J. R., Bashaw, A. G., & Tritsch, N. X. (2021) · eLife · doi:10.7554/elife.68041 · Cited by 62
Liraglutide restores impaired associative learning in individuals with obesity
Hanssen, R., Rigoux, L., Kuzmanovic, B., Iglesias, S., Kretschmer, A. C., Schlamann, M., Albus, K., Edwin Thanarajah, S., Sitnikow, T., Melzer, C., et al. (2023) · Nature Metabolism · doi:10.1038/s42255-023-00859-y · Cited by 52
Wu, M., Minkowicz, S., Dumrongprechachan, V., Hamilton, P., Xiao, L., & Kozorovitskiy, Y. (2021) · eLife · doi:10.7554/elife.64041 · Cited by 54
The Development of the Mesoprefrontal Dopaminergic System in Health and Disease
Islam, K. U. S., Meli, N., & Blaess, S. (2021) · Frontiers in Neural Circuits · doi:10.3389/fncir.2021.746582 · Cited by 55
Genetically encoded sensors towards imaging cAMP and PKA activity in vivo
Massengill, C. I., Day‐Cooney, J., Mao, T., & Zhong, H. (2021) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2021.109298 · Cited by 48
A Bright and Colorful Future for G-Protein Coupled Receptor Sensors
Ravotto, L., Duffet, L., Zhou, X., Weber, B., & Patriarchi, T. (2020) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2020.00067 · Cited by 46
Self-citationNigrostriatal dopamine pathway regulates auditory discrimination behavior
Chen, A. P. F., Malgady, J. M., Chen, L., Shi, K. W., Cheng, E., Plotkin, J. L., Ge, S., & Xiong, Q. (2022) · Nature Communications · doi:10.1038/s41467-022-33747-2 · Cited by 46
Neurophotonic tools for microscopic measurements and manipulation: status report
Abdelfattah, A. S., Allu, S., Campbell, R. E., Cheng, X., Čižmár, T., Costantini, I., Emiliani, V., Fomin-Thunemann, N., Gilad, A., Fernández-Alfonso, T., et al. (2022) · Neurophotonics · doi:10.1117/1.nph.9.s1.013001 · Cited by 49
Self-citationZhai, S., Cui, Q., Simmons, D. V., & Surmeier, D. J. (2023) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2023.102798 · Cited by 47
Genetically encoded fluorescent sensors for imaging neuronal dynamics in vivo
Day‐Cooney, J., Dalangin, R., Zhong, H., & Mao, T. (2022) · Journal of Neurochemistry · doi:10.1111/jnc.15608 · Cited by 43
Cheung, T. H. C., Ding, Y., Zhuang, X., & Kang, U. J. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2213093120 · Cited by 38
Adaptive control of synaptic plasticity integrates micro- and macroscopic network function
Scott, D. N., & Frank, M. J. (2022) · Neuropsychopharmacology · doi:10.1038/s41386-022-01374-6 · Cited by 40
Zhou, X., Lee, Y.-K., Li, X., Kim, H., Sánchez-Priego, C., Han, X., Tan, H., Zhou, S., Fu, Y., Purtell, K., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-47440-z · Cited by 38
Neuromodulator regulation and emotions: insights from the crosstalk of cell signaling
Tsuboi, D., Nagai, T., Yoshimoto, J., & Kaibuchi, K. (2024) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2024.1376762 · Cited by 37
Multimodal detection of dopamine by sniffer cells expressing genetically encoded fluorescent sensors
Herenbrink, C. K., Støier, J. F., Reith, W. D., Dagra, A., Gregorek, M. A. C., Cola, R. B., Patriarchi, T., Li, Y., Tian, L., Gether, U., et al. (2022) · Communications Biology · doi:10.1038/s42003-022-03488-5 · Cited by 36
Self-citationFast and slow: Recording neuromodulator dynamics across both transient and chronic time scales
Ma, P., Chen, P., Tilden, E. I., Aggarwal, S., Oldenborg, A., & Chen, Y. (2024) · Science Advances · doi:10.1126/sciadv.adi0643 · Cited by 36
Self-citationLutas, A., Fernando, K., Zhang, S. X., Sambangi, A., & Andermann, M. L. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.110297 · Cited by 30
Jones-Tabah, J., Mohammad, H., Hadj-Youssef, S., Kim, L., Martin, R., Benaliouad, F., Tanny, J. C., Clarke, P. B. S., & Hébert, T. E. (2020) · Scientific Reports · doi:10.1038/s41598-020-71121-8 · Cited by 31
Xenias, H. S., Chen, C., Kang, S., Cherian, S., Situ, X., Shanmugasundaram, B., Liu, G., Scesa, G., Chan, C. S., & Parisiadou, L. (2022) · Communications Biology · doi:10.1038/s42003-022-04136-8 · Cited by 32
