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Neuroscience

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

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
Shigeto Yamawaki
Shigeto Yamawaki Hiroshima University
Yasumasa Okamoto
Yasumasa Okamoto Hiroshima University
Nicolas Schweighofer
Nicolas Schweighofer University of Southern California
Go Okada
Go Okada Hiroshima University
Okihide Hikosaka
Okihide Hikosaka National Institutes of Health
Kenji F. Tanaka
Kenji F. Tanaka Keio University
Akihiro Yamanaka
Akihiro Yamanaka Chinese Academy of Sciences
Allen I. Selverston
Allen I. Selverston University of California, San Diego

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