Isao T. Tokuda

3.2k total citations
155 papers, 2.2k citations indexed

About

Isao T. Tokuda is a scholar working on Artificial Intelligence, Biomedical Engineering and Cognitive Neuroscience. According to data from OpenAlex, Isao T. Tokuda has authored 155 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Artificial Intelligence, 30 papers in Biomedical Engineering and 27 papers in Cognitive Neuroscience. Recurrent topics in Isao T. Tokuda's work include Nonlinear Dynamics and Pattern Formation (26 papers), Robotic Locomotion and Control (26 papers) and Circadian rhythm and melatonin (24 papers). Isao T. Tokuda is often cited by papers focused on Nonlinear Dynamics and Pattern Formation (26 papers), Robotic Locomotion and Control (26 papers) and Circadian rhythm and melatonin (24 papers). Isao T. Tokuda collaborates with scholars based in Japan, United States and Germany. Isao T. Tokuda's co-authors include Hanspeter Herzel, Kazuyuki Aihara, Tobias Riede, Fumihiko Asano, Wataru Nakamura, Hirokazu Fukuda, Hiroshi Gotoda, Michael J. Owren, Jan G. Švec and István Z. Kiss and has published in prestigious journals such as Science, Physical Review Letters and Journal of Biological Chemistry.

In The Last Decade

Isao T. Tokuda

146 papers receiving 2.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Isao T. Tokuda Japan 25 461 429 419 341 326 155 2.2k
George Moore United States 28 450 1.0× 205 0.5× 717 1.7× 3.2k 9.5× 47 0.1× 98 5.3k
Ben Fulcher Australia 33 151 0.3× 143 0.3× 230 0.5× 2.6k 7.6× 83 0.3× 67 4.1k
Sen Song China 32 119 0.3× 155 0.4× 1.2k 2.9× 3.9k 11.3× 33 0.1× 87 8.4k
George L. Gerstein United States 40 89 0.2× 239 0.6× 945 2.3× 7.2k 21.1× 122 0.4× 86 8.5k
Thomas M. McKenna United States 26 231 0.5× 108 0.3× 129 0.3× 1.1k 3.3× 28 0.1× 78 2.5k
W. Otto Friesen United States 37 146 0.3× 556 1.3× 106 0.3× 1.1k 3.1× 64 0.2× 86 3.8k
Uri T. Eden United States 36 73 0.2× 95 0.2× 314 0.7× 3.7k 10.8× 25 0.1× 131 4.9k
Donald H. Perkel United States 25 101 0.2× 224 0.5× 615 1.5× 3.9k 11.4× 44 0.1× 41 5.4k
Vasilis Z. Marmarelis United States 33 91 0.2× 90 0.2× 474 1.1× 2.4k 7.2× 17 0.1× 183 4.7k
Yoko Yamaguchi Japan 33 157 0.3× 96 0.2× 231 0.6× 2.0k 5.8× 8 0.0× 192 4.3k

Countries citing papers authored by Isao T. Tokuda

Since Specialization
Citations

This map shows the geographic impact of Isao T. Tokuda'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 Isao T. Tokuda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Isao T. Tokuda more than expected).

Fields of papers citing papers by Isao T. Tokuda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Isao T. Tokuda. 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 Isao T. Tokuda. The network helps show where Isao T. Tokuda may publish in the future.