Dissociable control of motivation and reinforcement by distinct ventral striatal dopamine receptors
Enríquez-Traba, J., Arenivar, M. A., Yarur, H. E., Noh, C., Flores, R. J., Weil, T. A., Roy, S., Usdin, T. B., LaGamma, C. T., Wang, H., et al. (2024) · Nature Neuroscience · doi:10.1038/s41593-024-01819-9 · Cited by 31
Neuromodulation and Neurophysiology on the Timescale of Learning and Decision-Making
Grossman, C. D., & Cohen, J. Y. (2022) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-092021-125059 · Cited by 30
Nishioka, T., Attachaipanich, S., Hamaguchi, K., Lazarus, M., d’Exaerde, A. D. K., Macpherson, T., & Hikida, T. (2023) · Nature Communications · doi:10.1038/s41467-023-38025-3 · Cited by 29
Dissociable contributions of phasic dopamine activity to reward and prediction
Pan, W. X., Coddington, L. T., & Dudman, J. T. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.109684 · Cited by 29
An opponent striatal circuit for distributional reinforcement learning
Lowet, A. S., Qiao, Z., Meng, M., Matias, S., Drugowitsch, J., & Uchida, N. (2025) · Nature · doi:10.1038/s41586-024-08488-5 · Cited by 30
Alvarado, J. S., Lutas, A., Madara, J. C., Isaac, J., Lommer, C., Massengill, C. I., & Andermann, M. L. (2024) · Neuron · doi:10.1016/j.neuron.2024.02.002 · Cited by 25
Striatal Dopamine Signals and Reward Learning
Bech, P., Crochet, S., Dard, R. F., Ghaderi, P., Liu, Y., Malekzadeh, M., Petersen, C. C. H., Pulin, M., Renard, A., & Sourmpis, C. (2023) · Function · doi:10.1093/function/zqad056 · Cited by 27
Past, Present, and Future of Tools for Dopamine Detection
Zheng, Y., & Li, Y. (2023) · Neuroscience · doi:10.1016/j.neuroscience.2023.06.025 · Cited by 27
Kasai, H. (2023) · Proceedings of the Japan Academy Series B · doi:10.2183/pjab.99.018 · Cited by 25
Pinto, S. R., & Uchida, N. (2025) · Nature Communications · doi:10.1038/s41467-025-62280-1 · Cited by 24
Vasiyani, H., Shinde, A., Roy, M., Mane, M., Singh, K., Singh, J., Gohel, D., Currim, F., Vaidya, K., Chhabria, M. T., et al. (2021) · APOPTOSIS · doi:10.1007/s10495-021-01669-x · Cited by 21
RetractedDiscrete spatiotemporal encoding of striatal dopamine transmission
Yee, A. G., Liao, Y., Muntean, B. S., & Ford, C. (2025) · Science · doi:10.1126/science.adp9833 · Cited by 20
Laverne, G., Pesce, J., Reynders, A., Combrisson, E., Gascon, E., Melon, C., Goff, L. K., Maurice, N., & Beurrier, C. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.111034 · Cited by 25
Visualization of differential GPCR crosstalk in DRD1-DRD2 heterodimer upon different dopamine levels
Kim, H., Nam, M., Jeong, S., Lee, H., Oh, S., Kim, J.-J., Choi, N., & Seong, J. (2022) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2022.102266 · Cited by 19
Fleming, W., Lee, J., Briones, B. A., Bolkan, S. S., & Witten, I. B. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.110874 · Cited by 18
Song, B. J., Ge, Y., Nicolella, A. A., Kwon, M. J., Lodder, B., Bonanno, K., Valle-Tojeiro, A., Hartley, N. D., Mandell, K. P., Adeleye, J., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-66504-2 · Cited by 18
Self-citationNucleus accumbens D1-receptors regulate and focus transitions to reward-seeking action
Grima, L. L., Panayi, M. C., Härmson, O., Syed, E. C. J., Manohar, S., Husain, M., & Walton, M. E. (2022) · Neuropsychopharmacology · doi:10.1038/s41386-022-01312-6 · Cited by 19
Lodder, B., Kamath, T. V., Savenco, E., Röring, B., Siegel, M., Chouinard, J. A., Lee, S. J., Zagoren, C., Rosen, P. C., Hartman, I., et al. (2025) · Neuron · doi:10.1016/j.neuron.2025.08.013 · Cited by 17
Self-citationAdaptive Cost-Benefit Control Fueled by Striatal Dopamine
Frank, M. J. (2025) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-112723-025228 · Cited by 23
Neural encoding of food and monetary reward delivery
Oren, S., Tittgemeyer, M., Rigoux, L., Schlamann, M. U., Schönberg, T., & Kuzmanovic, B. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119335 · Cited by 20
