J. Michael Herrmann
Impact in
- Cognitive Neuroscience top 2%
- Neural dynamics and brain function
- Functional Brain Connectivity Studies
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- stochastic dynamics and bifurcation
Papers in
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- Neural dynamics and brain function 32
- Memory and Neural Mechanisms 5
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- Neural Networks and Applications 14
- Evolutionary Algorithms and Applications 7
- Reinforcement Learning in Robotics 6
- Co-authors
- T. GeiselAnna LevinaT. A. JoyceUdo ErnstGbenga IbikunleChristian W. EurichSilke DodelJoachim Haß
- Journals
- Neurocomputing (9 papers)BMC Neuroscience (4 papers)Theory in Biosciences (2 papers)Neural Computation (2 papers)Journal of Computational Neuroscience (2 papers)
- Partner nations
- United KingdomGermanyChina
In The Last Decade
J. Michael Herrmann
65 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 117
- Cognitive Neuroscience 735
- Statistical and Nonlinear Physics 325
- Cellular and Molecular Neuroscience 151
- Artificial Intelligence 248
- Computer Networks and Communications 119
Countries citing papers authored by J. Michael Herrmann
This map shows the geographic impact of J. Michael Herrmann'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 J. Michael Herrmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites J. Michael Herrmann more than expected).
Fields of papers citing papers by J. Michael Herrmann
This network shows the impact of papers produced by J. Michael Herrmann. 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 J. Michael Herrmann. The network helps show where J. Michael Herrmann may publish in the future.
Co-authors
The 25 scholars most cited alongside J. Michael Herrmann, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 12 | |
| 2 | 2023 | 2 | |
| 3 | 2019 | 6 | |
| 4 | 2018 | 81 | |
| 5 | 2016 | 5 | |
| 6 | 2015 | 4 | |
| 7 | 2013 | 0 | |
| 8 | 2012 | 11 | |
| 9 | 2012 | 10 | |
| 10 | 2011 | 8 | |
| 11 | 2011 | 14 | |
| 12 | 2010 | 25 | |
| 13 | 2010 | 9 | |
| 14 | 2009 | 99 | |
| 15 | 2005 | 2 | |
| 16 | 2002 | 77 | |
| 17 | 2000 | 3 | |
| 18 | 1999 | 9 | |
| 19 | Magnification control in neural maps. | 1998 | 8 |
| 20 | Measuring topology preservation in maps of real-world data. | 1997 | 6 |
About J. Michael Herrmann
J. Michael Herrmann is a scholar working on Cognitive Neuroscience, Artificial Intelligence, Statistical and Nonlinear Physics, Human-Computer Interaction and Signal Processing, having authored 68 papers that have together received 1.2k indexed citations. Recurring topics across this work include Neural dynamics and brain function (32 papers), Neural Networks and Applications (14 papers), Evolutionary Algorithms and Applications (7 papers), stochastic dynamics and bifurcation (7 papers), Advanced Memory and Neural Computing (6 papers), Reinforcement Learning in Robotics (6 papers), Nonlinear Dynamics and Pattern Formation (5 papers) and Memory and Neural Mechanisms (5 papers). The work is most often cited by research in Cognitive Neuroscience (735 citations), Statistical and Nonlinear Physics (325 citations), Cellular and Molecular Neuroscience (151 citations), Artificial Intelligence (248 citations) and Computer Networks and Communications (119 citations). J. Michael Herrmann has collaborated with scholars based in United Kingdom, Germany and China. Frequent co-authors include T. Geisel, Anna Levina, T. A. Joyce, Udo Ernst, Gbenga Ibikunle, Christian W. Eurich, Silke Dodel, Joachim Haß, Jörg Behrendt and Marcus Hasselhorn. Their work appears in journals such as Neurocomputing, BMC Neuroscience, Theory in Biosciences, Neural Computation and Journal of Computational 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.