The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Three Dopamine Pathways Induce Aversive Odor Memories with Different Stability
Open accessAbstract
Animals acquire predictive values of sensory stimuli through reinforcement. In the brain of Drosophila melanogaster, activation of two types of dopamine neurons in the PAM and PPL1 clusters has been shown to induce aversive odor memory. Here, we identified the third cell type and characterized aversive memories induced by these dopamine neurons. These three dopamine pathways all project to the mushroom body but terminate in the spatially segregated subdomains. To understand the functional difference of these dopamine pathways in electric shock reinforcement, we blocked each one of them during memory acquisition. We found that all three pathways partially contribute to electric shock memory. Notably, the memories mediated by these neurons differed in temporal stability. Furthermore, combinatorial activation of two of these pathways revealed significant interaction of individual memory components rather than their simple summation. These results cast light on a cellular mechanism by which a noxious event induces different dopamine signals to a single brain structure to synthesize an aversive memory.
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
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
Frost, W. N., Castellucci, V. F., Hawkins, R. D., & Kandel, E. R. (1985) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.82.23.8266 · Cited by 334
Cited by
The neuronal architecture of the mushroom body provides a logic for associative learning
Aso, Y., Hattori, D., Yu, Y., Johnston, R. M., Iyer, N. A., Ngo, T.-T., Dionne, H., Abbott, L., Axel, R., Tanimoto, H., et al. (2014) · eLife · doi:10.7554/elife.04577 · Cited by 1,051
Self-citationA Complete Electron Microscopy Volume of the Brain of Adult Drosophila melanogaster
Zheng, Z., Lauritzen, J. S., Perlman, E., Robinson, C. G., Nichols, M., Milkie, D., Torrens, O., Price, J., Fisher, C. B., Sharifi, N., et al. (2018) · Cell · doi:10.1016/j.cell.2018.06.019 · Cited by 1,050
Layered reward signalling through octopamine and dopamine in Drosophila
Burke, C. J., Huetteroth, W., Owald, D., Perisse, E., Krashes, M. J., Das, G., Gohl, D., Silies, M., Certel, S., & Waddell, S. (2012) · Nature · doi:10.1038/nature11614 · Cited by 614
Coordinated and compartmentalized neuromodulation shapes sensory processing in Drosophila
Cohn, R., Morantte, I., & Ruta, V. (2015) · Cell · doi:10.1016/j.cell.2015.11.019 · Cited by 430
Activity of Defined Mushroom Body Output Neurons Underlies Learned Olfactory Behavior in Drosophila
Owald, D., Felsenberg, J., Talbot, C. B., Das, G., Perisse, E., Huetteroth, W., & Waddell, S. (2015) · Neuron · doi:10.1016/j.neuron.2015.03.025 · Cited by 401
Heterosynaptic plasticity underlies aversive olfactory learning in Drosophila
Hige, T., Aso, Y., Modi, M. N., Rubin, G. M., & Turner, G. C. (2015) · Neuron · doi:10.1016/j.neuron.2015.11.003 · Cited by 354
A connectome of a learning and memory center in the adult Drosophila brain
Takemura, S.-Y., Aso, Y., Hige, T., Wong, A., Lu, Z., Xu, C. S., Rivlin, P. K., Hess, H., Zhao, T., Parag, T., et al. (2017) · eLife · doi:10.7554/elife.26975 · Cited by 367
Self-citationCellular diversity in the Drosophila midbrain revealed by single-cell transcriptomics
Croset, V., Treiber, C. D., & Waddell, S. (2018) · eLife · doi:10.7554/elife.34550 · Cited by 299
Tsao, C.-H., Chen, C.-C., Lin, C.-H., Yang, H.-Y., & Lin, S. (2018) · eLife · doi:10.7554/elife.35264 · Cited by 214
Memory-Relevant Mushroom Body Output Synapses Are Cholinergic
Barnstedt, O., Owald, D., Felsenberg, J., Brain, R., Moszynski, J.-P., Talbot, C. B., Perrat, P. N., & Waddell, S. (2016) · Neuron · doi:10.1016/j.neuron.2016.02.015 · Cited by 197
Direct neural pathways convey distinct visual information to Drosophila mushroom bodies
Vogt, K., Aso, Y., Hige, T., Knapek, S., Ichinose, T., Friedrich, A. B., Turner, G. C., Rubin, G. M., & Tanimoto, H. (2016) · eLife · doi:10.7554/elife.14009 · Cited by 155
Self-citationAso, Y., Ray, R. P., Long, X., Bushey, D., Cichewicz, K., Ngo, T.-T., Sharp, B., Christoforou, C., Hu, A., Lemire, A. L., et al. (2019) · eLife · doi:10.7554/elife.49257 · Cited by 141
Self-citationCan insects feel pain? A review of the neural and behavioural evidence
(2022) · Advances in Insect Physiology · doi:10.1016/bs.aiip.2022.10.001 · Cited by 121
Metamorphosis of memory circuits in Drosophila reveals a strategy for evolving a larval brain
Truman, J. W., Price, J., Miyares, R. L., & Lee, T. (2023) · eLife · doi:10.7554/elife.80594 · Cited by 74
Glia transmit negative valence information during aversive learning in Drosophila
Miyashita, T., Murakami, K., Kikuchi, E., Ofusa, K., Mikami, K., Endo, K., Miyaji, T., Moriyama, S., Konno, K., Muratani, H., et al. (2023) · Science · doi:10.1126/science.adf7429 · Cited by 26
Metadata
- Authors
- Aso, Y., Herb, A., Ogueta, M., Siwanowicz, I., Templier, T., Friedrich, A. B., Ito, K., Scholz, H., & Tanimoto, H.
- Venue
- PLoS Genetics
- Publisher
- Public Library of Science (PLoS)
- Published
- 2012-07-12
- Volume
- 8
- Issue
- 7
- Pages
- e1002768
- ISSN
- 1553-7390 (ISSN-L)
- 1553-7404
- OpenAlex
- W1978530827
- Cited by
- 308
- References
- 2
- FWCI
- 6.97
- 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.