The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
Opposite initialization to novel cues in dopamine signaling in ventral and posterior striatum in mice
Open accessAbstract
Dopamine neurons are thought to encode novelty in addition to reward prediction error (the discrepancy between actual and predicted values). In this study, we compared dopamine activity across the striatum using fiber fluorometry in mice. During classical conditioning, we observed opposite dynamics in dopamine axon signals in the ventral striatum (‘VS dopamine’) and the posterior tail of the striatum (‘TS dopamine’). TS dopamine showed strong excitation to novel cues, whereas VS dopamine showed no responses to novel cues until they had been paired with a reward. TS dopamine cue responses decreased over time, depending on what the cue predicted. Additionally, TS dopamine showed excitation to several types of stimuli including rewarding, aversive, and neutral stimuli whereas VS dopamine showed excitation only to reward or reward-predicting cues. Together, these results demonstrate that dopamine novelty signals are localized in TS along with general salience signals, while VS dopamine reliably encodes 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.
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
Reinforcement Learning: An Introduction
Sutton, R. S., & Barto, A. G. (1998) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.1998.712192 · Cited by 27,225
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
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
Learning to predict by the methods of temporal differences
Sutton, R. S. (1988) · Machine Learning · doi:10.1007/bf00115009 · Cited by 5,148
Elastix: a toolbox for intensity-based medical image registration
Klein, S., Staring, M., Murphy, K., Viergever, M. A., & Pluim, J. (2010) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2009.2035616 · Cited by 4,311
WIDROW, B., & HOFF, M. E. (1960) · doi:10.21236/ad0241531 · Cited by 4,009
Pearce, J. M., & Hall, G. (1980) · Psychological Review · doi:10.1037/0033-295x.87.6.532 · Cited by 3,023 · cited 4×
“Thus, TS dopamine may be specialized for functions apart from value, such as attentional orientation (Redgrave et al., 1999), working attention, and/or as a filter for learning (Braver and Cohen, 1999; Dayan and Sejnowski, 1996; Matsumoto and Takada, 2013; Pearce and Hall, 1980).”
BackgroundResultInfluentialA theory of attention: Variations in the associability of stimuli with reinforcement
Mackintosh, N. J. (1975) · Psychological Review · doi:10.1037/h0076778 · Cited by 2,733
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
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
Self-citation
Cited by
McCutcheon, R. A., Reis Marques, T., & Howes, O. D. (2020) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2019.3360 · Cited by 1,481
Berke, J. D. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0152-y · Cited by 904
Schizophrenia, dopamine and the striatum: From biology to symptoms
McCutcheon, R. A., Abi-Dargham, A., & Howes, O. D. (2019) · Trends in Neurosciences · doi:10.1016/j.tins.2018.12.004 · Cited by 763
Dopamine and glutamate in schizophrenia: biology, symptoms and treatment
McCutcheon, R. A., Krystal, J. H., & Howes, O. D. (2020) · World Psychiatry · doi:10.1002/wps.20693 · Cited by 612
Dopamine and Cognitive Control in Prefrontal Cortex
Ott, T., & Nieder, A. (2019) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2018.12.006 · Cited by 530
Functional circuit architecture underlying parental behaviour
Kohl, J., Babayan, B. M., Rubinstein, N. D., Autry, A. E., Marin-Rodriguez, B., Kapoor, V., Miyamishi, K., Zweifel, L. S., Luo, L., Uchida, N., et al. (2018) · Nature · doi:10.1038/s41586-018-0027-0 · Cited by 444
Self-citationPoulin, J.-F., Caronia, G., Hofer, C., Cui, Q., Helm, B., Ramakrishnan, C., Chan, C. S., Dombeck, D. A., Deisseroth, K., & Awatramani, R. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0203-4 · Cited by 423
