Organization

Research Subject

A01 Perception and prediction

  • Improvement of Predictability by Integrating Deep Learning with Symbol  Processing

    Yutaka Matsuo

    University of Tokyo

  • Elucidation of the Mathematical Basis and Neural Mechanisms of Multi-layer Representation Learning

    Kenji Doya

    Okinawa Institute of Science and Technology

  • Neural bases of congruency-sequence effects on conflict costs

    Keiji Tanaka

    RIKEN Brain Science Institute

A02 Motor control and behaviors

  • Internal model construction by observing others and policy acquisition through self-learning

    Jun Morimoto

    ATR Brain Information Communication Research Laboratory Group

  • Computational mechanisms of implicit sensorimotor control

    Hiroaki Gomi

    NTT Communication Science Labs.

  • Roles of the dopamine system in reward and attentional processing

    Masayuki Matsumoto

    University of Tsukuba

  • Neuronal circuit mechanisms of reward/goal-directed behavior

    Takatoshi Hikida

    Osaka University

A03 Cognition and sociality

  • Understanding Neural Computation for Double Articulation Analysis Bridging Sensory-motor Information and Natural Language in Human Brain

    Tadahiro Taniguchi

    Ritsumeikan University

  • Neurocomputational primitives for decision-making with use of models of others

    Hiroyuki Nakahara

    RIKEN

  • Neural mechanisms of data abstraction and deductive inference in the prefrontal cortex

    Masamichi Sakagami

    Tamagawa University

  • Understanding of neural basis of thought disorder in psychiatric disorders and development of assistance for them.

    Hidehiko Takahashi

    Kyoto University

Publicly Offered Research Group

A01 Perception and prediction

  • Using recurrent neural networks to study neural computations in cortical networks

    Andrea Benucci

    RIKEN Brain Science Institute
    Team Leader (Assistant Professor)

  • Mutual reference approach bewteen artificail inteligence and neural correlates for investigation of value
    emergence

    Junichi Chikazoe

    National Institute for Physiological Sciences
    Associate professor

  • Novel architecture and learning rules inspired by cortical microcircuits

    Tomoki Fukai

    RIKEN BSI
    Senior Team Leader

  • Imaging learning rule from neural and molecular activity

    Kosuke Hamaguchi

    Kyoto University
    Senior Lecturer

  • Deep stacked independent component analysis and its application to brain science

    Junichiro Hirayama

    RIKEN Center for Advanced Intelligence Project
    Researcher

  • A study of Space/Sound Perception by using a Generative Deep Learning approach

    Takashi Ikegami

    University of Tokyo
    Professor

  • Predictive coding on auditory processing: spatio-temporal structure of signal flow in whole-cortical electrocorticograms

    Misako Komatsu

    RIKEN BSI
    Researcher

  • Inferring networks from neuronal signals and predicting emergent activity patterns

    Shigeru Shinomoto

    Kyoto University
    Associate Professor

  • Decoding of complex neural representations in prefrontal cortex

    Takanori Uka

    University of Yamanashi
    Professor

  • Development of novel artificial intelligence using ECoG big data

    Takufumi Yanagisawa

    Osaka University
    Endowed Division Lecturer

  • Multi-functional CNN by Piling up Single Functions for Emergence of New Functions

    Keiji Yanai

    The University of Electro-Communications
    Professor

A02 Motor control and behaviors

  • Organization of Cortico-Basal Ganglia and Cortico-Cerebellar Loop Circuits that Arise from the Prefrontal Cortex

    Kenichi Inoue

    Kyoto University
    Assistant Professor

  • Computational understanding of the neural basis of reward-based and sensory-based motor learning

    Jun Izawa

    University of Tsukuba
    Associate Professor

  • Parallel deep reinforcement learning

    Eiji Uchibe

    ATR
    Principal Researcher

A03 Cognition and sociality

  • Dialogue between the predictive coding and brain mechanism for active inference

    Yutaka Komura

    Kyoto University
    Professor

  • Social context segmentation analysis in a primate model of Autism Spectrum Disorder

    Koki Mimura

    QST NIRS
    Researcher

  • Computational and neural mechanisms underlying structure learning

    Shinsuke Suzuki

    Tohoku University
    Assistant Professor

  • Development of computational assay for psychiatric disorders using deep learning

    Yuichi Yamashita

    National Center of Neurology and Psychiatry
    Senior Team Leader

Management Group Organization

Project Leader

  • Head office

    Kenji Doya

    Machine learning・Computational neuroscienc

Organizing committee

  • Co-researcher

    Masamichi Sakagami

    Brain science

    Chair of Organizing committee

  • Collaborator

    Hiroaki Gomi

    Computational neuroscience

  • Collaborator

    Takatoshi Hikida

    Neuroscience・Psychiatry

Training promotion committee

  • Co-researcher

    Hiroyuki Nakahara

    Mathematical Neuroscience

    Chair of Training promotion committee

  • Collaborator

    Keiji Tanaka

     

  • Collaborator

    Jun Morimoto

    Machine learning ・ Robotics

  • Collaborator

    Masayuki Matsumoto

    Neuroscience

Public relations comittee

  • Co-researcher

    Tadahiro Taniguchi

    Artificial Intelligence ・ Robotics

    Chair of Public relations committee

  • Collaborator

    Yutaka Matsuo

    Artificial Intelligence

  • Collaborator

    Hidehiko Takahashi

    Psychiatry

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