World's Best Scientists 2026 revealed!

D-Index & Metrics

Neuroscience

D-Index
58
Citations
22844
World Ranking
4084
National Ranking
118

Kenji Doya 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 Kenji Doya 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: 275 publications — 79th percentile

79% of scientists in this discipline score the same or lower.

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

Kenji Doya 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 Kenji Doya 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: 58 D-Index — 57th percentile

57% of scientists in this discipline score the same or lower.

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

Overview

Kenji Doya is affiliated with the Okinawa Institute of Science and Technology in Japan. Their research primarily focuses on neuroscience, with a broad emphasis on cognitive neuroscience, artificial intelligence, radiology, nuclear medicine and imaging, cellular and molecular neuroscience, and experimental and cognitive psychology.

The scientist's work covers several main topics including neural dynamics and brain function, functional brain connectivity studies, advanced neuroimaging techniques and applications, EEG and brain-computer interfaces, neural and behavioral psychology studies, reinforcement learning in robotics, and mental health research topics.

Kenji Doya has published extensively, with frequent contributions to the journal Neural Networks, alongside notable appearances in bioRxiv (Cold Spring Harbor Laboratory), arXiv (Cornell University), Current Opinion in Behavioral Sciences, and Nature Communications.

Among their recent papers are:

  • "Serotonergic projections to the orbitofrontal and medial prefrontal cortices differentially modulate waiting for future rewards" (2020, Science Advances)
  • "Serotonergic modulation of cognitive computations" (2021, Current Opinion in Behavioral Sciences)
  • "Social impact and governance of AI and neurotechnologies" (2022, Neural Networks)
  • "A whole brain probabilistic generative model: Toward realizing cognitive architectures for developmental robots" (2022, Neural Networks)
  • "A biologically constrained spiking neural network model of the primate basal ganglia with overlapping pathways exhibits action selection" (2020, European Journal of Neuroscience)

Frequent collaborators in their research include Carlos Enrique Gutierrez with 10 joint works, Jun Tani (6), Ken Nakae (5), Henrik Skibbe (5), and Kenji F. Tanaka (4).

Best Publications

  • Sigmoid-weighted linear units for neural network function approximation in reinforcement learning.

    Stefan Elfwing;Eiji Uchibe;Kenji Doya

  • A unifying computational framework for motor control and social interaction

    Daniel M. Wolpert;Kenji Doya;Mitsuo Kawato

  • Reinforcement Learning in Continuous Time and Space

    Kenji Doya

  • Complementary roles of basal ganglia and cerebellum in learning and motor control.

    Kenji Doya

  • Prediction of immediate and future rewards differentially recruits cortico-basal ganglia loops

    Saori C Tanaka;Kenji Doya;Go Okada;Kazutaka Ueda

  • Representation of action-specific reward values in the striatum.

    Kazuyuki Samejima;Kazuyuki Samejima;Yasumasa Ueda;Yasumasa Ueda;Kenji Doya;Kenji Doya;Minoru Kimura;Minoru Kimura

  • What are the computations of the cerebellum, the basal ganglia and the cerebral cortex?

    K. Doya

  • Parallel neural networks for learning sequential procedures

    Okihide Hikosaka;Hiroyuki Nakahara;Miya K. Rand;Katsuyuki Sakai

  • Metalearning and neuromodulation

    Kenji Doya

  • Modulators of decision making

    Kenji Doya

  • The computational neurobiology of learning and reward

    Nathaniel Douglass Daw;Kenji Doya

  • Multiple model-based reinforcement learning

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

  • Consensus Paper: Towards a Systems-Level View of Cerebellar Function: the Interplay Between Cerebellum, Basal Ganglia, and Cortex.

    Daniele Caligiore;Giovanni Pezzulo;Gianluca Baldassarre;Andreea C. Bostan

  • Acquisition of stand-up behavior by a real robot using hierarchical reinforcement learning

    Jun Morimoto;Kenji Doya

  • A neural correlate of reward-based behavioral learning in caudate nucleus: a functional magnetic resonance imaging study of a stochastic decision task.

    Masahiko Haruno;Tomoe Kuroda;Kenji Doya;Keisuke Toyama

  • Validation of decision-making models and analysis of decision variables in the rat basal ganglia.

    Makoto Ito;Kenji Doya

  • Low-serotonin levels increase delayed reward discounting in humans

    Nicolas Schweighofer;Mathieu Bertin;Kazuhiro Shishida;Yasumasa Okamoto

  • Meta-learning in reinforcement learning

    Nicolas Schweighofer;Kenji Doya

  • Hierarchical Bayesian estimation for MEG inverse problem.

    Masa-aki Sato;Taku Yoshioka;Shigeki Kajihara;Keisuke Toyama

  • Robust Reinforcement Learning

    Jun Morimoto;Kenji Doya

  • Activation of Dorsal Raphe Serotonin Neurons Underlies Waiting for Delayed Rewards

    Katsuhiko Miyazaki;Kayoko W. Miyazaki;Kenji Doya

  • Learning CPG-based biped locomotion with a policy gradient method

    Takamitsu Matsubara;Jun Morimoto;Jun Nakanishi;Masa-aki Sato

Frequent Co-Authors

Mitsuo Kawato
Mitsuo Kawato Advanced Telecommunications Research Institute International
Yasumasa Okamoto
Yasumasa Okamoto Hiroshima University
Shigeto Yamawaki
Shigeto Yamawaki Hiroshima University
Nicolas Schweighofer
Nicolas Schweighofer University of Southern California
Go Okada
Go Okada Hiroshima University
Jun Morimoto
Jun Morimoto Advanced Telecommunications Research Institute International
Hideyuki Okano
Hideyuki Okano Keio University
Jun Tani
Jun Tani Okinawa Institute of Science and Technology
Okihide Hikosaka
Okihide Hikosaka National Institutes of Health

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