Natsue Yoshimura

1.8k total citations
98 papers, 1.3k citations indexed

About

Natsue Yoshimura is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Biomedical Engineering. According to data from OpenAlex, Natsue Yoshimura has authored 98 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 69 papers in Cognitive Neuroscience, 22 papers in Cellular and Molecular Neuroscience and 22 papers in Biomedical Engineering. Recurrent topics in Natsue Yoshimura's work include EEG and Brain-Computer Interfaces (51 papers), Neural dynamics and brain function (21 papers) and Muscle activation and electromyography studies (20 papers). Natsue Yoshimura is often cited by papers focused on EEG and Brain-Computer Interfaces (51 papers), Neural dynamics and brain function (21 papers) and Muscle activation and electromyography studies (20 papers). Natsue Yoshimura collaborates with scholars based in Japan, United States and Italy. Natsue Yoshimura's co-authors include Yasuharu Koike, Hiroyuki Kambara, Ludovico Minati, Duk Shin, Hitoshi Okazawa, Mattia Frasca, Kazuhiko Tagawa, Chao Chen, Abdelkader Nasreddine Belkacem and Hyeonseok Kim and has published in prestigious journals such as Physical Review Letters, Journal of Neuroscience and SHILAP Revista de lepidopterología.

In The Last Decade

Natsue Yoshimura

90 papers receiving 1.3k citations

Peers

Natsue Yoshimura

CMN

Chung Tin Hong Kong

Fábio R. Torres Brazil

Kost Elisevich United States

Amir Homayoun Jafari‬ Iran

Shiro Usui Japan

Joseph T. Francis United States

Christopher M. Harris United Kingdom

Angelo Arleo France

Brian Murphy United States

Gunnar Blohm Canada

Chung Tin Hong Kong

Natsue Yoshimura

589 ×0.8

181 ×0.4

CMN

533 ×1.7

288 ×1.2

93 ×0.6

Citations per year, relative to Natsue Yoshimura Natsue Yoshimura (= 1×) peers Chung Tin

Countries citing papers authored by Natsue Yoshimura

Since Specialization

Citations

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

Fields of papers citing papers by Natsue Yoshimura

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Natsue Yoshimura

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

All Works

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20 of 20 papers shown

Njitacke, Zeric Tabekoueng, Théophile Fonzin Fozin, Jan Awrejcewicz, et al.. (2025). Chaotic dynamics, topological analysis and flat analog electronic control by physiological signals of a neurally-inspired system. Chinese Journal of Physics. 96. 20–52. 2 indexed citations

Hashimoto, Ryuichiro, et al.. (2025). Electroencephalography-guided transcranial direct current stimulation improves picture-naming performance. NeuroImage. 308. 120997–120997. 3 indexed citations

Wang, Shan, et al.. (2024). Comparison of autism spectrum disorder subtypes based on functional and structural factors. Frontiers in Neuroscience. 18. 1440222–1440222. 3 indexed citations

Njitacke, Zeric Tabekoueng, Théophile Fonzin Fozin, Hilaire Bertrand Fotsin, et al.. (2024). A van der Pol-like complementary chaotic oscillator: Design, physical realizations, dynamics, and physiological data augmentation prospect. Chaos Solitons & Fractals. 191. 115886–115886. 3 indexed citations

Okaze, Tsubasa, et al.. (2024). Classification of pleasantness of wind by electroencephalography. PLoS ONE. 19(2). e0299036–e0299036.

Minati, Ludovico, et al.. (2023). Accelerometer time series augmentation through externally driving a non-linear dynamical system. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations

Minati, Ludovico, et al.. (2023). Accelerometer time series augmentation through externally driving a non-linear dynamical system. Chaos Solitons & Fractals. 168. 113100–113100. 12 indexed citations

Ozawa, Yusuke & Natsue Yoshimura. (2023). Temporal Electroencephalography Traits Dissociating Tactile Information and Cross-Modal Congruence Effects. Sensors. 24(1). 45–45.

Kambara, Hiroyuki, et al.. (2021). Investigating Neural Representation of Finger-Movement Directions Using Electroencephalography Independent Components. Journal of Biomedical Science and Engineering. 14(6). 240–265. 1 indexed citations

10.

Kambara, Hiroyuki, Atsushi Takagi, Toshihiro Kawase, et al.. (2021). Computational reproductions of external force field adaption without assuming desired trajectories. Neural Networks. 139. 179–198. 3 indexed citations

11.

Koike, Yasuharu, et al.. (2020). Generation of diverse insect-like gait patterns using networks of coupled Rössler systems. Chaos An Interdisciplinary Journal of Nonlinear Science. 30(12). 123132–123132. 7 indexed citations

12.

Ogata, Yousuke, et al.. (2020). Comparison of resting-state functional and effective connectivity between default mode network and memory encoding related areas. 4(1). 29–37. 2 indexed citations

13.

Piovesan, Davide, et al.. (2020). Towards a Simplified Estimation of Muscle Activation Pattern from MRI and EMG Using Electrical Network and Graph Theory. Sensors. 20(3). 724–724. 7 indexed citations

14.

Takagi, Atsushi, et al.. (2019). Finger Angle Estimation From Array EMG System Using Linear Regression Model With Independent Component Analysis. Frontiers in Neurorobotics. 13. 75–75. 22 indexed citations

15.

Ganesh, Gowrishankar, Keigo Nakamura, Eiichi Yoshida, et al.. (2018). Utilizing sensory prediction errors for movement intention decoding: A new methodology. Science Advances. 4(5). eaaq0183–eaaq0183. 12 indexed citations

16.

Yoshimura, Natsue, et al.. (2017). Decoding finger movement in humans using synergy of EEG cortical current signals. Scientific Reports. 7(1). 11382–11382. 27 indexed citations

17.

Shiwaku, Hiroki, Natsue Yoshimura, Takuya Tamura, et al.. (2010). Suppression of the novel ER protein Maxer by mutant ataxin‐1 in Bergman glia contributes to non‐cell‐autonomous toxicity. The EMBO Journal. 29(14). 2446–2460. 63 indexed citations

18.

Ito, Hikaru, Natsue Yoshimura, Masaru Kurosawa, et al.. (2009). Knock-down of PQBP1 impairs anxiety-related cognition in mouse. Human Molecular Genetics. 18(22). 4239–4254. 24 indexed citations

19.

Wada, Yoichi, et al.. (2005). PQBP‐1 is expressed predominantly in the central nervous system during development. European Journal of Neuroscience. 22(6). 1277–1286. 29 indexed citations

20.

Otsuki, Mika, Yoshiaki Soma, K. Aoki, et al.. (1998). [Functional difference between the left supplementary motor area and the left premotor area in a task of confrontation naming and word fluency].. PubMed. 50(3). 243–8. 2 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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