Ethan M. Meyers
- Cognitive Neuroscience top 2%
- Computer Vision and Pattern Recognition top 5%
- Experimental and Cognitive Psychology top 10%
- Cellular and Molecular Neuroscience top 10%
- Artificial Intelligence top 10%
- Co-authors
- Tomaso PoggioPawan SinhaLior WolfGabriel KreimanDavid J. FreedmanEarl K. MillerDavid CoxJoel Z. Leibo
- Topics
- Neural dynamics and brain function (12 papers)Face Recognition and Perception (7 papers)Visual perception and processing mechanisms (6 papers)
- Cited by
- Cognitive NeuroscienceComputer Vision and Pattern RecognitionExperimental and Cognitive Psychology
- Partner nations
- United StatesIndiaMexico
In The Last Decade
Ethan M. Meyers
20 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 70
- Cognitive Neuroscience 1.1k
- Computer Vision and Pattern Recognition 258
- Experimental and Cognitive Psychology 135
- Cellular and Molecular Neuroscience 126
- Artificial Intelligence 92
Countries citing papers authored by Ethan M. Meyers
This map shows the geographic impact of Ethan M. Meyers'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 Ethan M. Meyers with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ethan M. Meyers more than expected).
Fields of papers citing papers by Ethan M. Meyers
This network shows the impact of papers produced by Ethan M. Meyers. 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 Ethan M. Meyers. The network helps show where Ethan M. Meyers may publish in the future.
Co-authorship network of co-authors of Ethan M. Meyers
This figure shows the co-authorship network connecting the top 25 collaborators of Ethan M. Meyers. A scholar is included among the top collaborators of Ethan M. Meyers 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 Ethan M. Meyers. Ethan M. Meyers 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 | 26 | |
| 3 | 16 | |
| 4 | 3 | |
| 5 | 58 | |
| 6 | The neural decoding toolbox | 1 |
| 7 | 125 | |
| 8 | 174 | |
| 9 | Preliminary MEG decoding results | 2 |
| 10 | 83 | |
| 11 | 110 | |
| 12 | 14 | |
| 13 | Examining high level neural representations of cluttered scenes | 1 |
| 14 | 2 | |
| 15 | 94 | |
| 16 | 277 | |
| 17 | 104 | |
| 18 | 20 | |
| 19 | 11 | |
| 20 | 144 |
About Ethan M. Meyers
Ethan M. Meyers is a scholar working on Cognitive Neuroscience, Computer Vision and Pattern Recognition and Biophysics, having authored 20 papers that have together received 1.3k indexed citations. Recurring topics across this work include Neural dynamics and brain function (12 papers), Face Recognition and Perception (7 papers) and Visual perception and processing mechanisms (6 papers). The work is most often cited by research in Cognitive Neuroscience (1.1k citations), Computer Vision and Pattern Recognition (258 citations) and Experimental and Cognitive Psychology (135 citations). Ethan M. Meyers has collaborated with scholars based in United States, India and Mexico. Frequent co-authors include Tomaso Poggio, Pawan Sinha, Lior Wolf, Gabriel Kreiman, David J. Freedman, Earl K. Miller, David Cox, Joel Z. Leibo, Leyla Işık and Christos Constantinidis. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences 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.