Richard Gast
- Cognitive Neuroscience top 10%
- Cellular and Molecular Neuroscience
- Computer Networks and Communications
- Statistical and Nonlinear Physics top 10%
- Neurology
- Co-authors
- Thomas R. KnöschePeter KönigGordon PipaHelmut SchmidtAnn KennedySara A. SollaVadim V. NikulinChristopher Fricke
- Topics
- Neural dynamics and brain function (7 papers)Nonlinear Dynamics and Pattern Formation (5 papers)Functional Brain Connectivity Studies (3 papers)
- Journals
- Proceedings of the National Academy of SciencesPhysical Review LettersJournal of Neuroscience
- Partner nations
- GermanyUnited StatesNetherlands
In The Last Decade
Richard Gast
13 papers receiving 237 citations
Peers
Comparison fields: 5 of 60
- Cognitive Neuroscience 161
- Cellular and Molecular Neuroscience 61
- Computer Networks and Communications 55
- Statistical and Nonlinear Physics 43
- Neurology 33
Countries citing papers authored by Richard Gast
This map shows the geographic impact of Richard Gast'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 Richard Gast with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Richard Gast more than expected).
Fields of papers citing papers by Richard Gast
This network shows the impact of papers produced by Richard Gast. 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 Richard Gast. The network helps show where Richard Gast may publish in the future.
Co-authorship network of co-authors of Richard Gast
This figure shows the co-authorship network connecting the top 25 collaborators of Richard Gast. A scholar is included among the top collaborators of Richard Gast 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 Richard Gast. Richard Gast is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 25 | |
| 3 | 13 | |
| 4 | 2 | |
| 5 | 11 | |
| 6 | 14 | |
| 7 | 34 | |
| 8 | 18 | |
| 9 | 45 | |
| 10 | 7 | |
| 11 | 11 | |
| 12 | PyRates: A Python framework for rate-based neural simulations | 1 |
| 13 | 58 |
About Richard Gast
Richard Gast is a scholar working on Cognitive Neuroscience, Statistical and Nonlinear Physics and Computer Networks and Communications, having authored 13 papers that have together received 241 indexed citations. Recurring topics across this work include Neural dynamics and brain function (7 papers), Nonlinear Dynamics and Pattern Formation (5 papers) and Functional Brain Connectivity Studies (3 papers). The work is most often cited by research in Cognitive Neuroscience (161 citations), Safety Research (30 citations) and Statistical and Nonlinear Physics (43 citations). Richard Gast has collaborated with scholars based in Germany, United States and Netherlands. Frequent co-authors include Thomas R. Knösche, Peter König, Gordon Pipa, Helmut Schmidt, Ann Kennedy, Sara A. Solla, Vadim V. Nikulin, Christopher Fricke, Jost‐Julian Rumpf and Joseph Claßen. Their work appears in journals such as Proceedings of the National Academy of Sciences, Physical Review Letters 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.