A Genetic Toolkit for Dissecting Dopamine Circuit Function in Drosophila
Cell Reports, ISSN: 2211-1247, Vol: 23, Issue: 2, Page: 652-665
2018
- 51Citations
- 219Captures
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations51
- Citation Indexes51
- 51
- CrossRef32
- Captures219
- Readers219
- 219
Article Description
The neuromodulator dopamine (DA) plays a key role in motor control, motivated behaviors, and higher-order cognitive processes. Dissecting how these DA neural networks tune the activity of local neural circuits to regulate behavior requires tools for manipulating small groups of DA neurons. To address this need, we assembled a genetic toolkit that allows for an exquisite level of control over the DA neural network in Drosophila. To further refine targeting of specific DA neurons, we also created reagents that allow for the conversion of any existing GAL4 line into Split GAL4 or GAL80 lines. We demonstrated how this toolkit can be used with recently developed computational methods to rapidly generate additional reagents for manipulating small subsets or individual DA neurons. Finally, we used the toolkit to reveal a dynamic interaction between a small subset of DA neurons and rearing conditions in a social space behavioral assay.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S2211124718304297; http://dx.doi.org/10.1016/j.celrep.2018.03.068; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85044758892&origin=inward; http://www.ncbi.nlm.nih.gov/pubmed/29642019; https://linkinghub.elsevier.com/retrieve/pii/S2211124718304297; https://dx.doi.org/10.1016/j.celrep.2018.03.068
Elsevier BV
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