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Neuroscience
Japan
2026
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Engineering and Technology
Japan
2025

D-Index & Metrics

Neuroscience

D-Index
108
Citations
51879
World Ranking
575
National Ranking
5

Mitsuo Kawato publication distribution in Neuroscience in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Neuroscience in 2026. The highlighted bar marks where Mitsuo Kawato sits on this spectrum.

38–47 publications: 18 scientists 48–57 publications: 79 scientists 58–67 publications: 193 scientists 68–77 publications: 323 scientists 78–87 publications: 406 scientists 88–97 publications: 452 scientists 98–107 publications: 539 scientists 108–117 publications: 505 scientists 118–127 publications: 522 scientists 128–137 publications: 469 scientists 138–147 publications: 456 scientists 148–157 publications: 459 scientists 158–167 publications: 397 scientists 168–177 publications: 383 scientists 178–187 publications: 350 scientists 188–197 publications: 302 scientists 198–207 publications: 306 scientists 208–217 publications: 262 scientists 218–227 publications: 242 scientists 228–237 publications: 220 scientists 238–247 publications: 203 scientists 248–257 publications: 174 scientists 258–267 publications: 176 scientists 268–277 publications: 175 scientists 278–287 publications: 125 scientists 288–297 publications: 116 scientists 298–307 publications: 127 scientists 308–317 publications: 128 scientists 318–327 publications: 99 scientists 328–337 publications: 89 scientists 338–347 publications: 78 scientists 348–357 publications: 96 scientists 358–367 publications: 66 scientists 368–377 publications: 59 scientists 378–387 publications: 65 scientists 388–397 publications: 54 scientists 398–407 publications: 48 scientists 408–417 publications: 49 scientists 418–427 publications: 34 scientists 428–437 publications: 31 scientists 438–447 publications: 30 scientists 448–457 publications: 31 scientists 458–467 publications: 36 scientists 468–477 publications: 40 scientists 478–487 publications: 35 scientists 488–497 publications: 30 scientists 498–507 publications: 23 scientists 508–517 publications: 26 scientists 518–527 publications: 20 scientists 528–537 publications: 23 scientists 538–547 publications: 20 scientists 548–557 publications: 20 scientists 558–567 publications: 17 scientists 568–577 publications: 14 scientists 578–587 publications: 20 scientists 588–597 publications: 20 scientists 598–607 publications: 19 scientists 608–617 publications: 18 scientists 618–627 publications: 17 scientists 628–637 publications: 11 scientists 638–647 publications: 11 scientists 648–657 publications: 11 scientists 658–667 publications: 8 scientists 668–677 publications: 7 scientists 678–687 publications: 11 scientists 688–697 publications: 10 scientists 698–707 publications: 4 scientists 708–717 publications: 6 scientists 718–727 publications: 5 scientists 728–737 publications: 5 scientists 738–747 publications: 9 scientists 748–757 publications: 9 scientists 758–767 publications: 3 scientists 768–777 publications: 7 scientists 778–787 publications: 7 scientists 788–797 publications: 6 scientists 798–807 publications: 2 scientists 808–817 publications: 2 scientists 818–827 publications: 7 scientists 828–837 publications: 0 scientists 838–847 publications: 9 scientists 848–857 publications: 3 scientists 858–867 publications: 1 scientists 868–877 publications: 3 scientists 878–886 publications: 6 scientists 887+ publications: 100 scientists
38 publications 887+

This scientist: 511 publications — 95th percentile

95% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 887 publications or more.

Mitsuo Kawato D-index placement in Neuroscience in 2026

The chart shows the D-index (discipline H-index) distribution of Neuroscience scientists ranked by Research.com in 2026. The highlighted bar marks where Mitsuo Kawato sits on this spectrum.

