Carina Curto
- Cognitive Neuroscience top 5%
- Cellular and Molecular Neuroscience top 5%
- Computational Theory and Mathematics top 5%
- Molecular Biology
- Statistical and Nonlinear Physics top 5%
- Co-authors
- Vladimir ItskovEva PastalkovaChad GiustiKenneth D. HarrisStephan Lawrence MarguetShuzo SakataGyörgy BuzsákiC. A. Kletzing
- Topics
- Neural dynamics and brain function (14 papers)Neuroscience and Neuropharmacology Research (9 papers)Memory and Neural Mechanisms (8 papers)
- Cited by
- Cognitive NeuroscienceCellular and Molecular NeuroscienceComputational Theory and Mathematics
- Journals
- Proceedings of the National Academy of SciencesJournal of NeuroscienceJournal of Geophysical Research Atmospheres
- Partner nations
- United StatesGermanyItaly
In The Last Decade
Carina Curto
27 papers receiving 820 citations
Peers
Comparison fields: 5 of 79
- Cognitive Neuroscience 501
- Cellular and Molecular Neuroscience 280
- Computational Theory and Mathematics 186
- Molecular Biology 142
- Statistical and Nonlinear Physics 116
Countries citing papers authored by Carina Curto
This map shows the geographic impact of Carina Curto'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 Carina Curto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Carina Curto more than expected).
Fields of papers citing papers by Carina Curto
This network shows the impact of papers produced by Carina Curto. 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 Carina Curto. The network helps show where Carina Curto may publish in the future.
Co-authorship network of co-authors of Carina Curto
This figure shows the co-authorship network connecting the top 25 collaborators of Carina Curto. A scholar is included among the top collaborators of Carina Curto 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 Carina Curto. Carina Curto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 4 | |
| 4 | 12 | |
| 5 | 11 | |
| 6 | 21 | |
| 7 | 25 | |
| 8 | 1 | |
| 9 | 34 | |
| 10 | 2 | |
| 11 | 105 | |
| 12 | 16 | |
| 13 | 45 | |
| 14 | 30 | |
| 15 | 117 | |
| 16 | 77 | |
| 17 | 1 | |
| 18 | 2 | |
| 19 | Matrix model superpotentials and Calabi-Yau spaces: An A-D-E classification | 3 |
| 20 | 3 |
About Carina Curto
Carina Curto is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Statistical and Nonlinear Physics, having authored 29 papers that have together received 849 indexed citations. Recurring topics across this work include Neural dynamics and brain function (14 papers), Neuroscience and Neuropharmacology Research (9 papers) and Memory and Neural Mechanisms (8 papers). The work is most often cited by research in Cognitive Neuroscience (501 citations), Cellular and Molecular Neuroscience (280 citations) and Computational Theory and Mathematics (186 citations). Carina Curto has collaborated with scholars based in United States, Germany and Italy. Frequent co-authors include Vladimir Itskov, Eva Pastalkova, Chad Giusti, Kenneth D. Harris, Stephan Lawrence Marguet, Shuzo Sakata, György Buzsáki, C. A. Kletzing, J. D. Scudder and Artur Luczak. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Neuroscience and Journal of Geophysical Research Atmospheres.
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.