Jayeeta Basu

2.1k total citations
22 papers, 1.3k citations indexed

About

Jayeeta Basu is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience and Molecular Biology. According to data from OpenAlex, Jayeeta Basu has authored 22 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Cellular and Molecular Neuroscience, 12 papers in Cognitive Neuroscience and 9 papers in Molecular Biology. Recurrent topics in Jayeeta Basu's work include Neuroscience and Neuropharmacology Research (14 papers), Memory and Neural Mechanisms (11 papers) and Neural dynamics and brain function (6 papers). Jayeeta Basu is often cited by papers focused on Neuroscience and Neuropharmacology Research (14 papers), Memory and Neural Mechanisms (11 papers) and Neural dynamics and brain function (6 papers). Jayeeta Basu collaborates with scholars based in United States, Germany and United Kingdom. Jayeeta Basu's co-authors include Steven A. Siegelbaum, Christian Rosenmund, Stephanie Cheung, Nils Brose, Andrea Betz, Thomas C. Südhof, Oliver M. Schlüter, Roland Zemla, Boris V. Zemelman and Frederick L. Hitti and has published in prestigious journals such as Science, Cell and Nature Communications.

In The Last Decade

Jayeeta Basu

21 papers receiving 1.3k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Jayeeta Basu United States	13	822	619	455	402	110	22	1.3k
Sung Eun Kwon United States	11	628 0.8×	498 0.8×	383 0.8×	351 0.9×	68 0.6×	17	1.1k
Albrecht Sigler Germany	13	1.0k 1.2×	930 1.5×	674 1.5×	253 0.6×	134 1.2×	14	1.7k
Noriaki Ohkawa Japan	16	544 0.7×	357 0.6×	156 0.3×	390 1.0×	137 1.2×	34	1.1k
Joost H. Heeroma Netherlands	11	1.1k 1.4×	913 1.5×	680 1.5×	423 1.1×	140 1.3×	15	1.8k
Björn Granseth Sweden	13	589 0.7×	641 1.0×	477 1.0×	181 0.5×	80 0.7×	22	1.1k
Mio Nonaka Japan	17	878 1.1×	698 1.1×	189 0.4×	351 0.9×	112 1.0×	23	1.3k
Diasynou Fioravante United States	19	674 0.8×	473 0.8×	195 0.4×	294 0.7×	147 1.3×	24	1.1k
Skyler L. Jackman United States	14	849 1.0×	625 1.0×	292 0.6×	321 0.8×	91 0.8×	17	1.2k
Erika S. Piedras-Renterı́a United States	18	1.3k 1.5×	1.2k 2.0×	327 0.7×	164 0.4×	92 0.8×	32	1.8k
Austin R. Graves United States	11	464 0.6×	322 0.5×	142 0.3×	383 1.0×	105 1.0×	18	1.0k

Countries citing papers authored by Jayeeta Basu

Since Specialization

Citations

This map shows the geographic impact of Jayeeta Basu'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 Jayeeta Basu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jayeeta Basu more than expected).

Fields of papers citing papers by Jayeeta Basu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jayeeta Basu. 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 Jayeeta Basu. The network helps show where Jayeeta Basu may publish in the future.

Co-authorship network of co-authors of Jayeeta Basu

This figure shows the co-authorship network connecting the top 25 collaborators of Jayeeta Basu. A scholar is included among the top collaborators of Jayeeta Basu 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 Jayeeta Basu. Jayeeta Basu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Moore, Jason J., et al.. (2025). Sub-cellular population imaging tools reveal stable apical dendrites in hippocampal area CA3. Nature Communications. 16(1). 1119–1119. 2 indexed citations

Elmaleh, Margot, et al.. (2025). Hippocampus shapes entorhinal cortical output through a direct feedback circuit. Nature Neuroscience. 28(4). 811–822. 1 indexed citations

Robert, Vincent, et al.. (2025). Cortical glutamatergic and GABAergic inputs support learning-driven hippocampal stability. Science. 390(6778). eadn0623–eadn0623.

