Sou Nobukawa

1.3k total citations
95 papers, 875 citations indexed

About

Sou Nobukawa is a scholar working on Cognitive Neuroscience, Statistical and Nonlinear Physics and Electrical and Electronic Engineering. According to data from OpenAlex, Sou Nobukawa has authored 95 papers receiving a total of 875 indexed citations (citations by other indexed papers that have themselves been cited), including 76 papers in Cognitive Neuroscience, 41 papers in Statistical and Nonlinear Physics and 20 papers in Electrical and Electronic Engineering. Recurrent topics in Sou Nobukawa's work include Neural dynamics and brain function (68 papers), stochastic dynamics and bifurcation (40 papers) and Functional Brain Connectivity Studies (25 papers). Sou Nobukawa is often cited by papers focused on Neural dynamics and brain function (68 papers), stochastic dynamics and bifurcation (40 papers) and Functional Brain Connectivity Studies (25 papers). Sou Nobukawa collaborates with scholars based in Japan, India and Indonesia. Sou Nobukawa's co-authors include H. Nishimura, Teruya Yamanishi, Tetsuya Takahashi, Mitsuru Kikuchi, Nobuhiko Wagatsuma, Jian‐Qin Liu, Yuji Wada, Keiichiro Inagaki, Takashi Ikeda and Chiaki Hasegawa and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and NeuroImage.

In The Last Decade

Sou Nobukawa

81 papers receiving 862 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sou Nobukawa Japan 17 670 377 187 123 92 95 875
Dongchuan Yu China 16 499 0.7× 341 0.9× 306 1.6× 53 0.4× 73 0.8× 54 981
Teruya Yamanishi Japan 14 379 0.6× 253 0.7× 121 0.6× 73 0.6× 61 0.7× 42 513
Vadim Grubov Russia 20 850 1.3× 124 0.3× 133 0.7× 74 0.6× 156 1.7× 96 1.1k
Oren Shriki Israel 18 1.0k 1.5× 249 0.7× 72 0.4× 126 1.0× 242 2.6× 46 1.2k
Anastasiya E. Runnova Russia 17 751 1.1× 172 0.5× 133 0.7× 74 0.6× 97 1.1× 99 975
Daniel Chicharro Italy 17 596 0.9× 138 0.4× 67 0.4× 62 0.5× 246 2.7× 23 823
Kristin K. Jerger United States 7 583 0.9× 513 1.4× 351 1.9× 34 0.3× 183 2.0× 12 1.1k
Tobias Wagner Germany 13 610 0.9× 81 0.2× 102 0.5× 61 0.5× 166 1.8× 18 809
Adrián Ponce‐Alvarez Spain 21 1.7k 2.6× 176 0.5× 121 0.6× 88 0.7× 375 4.1× 37 1.9k
Spase Petkoski France 17 666 1.0× 127 0.3× 240 1.3× 20 0.2× 89 1.0× 32 862

Countries citing papers authored by Sou Nobukawa

Since Specialization
Citations

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

Fields of papers citing papers by Sou Nobukawa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sou Nobukawa

This figure shows the co-authorship network connecting the top 25 collaborators of Sou Nobukawa. A scholar is included among the top collaborators of Sou Nobukawa 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 Sou Nobukawa. Sou Nobukawa 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.
Kurnianingsih, Kurnianingsih, et al.. (2025). A novel ensemble XGBoost and deep Q-network for pregnancy risk prediction on multi-class imbalanced datasets. ICT Express. 11(4). 648–656.
2.
3.
Nobukawa, Sou, et al.. (2025). Neural activity responsiveness by maturation of inhibition underlying critical period plasticity. Frontiers in Neural Circuits. 18. 1519704–1519704.
4.
Wagatsuma, Nobuhiko, et al.. (2024). Assessment of the effect of attentional control and experience on event-related potential P300 in visual perception during vehicle driving. Transportation Research Part F Traffic Psychology and Behaviour. 103. 574–585. 2 indexed citations
5.
Nobukawa, Sou, et al.. (2024). Controlling Chaotic Resonance with Extremely Local-Specific Feedback Signals. IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences. E107.A(8). 1106–1114.
6.
Nobukawa, Sou, Takashi Ikeda, Mitsuru Kikuchi, & Tetsuya Takahashi. (2024). Atypical instantaneous spatio-temporal patterns of neural dynamics in Alzheimer’s disease. Scientific Reports. 14(1). 88–88. 1 indexed citations
7.
8.
Nobukawa, Sou, et al.. (2024). Emergence of chaotic resonance controlled by extremely weak feedback signals in neural systems. Frontiers in Applied Mathematics and Statistics. 10.
9.
Adachi, Masataka, Sou Nobukawa, & Keiichiro Inagaki. (2024). Assessment of driver fatigue-related brain responses and causal factors during driving under different traffic conditions. Frontiers in Applied Mathematics and Statistics. 10.
10.
Nishimura, H., et al.. (2023). Dynamic Pattern Recognition Model Based on Neural Network Response to Signal Fluctuation. Journal of Advanced Computational Intelligence and Intelligent Informatics. 27(1). 44–53. 1 indexed citations
11.
Nobukawa, Sou, et al.. (2023). Assessment of functional connectivity induced by driving experience. Nonlinear Theory and Its Applications IEICE. 14(2). 559–568. 1 indexed citations
12.
Nobukawa, Sou, et al.. (2023). Extremely Weak Feedback Method for Controlling Chaotic Resonance. 1727–1732. 2 indexed citations
13.
Nobukawa, Sou, et al.. (2021). Functional Connectivity Estimated using the Phase Lag Index and Transfer Entropy. Society of Instrument and Control Engineers of Japan. 1082–1087. 2 indexed citations
14.
Nobukawa, Sou, Tetsuya Takahashi, Toshinobu Takeda, et al.. (2021). Pupillometric Complexity and Symmetricity Follow Inverted-U Curves Against Baseline Diameter Due to Crossed Locus Coeruleus Projections to the Edinger-Westphal Nucleus. Frontiers in Physiology. 12. 614479–614479. 7 indexed citations
15.
Nobukawa, Sou, et al.. (2020). Synchronization of Chaos-Chaos Intermittency Controlled by External Feedback and Stochastic Noise. Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications. 2020(0). 17–22. 6 indexed citations
16.
Nobukawa, Sou, H. Nishimura, & Teruya Yamanishi. (2019). Pattern Classification by Spiking Neural Networks Combining Self-Organized and Reward-Related Spike-Timing-Dependent Plasticity. Journal of Artificial Intelligence and Soft Computing Research. 9(4). 283–291. 9 indexed citations
17.
Nobukawa, Sou, Mitsuru Kikuchi, & Tetsuya Takahashi. (2018). Changes in functional connectivity dynamics with aging: A dynamical phase synchronization approach. NeuroImage. 188. 357–368. 45 indexed citations
18.
Nobukawa, Sou & H. Nishimura. (2013). Characteristic of signal response in coupled inferior olive neurons with Velarde-Llinás model. Society of Instrument and Control Engineers of Japan. 1367–1374. 5 indexed citations
19.
Nobukawa, Sou & H. Nishimura. (2012). Synchronous spike propagation in Izhikevich neuron system with spike-timing dependent plasticity. Society of Instrument and Control Engineers of Japan. 453–458. 4 indexed citations
20.
Nobukawa, Sou, H. Nishimura, Teruya Yamanishi, & Jian‐Qin Liu. (2011). Signal response efficiency in Izhikevich neuron model. Society of Instrument and Control Engineers of Japan. 1242–1247. 3 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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