Wei, H., Li, L., Xue, Y., Yu, P., & Mao, L. (2023) · Analytical Chemistry · doi:10.1021/acs.analchem.3c00110 · Cited by 16
Molecular recording of cellular protein kinase activity with chemical labeling
Sun, D., Ng, S. W., Zheng, Y. R., Shu, X., Schwan, N., Breuer, P., Hoffmann, D. C., Michel, J., Azorín, D. D., Boonekamp, K. E., et al. (2025) · Nature Chemical Biology · doi:10.1038/s41589-025-01949-6 · Cited by 15
Fiber photometry-based investigation of brain function and dysfunction
Byron, N., & Sakata, S. (2023) · Neurophotonics · doi:10.1117/1.nph.11.s1.s11502 · Cited by 17
Sato, R., Shimomura, K., & Morita, K. (2023) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1011206 · Cited by 13
Sukhanov, I., Dorotenko, A. R., Fesenko, Z. S., Savchenko, A. A., Efimova, E. V., Mor, M. S., Владимировна, Б. И., Sotnikova, T. D., & Gainetdinov, R. R. (2022) · Biomolecules · doi:10.3390/biom13010009 · Cited by 13
Brykczyńska, D., Kubicki, M., Patroniak, V., Łuczak, T., & Gorczyński, A. (2024) · Electrochimica Acta · doi:10.1016/j.electacta.2023.143754 · Cited by 12
Ueda, H. H., Nagasawa, Y., & Murakoshi, H. (2021) · Neuroscience Research · doi:10.1016/j.neures.2021.10.004 · Cited by 12
Tilden, E. I., Maduskar, A., Oldenborg, A., Sabatini, B. L., & Chen, Y. (2024) · Scientific Reports · doi:10.1038/s41598-024-53313-8 · Cited by 13
Self-citationWang, Y., Perez‐Rosello, T., Smukowski, S. N., Surmeier, D. J., & Savas, J. N. (2024) · Molecular Psychiatry · doi:10.1038/s41380-024-02493-w · Cited by 15
Risi, M. D., Cavezza, D., Torromino, G., Capalbo, A., Cundin, X. B., Martino, R. D., Alvino, F. G., Iemolo, A., Speranza, L., Perrone‐Capano, C., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-57788-5 · Cited by 13
Wang, X., Wang, L., Wu, M., Zheng, Y., Wang, R., Shao, T., Zeng, S., Li, A., Li, R., & Yue, Q. (2025) · Talanta · doi:10.1016/j.talanta.2025.128288 · Cited by 13
From avoidance to new action: the multifaceted role of the striatal indirect pathway
Lee, J., & Sabatini, B. L. (2025) · Nature reviews. Neuroscience · doi:10.1038/s41583-025-00925-2 · Cited by 10
Self-citationBouabid, S., Zhang, L., Vu, M.-A. T., Tang, K., Graham, B. M., Noggle, C. A., & Howe, M. W. (2025) · Nature Communications · doi:10.1038/s41467-025-60462-5 · Cited by 12
Endoplasmic Reticulum in Metaplasticity: From Information Processing to Synaptic Proteostasis
Khan, S. (2022) · Molecular Neurobiology · doi:10.1007/s12035-022-02916-1 · Cited by 11
Zhong, X., Gu, H., Lim, J., Zhang, P., Wang, G., Zhang, K., & Li, X. (2025) · IBRO Neuroscience Reports · doi:10.1016/j.ibneur.2025.03.003 · Cited by 10
Lodder, B., Lee, S. J., & Sabatini, B. L. (2021) · Current Protocols · doi:10.1002/cpz1.265 · Cited by 9
Self-citationDynamics of striatal action selection and reinforcement learning
Lindsey, J. W., Markowitz, J. E., Gillis, W. F., Datta, S. R., & Litwin-Kumar, A. (2025) · eLife · doi:10.7554/elife.101747.3 · Cited by 9
LRRK2 mediates haloperidol-induced changes in indirect pathway striatal projection neurons
Chen, C., Masotti, M., Shepard, N., Promes, V., Tombesi, G., Arango, D., Manzoni, C., Greggio, E., Hilfiker, S., Kozorovitskiy, Y., et al. (2025) · Molecular Psychiatry · doi:10.1038/s41380-025-03030-z · Cited by 8
Purine nucleosides replace cAMP in allosteric regulation of PKA in trypanosomatid pathogens
Ober, V. T., Githure, G. B., Santos, Y. V., Becker, S. M., Munoz, G. M., Basquin, J., Schwede, F., Lorentzen, E., & Boshart, M. (2023) · eLife · doi:10.7554/elife.91040 · Cited by 9
Imaging neuronal protein signaling dynamics in vivo
Laviv, T., & Yasuda, R. (2021) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2021.02.002 · Cited by 8
Unraveling the complex electrochemistry of serotonin using engineered graphitic sensors
Cuniberto, E., Huang, Z., Ward, M. D., & Shahrjerdi, D. (2022) · The Analyst · doi:10.1039/d2an01451c · Cited by 7
Dopaminergic axons track somatic signaling in behaving micePreprint
