David Brown
Impact in
- Cognitive Neuroscience top 5%
- Neural dynamics and brain function
-
- stochastic dynamics and bifurcation
Papers in
-
- Neural dynamics and brain function 17
-
- stochastic dynamics and bifurcation 13
- Co-authors
- Jianfeng Feng (21 shared papers)Jens Krause (4 shared papers)Jean‐Guy J. Godin (2 shared papers)F. Moos (3 shared papers)Andrew P. Davison (3 shared papers)Maria Zambon (2 shared papers)Jake Chandler (1 shared paper)William F. Hunt (1 shared paper)
- Journals
- Neurocomputing (6 papers)Journal of Animal Ecology (4 papers)Vaccine (3 papers)Eurosurveillance (3 papers)Biological Cybernetics (2 papers)
- Partner nations
- United KingdomUnited StatesFrance
In The Last Decade
David Brown
79 papers receiving 2.1k citations
Peers
Comparison fields: 5 of 154
- Cognitive Neuroscience 423
- Statistical and Nonlinear Physics 231
- Virology 83
- Endocrine and Autonomic Systems 116
- Sensory Systems 83
Countries citing papers authored by David Brown
This map shows the geographic impact of David Brown'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 Brown with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Brown more than expected).
Fields of papers citing papers by David Brown
This network shows the impact of papers produced by David Brown. 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 Brown. The network helps show where David Brown may publish in the future.
Co-authors
The 25 scholars most cited alongside David Brown, 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 84 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2000 | 178 | |
| 2 | 2013 | 144 | |
| 3 | 2010 | 133 | |
| 4 | 2001 | 117 | |
| 5 | 1982 | 107 | |
| 6 | 1996 | 81 | |
| 7 | 1990 | 75 | |
| 8 | 1999 | 69 | |
| 9 | 2009 | 64 | |
| 10 | 2003 | 63 | |
| 11 | 2000 | 61 | |
| 12 | 2009 | 57 | |
| 13 | 2018 | 56 | |
| 14 | 1998 | 55 | |
| 15 | 1996 | 53 | |
| 16 | 1997 | 50 | |
| 17 | 1999 | 44 | |
| 18 | 2000 | 42 | |
| 19 | 2008 | 41 | |
| 20 | 1993 | 41 |
About David Brown
David Brown is a scholar working on Cognitive Neuroscience, Statistical and Nonlinear Physics, Cellular and Molecular Neuroscience, Ecology and Infectious Diseases, having authored 84 papers that have together received 2.2k indexed citations. Recurring topics across this work include Neural dynamics and brain function (17 papers), stochastic dynamics and bifurcation (13 papers), Nonlinear Dynamics and Pattern Formation (6 papers), Neural Networks and Applications (6 papers), Neuroscience and Neuropharmacology Research (5 papers), Neurobiology and Insect Physiology Research (4 papers), Fish Ecology and Management Studies (4 papers) and Olfactory and Sensory Function Studies (4 papers). The work is most often cited by research in Cognitive Neuroscience (423 citations), Statistical and Nonlinear Physics (231 citations), Virology (83 citations), Endocrine and Autonomic Systems (116 citations) and Sensory Systems (83 citations). David Brown has collaborated with scholars based in United Kingdom, United States and France. Frequent co-authors include Jianfeng Feng, Jens Krause, Jean‐Guy J. Godin, F. Moos, Andrew P. Davison, Maria Zambon, Jake Chandler, William F. Hunt, Ryan J. Winston and Andrew M. Forman. Their work appears in journals such as Neurocomputing, Journal of Animal Ecology, Vaccine, Eurosurveillance and Biological Cybernetics.
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.