30–31 D-Index: 42 scientists 32–33 D-Index: 172 scientists 34–35 D-Index: 296 scientists 36–37 D-Index: 435 scientists 38–39 D-Index: 459 scientists 40–41 D-Index: 456 scientists 42–43 D-Index: 467 scientists 44–45 D-Index: 478 scientists 46–47 D-Index: 512 scientists 48–49 D-Index: 435 scientists 50–51 D-Index: 425 scientists 52–53 D-Index: 418 scientists 54–55 D-Index: 392 scientists 56–57 D-Index: 357 scientists 58–59 D-Index: 334 scientists 60–61 D-Index: 328 scientists 62–63 D-Index: 260 scientists 64–65 D-Index: 278 scientists 66–67 D-Index: 239 scientists 68–69 D-Index: 250 scientists 70–71 D-Index: 210 scientists 72–73 D-Index: 200 scientists 74–75 D-Index: 189 scientists 76–77 D-Index: 170 scientists 78–79 D-Index: 146 scientists 80–81 D-Index: 113 scientists 82–83 D-Index: 126 scientists 84–85 D-Index: 100 scientists 86–87 D-Index: 84 scientists 88–89 D-Index: 99 scientists 90–91 D-Index: 84 scientists 92–93 D-Index: 85 scientists 94–95 D-Index: 72 scientists 96–97 D-Index: 76 scientists 98–99 D-Index: 45 scientists 100–101 D-Index: 49 scientists 102–103 D-Index: 43 scientists 104–105 D-Index: 32 scientists 106–107 D-Index: 45 scientists 108–109 D-Index: 50 scientists 110–111 D-Index: 32 scientists 112–113 D-Index: 39 scientists 114–115 D-Index: 32 scientists 116–117 D-Index: 29 scientists 118–119 D-Index: 27 scientists 120–121 D-Index: 19 scientists 122–123 D-Index: 23 scientists 124–125 D-Index: 27 scientists 126–127 D-Index: 16 scientists 128–129 D-Index: 24 scientists 130–131 D-Index: 13 scientists 132–133 D-Index: 21 scientists 134–135 D-Index: 17 scientists 136–137 D-Index: 14 scientists 138–139 D-Index: 15 scientists 140–141 D-Index: 10 scientists 142–143 D-Index: 10 scientists 144–145 D-Index: 13 scientists 146–147 D-Index: 9 scientists 148–149 D-Index: 8 scientists 150–151 D-Index: 6 scientists 152–153 D-Index: 6 scientists 154–155 D-Index: 7 scientists 156–157 D-Index: 7 scientists 158–159 D-Index: 10 scientists 160–161 D-Index: 4 scientists 162 D-Index: 8 scientists 163+ D-Index: 100 scientists
30 D-Index 163+

This scientist: 108 D-Index — 94th percentile

94% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 163 D-Index or more.

Research.com Recognitions

  • 2026 - Research.com Neuroscience in Japan Leader Award
  • 2025 - Research.com Engineering and Technology in Japan Leader Award
  • 2025 - Research.com Neuroscience in Japan Leader Award
  • 2023 - Research.com Engineering and Technology in Japan Leader Award
  • 2023 - Research.com Neuroscience in Japan Leader Award
  • 2022 - Research.com Engineering and Technology in Japan Leader Award
  • 2022 - Research.com Neuroscience in Japan Leader Award

Overview

Mitsuo Kawato is affiliated with the Advanced Telecommunications Research Institute International in Japan. Their research focuses primarily on neuroscience, with significant contributions to subfields such as cognitive neuroscience, experimental and cognitive psychology, radiology, nuclear medicine and imaging, clinical psychology, and neurology.

Their work encompasses various topics, including:

  • Functional Brain Connectivity Studies
  • Neural dynamics and brain function
  • Neural and Behavioral Psychology Studies
  • Mental Health Research Topics
  • EEG and Brain-Computer Interfaces
  • Advanced Neuroimaging Techniques and Applications
  • Vestibular and auditory disorders

Mitsuo Kawato has coauthored extensively with several researchers, including:

  • Yasumasa Okamoto (24 publications)
  • Ayumu Yamashita (22 publications)
  • Go Okada (22 publications)
  • Hidehiko Takahashi (22 publications)
  • Aurelio Cortese (21 publications)

Their research has been published repeatedly in venues such as:

  • bioRxiv (Cold Spring Harbor Laboratory) - 24 publications
  • Scientific Reports - 8 publications
  • Psychiatry and Clinical Neurosciences - 6 publications
  • arXiv (Cornell University) - 5 publications
  • Molecular Psychiatry - 4 publications

Some of their notable recent papers include:

  • A multi-site, multi-disorder resting-state magnetic resonance image database (2021, Scientific Data)
  • Prevalence and risk factors of internet gaming disorder and problematic internet use before and during the COVID-19 pandemic: A large online survey of Japanese adults (2021, Journal of Psychiatric Research)
  • Generalizable brain network markers of major depressive disorder across multiple imaging sites (2020, PLoS Biology)
  • Primary functional brain connections associated with melancholic major depressive disorder and modulation by antidepressants (2020, Scientific Reports)
  • Brain/MINDS beyond human brain MRI project: A protocol for multi-level harmonization across brain disorders throughout the lifespan (2021, NeuroImage Clinical)

Best Publications

  • Internal models for motor control and trajectory planning

    Mitsuo Kawato

  • Internal models in the cerebellum

    Daniel M Wolpert;R.Chris Miall;Mitsuo Kawato

  • Multiple paired forward and inverse models for motor control

    D. M. Wolpert;M. Kawato

  • Formation and control of optimal trajectory in human multijoint arm movement

    Y. Uno;M. Kawato;R. Suzuki

  • A hierarchical neural-network model for control and learning of voluntary movement

    M. Kawato;Kazunori Furukawa;R. Suzuki

  • A unifying computational framework for motor control and social interaction

    Daniel M. Wolpert;Kenji Doya;Mitsuo Kawato

  • The central nervous system stabilizes unstable dynamics by learning optimal impedance.

    Etienne Burdet;Rieko Osu;David W. Franklin;Theodore E. Milner

  • Human cerebellar activity reflecting an acquired internal model of a new tool

    Hiroshi Imamizu;Satoru Miyauchi;Tomoe Tamada;Yuka Sasaki

  • MOSAIC Model for Sensorimotor Learning and Control

    Masahiko Haruno;Daniel M. Wolpert;Mitsuo M. Kawato

  • A computational model of four regions of the cerebellum based on feedback-error learning.

    Mitsuo Kawato;Hiroaki Gomi

  • Feedback-error-learning neural network for trajectory control of a robotic manipulator

    Hiroyuki Miyamoto;Mitsuo Kawato;Tohru Setoyama;Ryoji Suzuki

  • Equilibrium-Point Control Hypothesis Examined by Measured Arm Stiffness During Multijoint Movement

    Hiroaki Gomi;Mitsuo Kawato

  • Multiple model-based reinforcement learning

    Kenji Doya;Kazuyuki Samejima;Ken-ichi Katagiri;Mitsuo Kawato

  • Hierarchical neural network model for voluntary movement with application to robotics

    M. Kawato;Y. Uno;M. Isobe;R. Suzuki

  • Perceptual Learning Incepted by Decoded fMRI Neurofeedback Without Stimulus Presentation

    Kazuhisa Shibata;Takeo Watanabe;Yuka Sasaki;Mitsuo Kawato

  • Learning from demonstration and adaptation of biped locomotion

    Jun Nakanishi;Jun Morimoto;Gen Endo;Gordon Cheng

  • Adaptation to Stable and Unstable Dynamics Achieved By Combined Impedance Control and Inverse Dynamics Model

    David W. Franklin;Rieko Osu;Etienne Burdet;Mitsuo Kawato

  • Human arm stiffness and equilibrium-point trajectory during multi-joint movement

    Hiroaki Gomi;Mitsuo Kawato

  • Different neural correlates of reward expectation and reward expectation error in the putamen and caudate nucleus during stimulus-action-reward association learning.

    Masahiko Haruno;Mitsuo Kawato

  • Feedback-Error-Learning Neural Network for Supervised Motor Learning

    Mitsuo Kawato

Frequent Co-Authors

Hiroshi Imamizu
Hiroshi Imamizu University of Tokyo
Takeo Watanabe
Takeo Watanabe Brown University
Etienne Burdet
Etienne Burdet Imperial College London
Jun Morimoto
Jun Morimoto Advanced Telecommunications Research Institute International
Kenji Doya
Kenji Doya Okinawa Institute of Science and Technology
Yuka Sasaki
Yuka Sasaki Brown University
Noriaki Yahata
Noriaki Yahata National Institutes for Quantum and Radiological Science and Technology
Nicolas Schweighofer
Nicolas Schweighofer University of Southern California
Tadashi Isa
Tadashi Isa Kyoto University
Daniel M. Wolpert
Daniel M. Wolpert Columbia University

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