Co-authorship network of co-authors of Isao T. Tokuda

This figure shows the co-authorship network connecting the top 25 collaborators of Isao T. Tokuda. A scholar is included among the top collaborators of Isao T. Tokuda 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 Isao T. Tokuda. Isao T. Tokuda 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.
2.
Herbst, Christian T., Isao T. Tokuda, Takeshi Nishimura, et al.. (2025). ‘Monkey yodels’—frequency jumps in New World monkey vocalizations greatly surpass human vocal register transitions. Philosophical Transactions of the Royal Society B Biological Sciences. 380(1923). 20240005–20240005. 8 indexed citations
3.
Inoue, T., et al.. (2024). Nonlinear dynamics and chaos in a vocal-ventricular fold system. Chaos An Interdisciplinary Journal of Nonlinear Science. 34(2). 6 indexed citations
4.
5.
Yoshinaga, Tsukasa, et al.. (2023). Effects of vocal fold oscillation characteristics on the aerosol droplet production. Journal of Aerosol Science. 174. 106251–106251. 2 indexed citations
6.
Chang, Chun‐Wei, Vasilis Dakos, Egbert H. van Nes, et al.. (2023). Anticipating the occurrence and type of critical transitions. Science Advances. 9(1). eabq4558–eabq4558. 30 indexed citations
7.
Miyachi, Shigehiro, et al.. (2023). Ventricular fold oscillations lower the vocal pitch in rhesus macaques. Journal of Experimental Biology. 226(12). 1 indexed citations
8.
Nakagawa, Takumi, et al.. (2022). Experimental Study on Inspiratory Phonation Using Physical Model of the Vocal Folds. Journal of Voice. 38(4). 826–835. 4 indexed citations
9.
Hayasaka, Naoto, Arisa Hirano, Isao T. Tokuda, et al.. (2021). Correction: Salt-inducible kinase 3 regulates the mammalian circadian clock by destabilizing PER2 protein. eLife. 10. 1 indexed citations
10.
Schmal, Christoph, Daisuke Ono, Jihwan Myung, et al.. (2019). Weak coupling between intracellular feedback loops explains dissociation of clock gene dynamics. PLoS Computational Biology. 15(9). e1007330–e1007330. 14 indexed citations
11.
Okada, Masahiro, Tokihiko Kaburagi, & Isao T. Tokuda. (2019). Acoustic measurements of the infinitesimal phase response curve from a sounding organ pipe. Physics Letters A. 383(15). 1733–1741.
12.
Gould, Peter, Mirela Domijan, Mark Greenwood, et al.. (2018). Coordination of robust single cell rhythms in the Arabidopsis circadian clock via spatial waves of gene expression. eLife. 7. 78 indexed citations
13.
Teramae, Jun-nosuke, et al.. (2018). Highly Heterogeneous Excitatory Connections Require Less Amount of Noise to Sustain Firing Activities in Cortical Networks. Frontiers in Computational Neuroscience. 12. 104–104. 2 indexed citations
14.
Gotoda, Hiroshi, et al.. (2017). Nonlinear dynamics of a buoyancy-induced turbulent fire. Physical review. E. 96(5). 52223–52223. 23 indexed citations
15.
Asano, Fumihiko, et al.. (2017). Experimental Verification of Underactuated Locomotion Robot Utilizing Effects of Sliding and Wobbling. The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec). 2017(0). 2P2–H04.
16.
Hayasaka, Naoto, Arisa Hirano, Isao T. Tokuda, et al.. (2017). Salt-inducible kinase 3 regulates the mammalian circadian clock by destabilizing PER2 protein. eLife. 6. 27 indexed citations
17.
Tanaka, Daiki, Fumihiko Asano, & Isao T. Tokuda. (2013). Gait Analysis and Efficiency Improvement of Combined Rimless Wheel with Wobbling Mass. Transactions of the Society of Instrument and Control Engineers. 49(9). 865–874. 1 indexed citations
18.
Tokuda, Isao T.. (1998). Approximation Capability of Neural Networks with Time-Delayed Feedbacks. Natural Computing. 97(532). 1–5. 1 indexed citations
19.
Miyazaki, Jun, et al.. (1997). Dynamical Associative Memory based on Synchronization in Chaotic Neural Network : Proposal for the Scenario via Spatio-Temporal Symmetry Recovering Bifurcation. Natural Computing. 96(511). 95–100. 1 indexed citations
20.
Tokuda, Isao T., et al.. (1996). A SIMPLE GEOMETRICAL STRUCTURE UNDERLYING SPEECH SIGNALS OF THE JAPANESE VOWEL /a/. International Journal of Bifurcation and Chaos. 6(1). 149–160. 22 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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