Azcorra, M., Gaertner, Z. A., Davidson, C., Ramakrishnan, C., Fenno, L. E., Kim, Y. S., Deisseroth, K. A., Awatramani, R. B., & Dombeck, D. A. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.06.20.496872 · Cited by 7
Hunger modulates exploration through suppression of dopamine signaling in the tail of the striatum
Kamath, T. V., Lodder, B., Bilsel, E., Green, I., Dalangin, R., Raghubardayal, M., Wang, W., Capelli, P., Legister, J., Timmins, J., et al. (2025) · Neuron · doi:10.1016/j.neuron.2025.09.009 · Cited by 9
Self-citationJamalzadeh, M., Cuniberto, E., Huang, Z., Feeley, R. M., Patel, J. C., Rice, M. E., UICHANCO, J. A. V., & Shahrjerdi, D. (2024) · The Analyst · doi:10.1039/d3an02086j · Cited by 6
Kato, A., & Morita, K. (2025) · Journal of Neuroscience · doi:10.1523/jneurosci.0170-25.2025 · Cited by 6
Convergence Circuit Mapping: Genetic Approaches From Structure to Function
Yook, J. S., Kim, J., & Kim, J. (2021) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2021.688673 · Cited by 6
Cell type specificity for circuit output in the midbrain dopaminergic system
Blaess, S., & Krabbe, S. (2023) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2023.102811 · Cited by 6
Dynamics of striatal action selection and reinforcement learningPreprint
Lindsey, J. W., Markowitz, J. E., Gillis, W. F., Datta, S. R., & Litwin-Kumar, A. (2024) · eLife · doi:10.7554/elife.101747 · Cited by 6
Dernič, J., Eleftheriou, A., Vasilikos, L., Rauch, M., Imseng, P., Zanker, H. S., Looser, Z. J., Meister, R., Moros, F. V., Kagan, T., et al. (2025) · Communications Biology · doi:10.1038/s42003-025-08677-6 · Cited by 5
Local and long-distance inputs dynamically regulate striatal acetylcholine during decision makingPreprint
Chantranupong, L., Beron, C. C., Zimmer, J. A., Wen, M. J., Wang, W., & Sabatini, B. L. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.09.09.507130 · Cited by 5
Self-citationAxial modulation of Fe sites for boosted electrochemical oxidation
Mao, Z., Li, S., Tan, F., Li, C., Jiao, L., Gu, W., & Luo, X. (2025) · Nanoscale Horizons · doi:10.1039/d5nh00476d · Cited by 4
The promise and peril of comparing fluorescence lifetime in biology revealed by simulations
Ma, P., Chen, P., Sternson, S. M., & Chen, Y. (2025) · eLife · doi:10.7554/elife.101559.3 · Cited by 4
Self-citationLu, X., Xue, J., Lai, Y., & Tang, X. (2024) · The FASEB Journal · doi:10.1096/fj.202302031r · Cited by 4
Metadata
- Authors
- Lee, S. J., Lodder, B., Chen, Y., Patriarchi, T., Tian, L., & Sabatini, B. L.
- Affiliations
- Howard Hughes Medical Institute (US)
- University of Zurich (CH)
- University of California, Davis (US)
- Corresponding author
- Sabatini, Bernardo L.
- Venue
- Nature
- Published
- 2020-12-23
- Volume
- 590
- Issue
- 7846
- Pages
- 451-456
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC7889726
- OpenAlex
- W3116416936
- Cited by
- 160
- References
- 45
- Citations by year
- 2026: 14 · 2025: 35 · 2024: 25 · 2023: 30 · 2022: 33 · 2021: 18 · 2020: 4
- FWCI
- 9.74
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Zurich Open Repository and Archive (University of Zurich) (acceptedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Zurich Open Repository and Archive (University of Zurich) (submittedVersion)
- Zurich Open Repository and Archive (University of Zurich)
- Funders
- Howard Hughes Medical Institute
- National Institutes of Health (U01NS013522, R35NS105107)
- National Institute on Drug Abuse (F32DA035543)
- National Institute of Neurological Disorders and Stroke (P30NS072030, U01NS090604, R37NS046579, U19NS113201)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Keywords
- dopamine, protein kinase A, medium spiny neurons, nucleus accumbens, reinforcement learning, dopamine receptors, dopamine release, learning, striatum
- MeSH terms
- Animals, Dopamine, Female, Fluorescence, Learning, Male, Neuronal Plasticity, Nucleus Accumbens, Photometry, Receptors, Dopamine, Cyclic AMP-Dependent Protein Kinases, 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
