Marina Garrett

3.4k total citations
13 papers, 931 citations indexed

About

Marina Garrett is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Molecular Biology. According to data from OpenAlex, Marina Garrett has authored 13 papers receiving a total of 931 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Cognitive Neuroscience, 8 papers in Cellular and Molecular Neuroscience and 6 papers in Molecular Biology. Recurrent topics in Marina Garrett's work include Neural dynamics and brain function (12 papers), Visual perception and processing mechanisms (5 papers) and Neuroscience and Neuropharmacology Research (5 papers). Marina Garrett is often cited by papers focused on Neural dynamics and brain function (12 papers), Visual perception and processing mechanisms (5 papers) and Neuroscience and Neuropharmacology Research (5 papers). Marina Garrett collaborates with scholars based in United States. Marina Garrett's co-authors include Edward M. Callaway, Ian Nauhaus, James H. Marshel, Jun Zhuang, Shawn R. Olsen, Yang Li, Derric Williams, Jack Waters, Lydia Ng and Matthew T. Valley and has published in prestigious journals such as Neuron, Journal of Neuroscience and PLoS ONE.

In The Last Decade

Marina Garrett

13 papers receiving 927 citations

Peers

Marina Garrett
Farran Briggs United States
Charu Bai Reddy United Kingdom
Henry Lütcke Switzerland
Aslı Ayaz United Kingdom
Tsukasa Kamigaki United States
Anita A. Disney United States
Jennifer M. Ichida United States
Marina Garrett
Citations per year, relative to Marina Garrett Marina Garrett (= 1×) peers Tatsuo K. Sato

Countries citing papers authored by Marina Garrett

Since Specialization
Citations

This map shows the geographic impact of Marina Garrett's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Marina Garrett with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marina Garrett more than expected).

Fields of papers citing papers by Marina Garrett

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marina Garrett. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Marina Garrett. The network helps show where Marina Garrett may publish in the future.

Co-authorship network of co-authors of Marina Garrett

This figure shows the co-authorship network connecting the top 25 collaborators of Marina Garrett. A scholar is included among the top collaborators of Marina Garrett based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Marina Garrett. Marina Garrett is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

13 of 13 papers shown
1.
Ito, Shinya, Alex T. Piet, Corbett Bennett, et al.. (2024). Coordinated changes in a cortical circuit sculpt effects of novelty on neural dynamics. Cell Reports. 43(9). 114763–114763. 2 indexed citations
2.
Piet, Alex T., Douglas R. Ollerenshaw, Marina Garrett, et al.. (2024). Behavioral strategy shapes activation of the Vip-Sst disinhibitory circuit in visual cortex. Neuron. 112(11). 1876–1890.e4. 6 indexed citations
3.
Campagnola, Luke, et al.. (2024). Simple synaptic modulations implement diverse novelty computations. Cell Reports. 43(5). 114188–114188. 3 indexed citations
4.
Garrett, Marina, et al.. (2022). The geometry of representational drift in natural and artificial neural networks. PLoS Computational Biology. 18(11). e1010716–e1010716. 12 indexed citations
5.
Hu, Brian, Marina Garrett, Peter A. Groblewski, et al.. (2021). Adaptation supports short-term memory in a visual change detection task. PLoS Computational Biology. 17(9). e1009246–e1009246. 12 indexed citations
6.
Groblewski, Peter A., Douglas R. Ollerenshaw, Justin Kiggins, et al.. (2020). Characterization of Learning, Motivation, and Visual Perception in Five Transgenic Mouse Lines Expressing GCaMP in Distinct Cell Populations. Frontiers in Behavioral Neuroscience. 14. 104–104. 9 indexed citations
7.
Garrett, Marina, Sahar Manavi, Kate Roll, et al.. (2020). Experience shapes activity dynamics and stimulus coding of VIP inhibitory cells. eLife. 9. 56 indexed citations
8.
Waters, Jack, Eric Lee, Nathalie Gaudreault, et al.. (2019). Biological variation in the sizes, shapes and locations of visual cortical areas in the mouse. PLoS ONE. 14(5). e0213924–e0213924. 13 indexed citations
9.
Bennett, Corbett, Samuel D. Gale, Marina Garrett, et al.. (2019). Higher-Order Thalamic Circuits Channel Parallel Streams of Visual Information in Mice. Neuron. 102(2). 477–492.e5. 107 indexed citations
10.
Zhuang, Jun, Lydia Ng, Derric Williams, et al.. (2017). An extended retinotopic map of mouse cortex. eLife. 6. 141 indexed citations
11.
Juavinett, Ashley, Ian Nauhaus, Marina Garrett, Jun Zhuang, & Edward M. Callaway. (2016). Automated identification of mouse visual areas with intrinsic signal imaging. Nature Protocols. 12(1). 32–43. 59 indexed citations
12.
Garrett, Marina, Ian Nauhaus, James H. Marshel, & Edward M. Callaway. (2014). Topography and Areal Organization of Mouse Visual Cortex. Journal of Neuroscience. 34(37). 12587–12600. 199 indexed citations
13.
Marshel, James H., Marina Garrett, Ian Nauhaus, & Edward M. Callaway. (2011). Functional Specialization of Seven Mouse Visual Cortical Areas. Neuron. 72(6). 1040–1054. 312 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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