The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
New Rabies Virus Variants for Monitoring and Manipulating Activity and Gene Expression in Defined Neural Circuits
Open accessAbstract
SUMMARY Glycoprotein-deleted (ΔG) rabies virus is a powerful tool for studies of neural circuit structure. Here we describe the development and demonstrate the utility of new resources that allow experiments directly investigating relationships between the structure and function of neural circuits. New methods and reagents allowed efficient production of twelve novel ΔG rabies variants from plasmid DNA. These new rabies viruses express useful neuroscience tools, including: the Ca++ indicator GCaMP3, for monitoring activity; Channelrhodopsin-2, for photoactivation; allatostatin receptor, for inactivation by ligand application; rtTA, ERT2CreERT2, or FLPo, for control of gene expression. These new tools allow neurons targeted based on their connectivity, to have their function assayed or their activity or gene expression manipulated. Combining these tools with in vivo imaging and optogenetic methods, and/or inducible gene expression in transgenic mice, will facilitate experiments investigating neural circuit development, plasticity, and function that have not been possible with existing reagents.
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
A robust and high-throughput Cre reporting and characterization system for the whole mouse brain
Madisen, L., Zwingman, T. A., Sunkin, S. M., Oh, S. W., Zariwala, H. A., Gu, H., Ng, L. L., Palmiter, R. D., Hawrylycz, M. J., Jones, A. R., et al. (2010) · Nature Neuroscience · doi:10.1038/nn.2467 · Cited by 6,907
Parvalbumin neurons and gamma rhythms enhance cortical circuit performance
Sohal, V. S., Zhang, F., Yizhar, O., & Deisseroth, K. (2009) · Nature · doi:10.1038/nature07991 · Cited by 2,606
Driving fast-spiking cells induces gamma rhythm and controls sensory responses
Cardin, J. A., Carlén, M., Meletis, K., Knoblich, U., Zhang, F., Deisseroth, K., Tsai, L.-H., & Moore, C. I. (2009) · Nature · doi:10.1038/nature08002 · Cited by 2,603
Transgenic strategies for combinatorial expression of fluorescent proteins in the nervous system
Livet, J., Weissman, T. A., Kang, H., Draft, R. W., Lu, J., Bennis, R. A., Sanes, J. R., & Lichtman, J. W. (2007) · Nature · doi:10.1038/nature06293 · Cited by 1,876 · cited 2×
“For example, using a Cre-expressing rabies in Brainbow mice (Livet et al., 2007) could allow labeling of the inputs to single neurons (Marshel et al., 2010; Wickersham et al., 2007b), with the individual presynaptic cells each uniquely marked by expression of different combinations of fluorescent…”
Channelrhodopsin-2-assisted circuit mapping of long-range callosal projections
Petreanu, L., Huber, D., Sobczyk, A., & Svoboda, K. (2007) · Nature Neuroscience · doi:10.1038/nn1891 · Cited by 930
Genetic dissection of an amygdala microcircuit that gates conditioned fear
Haubensak, W., Kunwar, P. S., Cai, H., Ciocchi, S., Wall, N. R., Ponnusamy, R., Biag, J., Dong, H.-W., Deisseroth, K., Callaway, E. M., et al. (2010) · Nature · doi:10.1038/nature09553 · Cited by 840 · cited 8×
“…SADΔG-GFP rabies viruses can be used to selectively label the direct inputs to a targeted neuronal population or even a single neuron (Haubensak et al., 2010; Marshel et al., 2010; Miyamichi et al., 2011; Rancz et al., 2011; Stepien et al., 2010; Wall et al., 2010; Wickersham et…”
InfluentialSelf-citationV1 spinal neurons regulate the speed of vertebrate locomotor outputs
Gosgnach, S., Lanuza, G. M., Butt, S. J. B., Saueressig, H., Zhang, Y., Velasquez, T., Riethmacher, D., Callaway, E. M., Kiehn, O., & Goulding, M. (2006) · Nature · doi:10.1038/nature04545 · Cited by 405
Self-citationRunyan, C. A., Schummers, J., Van Wart, A., Kuhlman, S. J., Wilson, N. R., Huang, Z. J., & Sur, M. (2010) · Neuron · doi:10.1016/j.neuron.2010.08.006 · Cited by 244
Molecular genetics and imaging technologies for circuit-based neuroanatomy
Arenkiel, B. R., & Ehlers, M. D. (2009) · Nature · doi:10.1038/nature08536 · Cited by 78
Cited by
Reward and aversion in a heterogeneous midbrain dopamine system
Lammel, S., Lim, B. K., & Malenka, R. C. (2014) · Neuropharmacology · doi:10.1016/j.neuropharm.2013.03.019 · Cited by 804
Neural Networks of the Mouse Neocortex
Zingg, B., Hintiryan, H., Gou, L., Song, M. Y., Bay, M., Bienkowski, M. S., Foster, N. N., Yamashita, S., Bowman, I., Toga, A. W., et al. (2014) · Cell · doi:10.1016/j.cell.2014.02.023 · Cited by 797
A Neural Circuit for Memory Specificity and Generalization
Xu, W., & Südhof, T. C. (2013) · Science · doi:10.1126/science.1229534 · Cited by 634
High-speed recording of neural spikes in awake mice and flies with a fluorescent voltage sensor
Gong, Y., Huang, C., Li, J. Z., Grewe, B. F., Zhang, Y., Eismann, S., & Schnitzer, M. J. (2015) · Science · doi:10.1126/science.aab0810 · Cited by 462
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
Metadata
- Authors
- Osakada, F., Mori, T., Cetin, A. H., Marshel, J. H., Virgen, B., & Callaway, E. M.
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2011-08
- Volume
- 71
- Issue
- 4
- Pages
- 617-631
- ISSN
- 0896-6273 (ISSN-L)
- OpenAlex
- W2030337024
- Cited by
- 318
- References
- 9
- FWCI
- 10.84
- Type
- journal article
- Language
- en
- Open access
- bronze
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.
