Gen Matsumoto
- Molecular Biology top 5%
- Cellular and Molecular Neuroscience top 1%
- Cognitive Neuroscience top 2%
- Epidemiology top 5%
- Cell Biology top 1%
- Co-authors
- Nobuyuki NukinaMasaru KurosawaMichinori IchikawaMisako OkunoKazuyuki AiharaRichard I. MorimotoKoji WadaNobutaka Hattori
- Topics
- Photoreceptor and optogenetics research (36 papers)Neural dynamics and brain function (29 papers)Neuroscience and Neuropharmacology Research (25 papers)
- Partner nations
- JapanPolandUnited States
In The Last Decade
Gen Matsumoto
157 papers receiving 5.5k citations
Hit Papers
Peers
Comparison fields: 5 of 165
- Molecular Biology 2.5k
- Cellular and Molecular Neuroscience 1.5k
- Cognitive Neuroscience 956
- Epidemiology 907
- Cell Biology 851
Countries citing papers authored by Gen Matsumoto
This map shows the geographic impact of Gen Matsumoto'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 Gen Matsumoto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gen Matsumoto more than expected).
Fields of papers citing papers by Gen Matsumoto
This network shows the impact of papers produced by Gen Matsumoto. 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 Gen Matsumoto. The network helps show where Gen Matsumoto may publish in the future.
Co-authorship network of co-authors of Gen Matsumoto
This figure shows the co-authorship network connecting the top 25 collaborators of Gen Matsumoto. A scholar is included among the top collaborators of Gen Matsumoto 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 Gen Matsumoto. Gen Matsumoto 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 | 0 | |
| 3 | 2 | |
| 4 | 2 | |
| 5 | 80 | |
| 6 | 7 | |
| 7 | 75 | |
| 8 | 0 | |
| 9 | 8 | |
| 10 | 34 | |
| 11 | The Brain and Brainway Computer. | 1 |
| 12 | 8 | |
| 13 | 88 | |
| 14 | Top-down Selforganization of Semantic Constraints for Knowledge Representation in Autonomous Systems:A Model on The Role of an Emotional System in Brains | 0 |
| 15 | 3 | |
| 16 | A New Learning Rule for Temporal Sequence | 6 |
| 17 | The Brain as a computer | 3 |
| 18 | 2 | |
| 19 | 8 | |
| 20 | High molecular weight proteins of nerve cells inducing cross-linking or bundling of cytoskeletal proteins | 2 |
About Gen Matsumoto
Gen Matsumoto is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience and Cell Biology, having authored 163 papers that have together received 5.7k indexed citations. Recurring topics across this work include Photoreceptor and optogenetics research (36 papers), Neural dynamics and brain function (29 papers) and Neuroscience and Neuropharmacology Research (25 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (1.5k citations), Cell Biology (851 citations) and Aging (89 citations). Gen Matsumoto has collaborated with scholars based in Japan, Poland and United States. Frequent co-authors include Nobuyuki Nukina, Masaru Kurosawa, Michinori Ichikawa, Misako Okuno, Kazuyuki Aihara, Richard I. Morimoto, Koji Wada, Nobutaka Hattori, Yoshiro Hanyu and Hikoichi Sakai. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.
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.