David Dahmen
Impact in
- Cognitive Neuroscience top 10%
- Neural dynamics and brain function
- Functional Brain Connectivity Studies
- EEG and Brain-Computer Interfaces
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- stochastic dynamics and bifurcation
Papers in
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- Neural dynamics and brain function 19
- Functional Brain Connectivity Studies 4
- EEG and Brain-Computer Interfaces 3
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- Neural Networks and Applications 5
- Neural Networks and Reservoir Computing 4
- Co-authors
- Moritz Helias (14 shared papers)Markus Diesmann (5 shared papers)Sonja Grün (6 shared papers)Tom Tetzlaff (4 shared papers)Henrik Lindén (3 shared papers)Sacha J. van Albada (2 shared papers)Gaute T. Einevoll (3 shared papers)Maria Stavrinou (2 shared papers)
In The Last Decade
David Dahmen
18 papers receiving 260 citations
Peers
Comparison fields: 5 of 52
- Cognitive Neuroscience 213
- Statistical and Nonlinear Physics 68
- Cellular and Molecular Neuroscience 80
- Computational Mathematics 1
- Artificial Intelligence 49
Countries citing papers authored by David Dahmen
This map shows the geographic impact of David Dahmen'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 David Dahmen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Dahmen more than expected).
Fields of papers citing papers by David Dahmen
This network shows the impact of papers produced by David Dahmen. 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 David Dahmen. The network helps show where David Dahmen may publish in the future.
Co-authors
The 25 scholars most cited alongside David Dahmen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 73 | |
| 2 | 2016 | 58 | |
| 3 | 2021 | 18 | |
| 4 | 2021 | 17 | |
| 5 | 2016 | 16 | |
| 6 | 2022 | 14 | |
| 7 | 2022 | 12 | |
| 8 | 2021 | 11 | |
| 9 | 2020 | 10 | |
| 10 | 2020 | 8 | |
| 11 | 2015 | 7 | |
| 12 | 2024 | 4 | |
| 13 | 2023 | 4 | |
| 14 | Developing the electronics industry : a World Bank symposium | 1993 | 3 |
| 15 | 2015 | 3 | |
| 16 | 2025 | 2 | |
| 17 | 2014 | 2 | |
| 18 | 2020 | 1 | |
| 19 | 2025 | 0 | |
| 20 | 2023 | 0 |
About David Dahmen
David Dahmen is a scholar working on Cognitive Neuroscience, Artificial Intelligence, Statistical and Nonlinear Physics, Cellular and Molecular Neuroscience and Electrical and Electronic Engineering, having authored 23 papers that have together received 263 indexed citations. Recurring topics across this work include Neural dynamics and brain function (19 papers), Neural Networks and Applications (5 papers), Advanced Memory and Neural Computing (4 papers), Neural Networks and Reservoir Computing (4 papers), Functional Brain Connectivity Studies (4 papers), stochastic dynamics and bifurcation (4 papers), Neuroscience and Neural Engineering (3 papers) and EEG and Brain-Computer Interfaces (3 papers). The work is most often cited by research in Cognitive Neuroscience (213 citations), Statistical and Nonlinear Physics (68 citations), Cellular and Molecular Neuroscience (80 citations), Computational Mathematics (1 citation) and Artificial Intelligence (49 citations). David Dahmen has collaborated with scholars based in Germany, France and Norway. Frequent co-authors include Moritz Helias, Markus Diesmann, Sonja Grün, Tom Tetzlaff, Henrik Lindén, Sacha J. van Albada, Gaute T. Einevoll, Maria Stavrinou, Espen Hagen and Thomas Luu. Their work appears in journals such as Physical Review X, PLoS Computational Biology, eLife, Lecture notes in physics and BMC 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.