Satoshi Tsujimoto

2.7k total citations
84 papers, 1.7k citations indexed

About

Satoshi Tsujimoto is a scholar working on Cognitive Neuroscience, Statistical and Nonlinear Physics and Geometry and Topology. According to data from OpenAlex, Satoshi Tsujimoto has authored 84 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Cognitive Neuroscience, 29 papers in Statistical and Nonlinear Physics and 13 papers in Geometry and Topology. Recurrent topics in Satoshi Tsujimoto's work include Nonlinear Waves and Solitons (27 papers), Neural dynamics and brain function (26 papers) and Neural and Behavioral Psychology Studies (22 papers). Satoshi Tsujimoto is often cited by papers focused on Nonlinear Waves and Solitons (27 papers), Neural dynamics and brain function (26 papers) and Neural and Behavioral Psychology Studies (22 papers). Satoshi Tsujimoto collaborates with scholars based in Japan, Italy and United States. Satoshi Tsujimoto's co-authors include Aldo Genovesio, Steven P. Wise, Ryogo Hirota, Toshiyuki Sawaguchi, Alexei Zhedanov, Luc Vinet, Yasuhiro Ohta, Hiroshi Miki, C. R. Gilson and Encarni Marcos and has published in prestigious journals such as Nature Communications, Neuron and Journal of Neuroscience.

In The Last Decade

Satoshi Tsujimoto

74 papers receiving 1.7k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Satoshi Tsujimoto Japan 23 1.0k 455 227 130 128 84 1.7k
James Vickers United Kingdom 19 338 0.3× 238 0.5× 136 0.6× 52 0.4× 20 0.2× 61 1.5k
В. А. Пономарев Russia 20 1.2k 1.1× 125 0.3× 415 1.8× 13 0.1× 11 0.1× 107 1.8k
Jennifer J. Quinn United States 24 1.8k 1.7× 165 0.4× 88 0.4× 38 0.3× 10 0.1× 69 3.0k
Arthur S. Schwartz United States 14 359 0.4× 418 0.9× 89 0.4× 340 2.6× 5 0.0× 31 2.5k
Masafumi Oizumi Japan 12 776 0.8× 136 0.3× 10 0.0× 55 0.4× 12 0.1× 42 1.1k
Daniel Matthes Germany 18 187 0.2× 235 0.5× 36 0.2× 60 0.5× 22 0.2× 55 1.1k
Erik Hendriksen Netherlands 23 102 0.1× 182 0.4× 99 0.4× 115 0.9× 12 0.1× 85 1.7k
Anders Ledberg Sweden 17 2.1k 2.0× 122 0.3× 16 0.1× 13 0.1× 23 0.2× 39 2.6k
Philippe Ciuciu France 26 1.4k 1.3× 43 0.1× 7 0.0× 75 0.6× 164 1.3× 120 2.3k
Xavier Gigandet Switzerland 9 3.9k 3.8× 248 0.5× 26 0.1× 27 0.2× 10 0.1× 20 4.6k

Countries citing papers authored by Satoshi Tsujimoto

Since Specialization
Citations

This map shows the geographic impact of Satoshi Tsujimoto'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 Satoshi Tsujimoto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Satoshi Tsujimoto more than expected).

Fields of papers citing papers by Satoshi Tsujimoto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Satoshi Tsujimoto. 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 Satoshi Tsujimoto. The network helps show where Satoshi Tsujimoto may publish in the future.