Levenstein, Daniel, et al.. (2025). Topography of putative bi-directional interaction between hippocampal sharp-wave ripples and neocortical slow oscillations. Neuron. 113(5). 754–768.e9. 3 indexed citations

Basu, Jayeeta & Katherine I. Nagel. (2024). Neural circuits for goal-directed navigation across species. Trends in Neurosciences. 47(11). 904–917. 9 indexed citations

Konishi, Colin T., Qinkun Zhang, Qiaoyan Yang, et al.. (2024). Modeling and correction of protein conformational disease in iPSC-derived neurons through personalized base editing. Molecular Therapy — Nucleic Acids. 36(1). 102441–102441. 2 indexed citations

Chavlis, Spyridon, et al.. (2023). Lateral entorhinal cortex inputs modulate hippocampal dendritic excitability by recruiting a local disinhibitory microcircuit. Cell Reports. 42(1). 111962–111962. 18 indexed citations

Zemla, Roland, et al.. (2022). Task-selective place cells show behaviorally driven dynamics during learning and stability during memory recall. Cell Reports. 41(8). 111700–111700. 12 indexed citations

Moore, Jason J., et al.. (2021). Assessing Local and Branch-specific Activity in Dendrites. Neuroscience. 489. 143–164. 7 indexed citations

10.

Magnus, Christopher, Peter H. Lee, Jordi Bonaventura, et al.. (2019). Ultrapotent chemogenetics for research and potential clinical applications. Science. 364(6436). 112 indexed citations

11.

Camacho, Marcial, Jayeeta Basu, Thorsten Trimbuch, et al.. (2017). Heterodimerization of Munc13 C2A domain with RIM regulates synaptic vesicle docking and priming. Nature Communications. 8(1). 15293–15293. 70 indexed citations

12.

Zemla, Roland & Jayeeta Basu. (2017). Hippocampal function in rodents. Current Opinion in Neurobiology. 43. 187–197. 42 indexed citations

13.

Basu, Jayeeta & C. RoyChaudhuri. (2016). Graphene Nanogrids FET Immunosensor: Signal to Noise Ratio Enhancement. Sensors. 16(10). 1481–1481. 18 indexed citations

14.

Basu, Jayeeta & Steven A. Siegelbaum. (2015). The Corticohippocampal Circuit, Synaptic Plasticity, and Memory. Cold Spring Harbor Perspectives in Biology. 7(11). a021733–a021733. 150 indexed citations

15.

Basu, Jayeeta, et al.. (2014). Reelin Signaling Specifies the Molecular Identity of the Pyramidal Neuron Distal Dendritic Compartment. Cell. 158(6). 1335–1347. 51 indexed citations

16.

Basu, Jayeeta, Kalyan V. Srinivas, Stephanie Cheung, et al.. (2013). A Cortico-Hippocampal Learning Rule Shapes Inhibitory Microcircuit Activity to Enhance Hippocampal Information Flow. Neuron. 79(6). 1208–1221. 87 indexed citations

17.

Basu, Jayeeta, Andrea Betz, Nils Brose, & Christian Rosenmund. (2007). Munc13-1 C1 Domain Activation Lowers the Energy Barrier for Synaptic Vesicle Fusion. Journal of Neuroscience. 27(5). 1200–1210. 153 indexed citations

18.

Schlüter, Oliver M., Jayeeta Basu, Thomas C. Südhof, & Christian Rosenmund. (2006). Rab3 Superprimes Synaptic Vesicles for Release: Implications for Short-Term Synaptic Plasticity. Journal of Neuroscience. 26(4). 1239–1246. 147 indexed citations

19.

Basu, Jayeeta, Frédérique Varoqueaux, Kerstin Reim, et al.. (2006). Molecular Dynamics of a Presynaptic Active Zone Protein Studied in Munc13-1–Enhanced Yellow Fluorescent Protein Knock-In Mutant Mice. Journal of Neuroscience. 26(50). 13054–13066. 63 indexed citations

20.

Basu, Jayeeta, Nan Shen, Irina Dulubova, et al.. (2005). A minimal domain responsible for Munc13 activity. Nature Structural & Molecular Biology. 12(11). 1017–1018. 154 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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