Lucas C. Parra
- Cognitive Neuroscience top 0.1%
- Neurology top 0.05%
- Cellular and Molecular Neuroscience top 0.5%
- Signal Processing top 0.2%
- Biomedical Engineering top 1%
- Co-authors
- Marom BiksonPaul SajdaClay D. SpenceAbhishek DattaYu HuangJacek DmochowskiAsif RahmanDavide Reato
- Topics
- Neural dynamics and brain function (66 papers)EEG and Brain-Computer Interfaces (52 papers)Transcranial Magnetic Stimulation Studies (50 papers)
- Journals
- Proceedings of the National Academy of SciencesNature CommunicationsJournal of Neuroscience
- Partner nations
- United StatesGermanyFrance
In The Last Decade
Lucas C. Parra
193 papers receiving 11.8k citations
Hit Papers
Peers
Comparison fields: 5 of 174
- Cognitive Neuroscience 7.1k
- Neurology 4.1k
- Cellular and Molecular Neuroscience 2.4k
- Signal Processing 2.0k
- Biomedical Engineering 1.7k
Countries citing papers authored by Lucas C. Parra
This map shows the geographic impact of Lucas C. Parra'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 Lucas C. Parra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lucas C. Parra more than expected).
Fields of papers citing papers by Lucas C. Parra
This network shows the impact of papers produced by Lucas C. Parra. 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 Lucas C. Parra. The network helps show where Lucas C. Parra may publish in the future.
Co-authorship network of co-authors of Lucas C. Parra
This figure shows the co-authorship network connecting the top 25 collaborators of Lucas C. Parra. A scholar is included among the top collaborators of Lucas C. Parra 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 Lucas C. Parra. Lucas C. Parra is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 3 | |
| 5 | 6 | |
| 6 | 0 | |
| 7 | 4 | |
| 8 | 20 | |
| 9 | 19 | |
| 10 | 31 | |
| 11 | 1 | |
| 12 | 9 | |
| 13 | 58 | |
| 14 | 25 | |
| 15 | 68 | |
| 16 | 47 | |
| 17 | 50 | |
| 18 | 16 | |
| 19 | 83 | |
| 20 | A Context-Sensitive Generalization of ICA | 101 |
About Lucas C. Parra
Lucas C. Parra is a scholar working on Neurology, Cognitive Neuroscience and Signal Processing, having authored 202 papers that have together received 12.2k indexed citations. Recurring topics across this work include Neural dynamics and brain function (66 papers), EEG and Brain-Computer Interfaces (52 papers) and Transcranial Magnetic Stimulation Studies (50 papers). The work is most often cited by research in Neurology (4.1k citations), Cognitive Neuroscience (7.1k citations) and Signal Processing (2.0k citations). Lucas C. Parra has collaborated with scholars based in United States, Germany and France. Frequent co-authors include Marom Bikson, Paul Sajda, Clay D. Spence, Abhishek Datta, Yu Huang, Jacek Dmochowski, Asif Rahman, Davide Reato, Adam D. Gerson and Harrison H. Barrett. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications and Journal of Neuroscience.
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.