Co-authorship network of co-authors of Satoshi Tsujimoto

This figure shows the co-authorship network connecting the top 25 collaborators of Satoshi Tsujimoto. A scholar is included among the top collaborators of Satoshi Tsujimoto 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 Satoshi Tsujimoto. Satoshi Tsujimoto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Tsujimoto, Satoshi, et al.. (2025). Cell types implement multiple coding schemes in distinct prefrontal cortex areas during goal-directed behavior. Progress in Neurobiology. 251. 102803–102803.
2.
Takahashi, Daisuke, et al.. (2025). Neighborhood-five cellular automaton model for pedestrian flow. Japan Journal of Industrial and Applied Mathematics. 42(5). 2197–2212.
3.
Tsujimoto, Satoshi, et al.. (2024). Recurrence Relations of Exceptional Laurent Biorthogonal Polynomials. Constructive Approximation. 62(3). 613–644.
4.
Fascianelli, V., et al.. (2024). Neural representational geometries reflect behavioral differences in monkeys and recurrent neural networks. Nature Communications. 15(1). 6479–6479. 11 indexed citations
5.
Tsujimoto, Satoshi, et al.. (2024). Generalization of the $$\epsilon $$-BBS and the Schensted insertion algorithm. Journal of Algebraic Combinatorics. 60(2). 407–433.
6.
Croydon, David A., et al.. (2022). Bi-infinite Solutions for KdV- and Toda-Type Discrete Integrable Systems Based on Path Encodings. Mathematical Physics Analysis and Geometry. 25(4). 2 indexed citations
7.
Tsujimoto, Satoshi, Luc Vinet, & Alexei Zhedanov. (2020). An algebraic description of the bispectrality of the biorthogonal rational functions of Hahn type. Proceedings of the American Mathematical Society. 149(2). 715–728. 6 indexed citations
8.
Miki, Hiroshi, Satoshi Tsujimoto, & Luc Vinet. (2020). Perfect state transfer in two dimensions and the bivariate dual-Hahn polynomials. arXiv (Cornell University). 1 indexed citations
9.
Hosoda, Chihiro, et al.. (2020). Plastic frontal pole cortex structure related to individual persistence for goal achievement. Communications Biology. 3(1). 194–194. 17 indexed citations
10.
Fascianelli, V., et al.. (2020). Neural Correlates of Strategy Switching in the Macaque Orbital Prefrontal Cortex. Journal of Neuroscience. 40(15). 3025–3034. 5 indexed citations
11.
Tsujimoto, Satoshi, et al.. (2018). Exceptional Bannai–Ito polynomials. Journal of Approximation Theory. 239. 144–173. 2 indexed citations
12.
Genovesio, Aldo, et al.. (2014). Autonomous Encoding of Irrelevant Goals and Outcomes by Prefrontal Cortex Neurons. Journal of Neuroscience. 34(5). 1970–1978. 39 indexed citations
13.
Tsujimoto, Satoshi, Aldo Genovesio, & Steven P. Wise. (2012). Neuronal Activity during a Cued Strategy Task: Comparison of Dorsolateral, Orbital, and Polar Prefrontal Cortex. Journal of Neuroscience. 32(32). 11017–11031. 46 indexed citations
14.
Tsujimoto, Satoshi, Aldo Genovesio, & Steven P. Wise. (2009). Monkey Orbitofrontal Cortex Encodes Response Choices Near Feedback Time. Journal of Neuroscience. 29(8). 2569–2574. 74 indexed citations
15.
Genovesio, Aldo, Satoshi Tsujimoto, & Steven P. Wise. (2008). Encoding problem‐solving strategies in prefrontal cortex: activity during strategic errors. European Journal of Neuroscience. 27(4). 984–990. 29 indexed citations
16.
Tsujimoto, Satoshi & Toshiyuki Sawaguchi. (2007). Prediction of relative and absolute time of reward in monkey prefrontal neurons. Neuroreport. 18(7). 703–707. 6 indexed citations
17.
Tsujimoto, Satoshi & Toshiyuki Sawaguchi. (2005). Neuronal Activity Representing Temporal Prediction of Reward in the Primate Prefrontal Cortex. Journal of Neurophysiology. 93(6). 3687–3692. 54 indexed citations
18.
Tsujimoto, Satoshi & Toshiyuki Sawaguchi. (2004). Properties of delay‐period neuronal activity in the primate prefrontal cortex during memory‐ and sensory‐guided saccade tasks. European Journal of Neuroscience. 19(2). 447–457. 25 indexed citations
19.
Tsujimoto, Satoshi. (2002). On a Discrete Analogue of the Two-Dimensional Toda Lattice Hierarchy. Publications of the Research Institute for Mathematical Sciences. 38(1). 113–133. 6 indexed citations
20.
Gilson, C. R., et al.. (2001). Pfaffianization of the discrete KP equation. Journal of Physics A Mathematical and General. 34(48). 10569–10575. 47 indexed citations

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.

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