What, If, and When to Move: Basal Ganglia Circuits and Self-Paced Action Initiation
Klaus, A., Alves da Silva, J., & Costa, R. M. (2019) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-072116-031033 · Cited by 284
Neural mechanisms of social homeostasis
Matthews, G. A., & Tye, K. M. (2019) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.14016 · Cited by 273
Gershman, S. J., & Uchida, N. (2019) · Nature Reviews Neuroscience · doi:10.1038/s41583-019-0220-7 · Cited by 236
Self-citationImaging neurotransmitter and neuromodulator dynamics in vivo with genetically encoded indicators
Sabatini, B. L., & Tian, L. (2020) · Neuron · doi:10.1016/j.neuron.2020.09.036 · Cited by 203
Bariselli, S., Hörnberg, H., Prévost-Solié, C., Musardo, S., Hatstatt-Burklé, L., Scheiffele, P., & Bellone, C. (2018) · Nature Communications · doi:10.1038/s41467-018-05382-3 · Cited by 171
Model-based predictions for dopamine
Langdon, A. J., Sharpe, M. J., Schoenbaum, G., & Niv, Y. (2018) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2017.10.006 · Cited by 161
Development, wiring and function of dopamine neuron subtypes
Garritsen, O., van Battum, E. Y., Grossouw, L. M., & Pasterkamp, R. J. (2023) · Nature reviews. Neuroscience · doi:10.1038/s41583-022-00669-3 · Cited by 128
Belief state representation in the dopamine system
Babayan, B. M., Uchida, N., & Gershman, S. J. (2018) · Nature Communications · doi:10.1038/s41467-018-04397-0 · Cited by 101
Self-citationAn integrative framework for perceptual disturbances in psychosis
Horga, G., & Abi-Dargham, A. (2019) · Nature Reviews Neuroscience · doi:10.1038/s41583-019-0234-1 · Cited by 103
Dopamine signaling in the nucleus accumbens core mediates latent inhibition
Kutlu, M. G., Zachry, J. E., Melugin, P. R., Tat, J., Cajigas, S., Isiktas, A. U., Patel, D. D., Siciliano, C. A., Schoenbaum, G., Sharpe, M. J., et al. (2022) · Nature Neuroscience · doi:10.1038/s41593-022-01126-1 · Cited by 78
Imaging neuromodulators with high spatiotemporal resolution using genetically encoded indicators
Patriarchi, T., Cho, J. R., Merten, K., Marley, A., Broussard, G. J., Liang, R., Williams, J., Nimmerjahn, A., von Zastrow, M., Gradinaru, V., et al. (2019) · Nature Protocols · doi:10.1038/s41596-019-0239-2 · Cited by 66
Leveraging calcium imaging to illuminate circuit dysfunction in addiction
Siciliano, C. A., & Tye, K. M. (2019) · Alcohol · doi:10.1016/j.alcohol.2018.05.013 · Cited by 53
Nigrostriatal 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
Curiosity: primate neural circuits for novelty and information seeking
Monosov, I. E. (2024) · Nature Reviews Neuroscience · doi:10.1038/s41583-023-00784-9 · Cited by 44
Goedhoop, J., Arbab, T., & Willuhn, I. (2023) · The Journal of Neuroscience · doi:10.1523/jneurosci.1527-22.2023 · Cited by 24
Mesolimbic dopamine release precedes actively sought aversive stimuli in mice
Yawata, Y., Shikano, Y., Ogasawara, J., Makino, K., Kashima, T., Ihara, K., Yoshimoto, A., Morikawa, S., Yagishita, S., Tanaka, K. F., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-38130-3 · Cited by 24
Whitton, A. E., Lewandowski, K. E., & Hall, M.-H. (2021) · Brain Sciences · doi:10.3390/brainsci11121581 · Cited by 4
Tsuruga, R., Tajika, Y., Minami, M., & Tsutsui-Kimura, I. (2026) · Communications Biology · doi:10.1038/s42003-026-10485-5 · Cited by 2
Metadata
- Authors
- Menegas, W., Babayan, B. M., Uchida, N., & Watabe-Uchida, M.
- Venue
- eLife
- Publisher
- eLife Sciences Publications, Ltd
- Published
- 2017-01-05
- Volume
- 6
- ISSN
- 2050-084X (ISSN-L)
- OpenAlex
- W2571008383
- Cited by
- 265
- References
- 26
- FWCI
- 11.74
- Type
- journal article
- Language
- en
- Open access
- gold
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
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.