Research Subject Group

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 Brain Science Institute
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

Tokyo Medical and Dental University

FY2019-2020 Publicly Offered Research Group

A01 Perception and prediction

Learning perceptual representations in biological and artificial neural networks

Andrea Benucci

RIKEN Center for Brain Science
Team Leader
Creation of novel paradigms to integrate neural network learning with dendrites

Tomoki Fukai

Okinawa Institute of Science and Technology
Professor
Neural Representation of Internal Model Based Decision Making

Kosuke Hamaguchi

Kyoto University Graduate School of Medicine, Department of Biological Sciences
Senior Lecturer
One shot learning based on computational theory of higher visual cortex

Haruo Hosoya

ATR
Senior Researcher
Studying a Brain Model based on Self-Simulation and Homeostasis

Takashi Ikegami

The University of Tokyo, Graduate School of Arts and Sciences, Department of General Systems Studies
Professor
Predictive coding on auditory processing: spatio-temporal structure of signal flow in whole-cortical electrocorticograms

Misako Komatsu

RIKEN Center for Brain Science
Research Scientist
Analyses of off-line learning algorithm during sleep by using super large-scale electrophysiology

Hiroyuki Miyawaki

Osaka City University, Graduate School of Medicine
Assistant Professor
Nonlinear dynamical representation learning and its application to analysis and prediction of the brain

Hiroshi Morioka

RIKEN Center for Advanced Intelligence Project
Postdoctoral Researcher
Elucidation of neural mechanism underlying model-based decision making using optogenetic manipulation and imaging of the central serotonergic system

Yu Ohmura

Hokkaido University
Lecturer
Decision making based on multi-dimensional state- and action-space, and the neural coding in the basal ganglia

Kazuyuki Samejima

Tamagawa University, Brain science institute
Professor
Feature representation mapping between deep neural network and psychophysical texture properties

Hayaru Shouno

University of Electro-Communications
Professor

A02 Motor control and behaviors

Study of the mechanisms of the nervous system through neural network models

Yuichi Iino

The University of Tokyo, Graduate School of Science, Department of Biological Sciences
Professor
Architectonic organization of prefrontal cortex-related neural networks involved in action selection

Ken-ichi Inoue

Kyoto University, Primate Research Institute
Assistant professor
Meta-learning mechanism based on sensory- and reward- prediction errors: a computational approach to understanding the neural mechanism

Jun Izawa

University of Tsukuba
Associate Professor
Visualization of striatal cell type-specific neuronal activity during stimulus discrimination operant learning

Kazuto Kobayashi

Fukushima Medical University, Dept. Molecular Genetics
Professor
Pathway-specific roles of midbrain dopamine neurons in value-based decision-making

Hideyuki Matsumoto

Osaka City University
Assistant Professor
Deep Parallel Reinforcement Learning with Model-Free and Model-Based Methods

Eiji Uchibe

ATR Computational Neuroscience Laboratories
Principal Researcher

A03 Cognition and sociality

Computational Modeling of Dynamical Social Interaction in Non-Human Primate

Koki Mimura

QST NIRS, Department of Functional Brain Imaging
Researcher
Construction and evaluation of neurocomputational models of natural language

Yohei Oseki

University of Tokyo
Assistant Professor
Extraction of versatile features from resting state fMRI using deep neural networks

Yuichi Yamashita

National Center of Neurology and Psychiatry
Section chief

FY2017-2018 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

Research Subject Group

A01 Perception and prediction

Improvement of Predictability by Integrating Deep Learning with Symbol Processing

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

Neural bases of congruency-sequence effects on conflict costs

A02 Motor control and behaviors

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

Computational mechanisms of implicit sensorimotor control

Roles of the dopamine system in reward and attentional processing

Neuronal circuit mechanisms of reward/goal-directed behavior

A03 Cognition and sociality

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

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

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

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

FY2019-2020 Publicly Offered Research Group

A01 Perception and prediction

Learning perceptual representations in biological and artificial neural networks

Creation of novel paradigms to integrate neural network learning with dendrites

Neural Representation of Internal Model Based Decision Making

One shot learning based on computational theory of higher visual cortex

Studying a Brain Model based on Self-Simulation and Homeostasis

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

Analyses of off-line learning algorithm during sleep by using super large-scale electrophysiology

Nonlinear dynamical representation learning and its application to analysis and prediction of the brain

Elucidation of neural mechanism underlying model-based decision making using optogenetic manipulation and imaging of the central serotonergic system

Decision making based on multi-dimensional state- and action-space, and the neural coding in the basal ganglia

Feature representation mapping between deep neural network and psychophysical texture properties

A02 Motor control and behaviors

Study of the mechanisms of the nervous system through neural network models

Architectonic organization of prefrontal cortex-related neural networks involved in action selection

Meta-learning mechanism based on sensory- and reward- prediction errors: a computational approach to understanding the neural mechanism

Visualization of striatal cell type-specific neuronal activity during stimulus discrimination operant learning

Pathway-specific roles of midbrain dopamine neurons in value-based decision-making

Deep Parallel Reinforcement Learning with Model-Free and Model-Based Methods

A03 Cognition and sociality

Computational Modeling of Dynamical Social Interaction in Non-Human Primate

Construction and evaluation of neurocomputational models of natural language

Extraction of versatile features from resting state fMRI using deep neural networks

FY2017-2018 Publicly Offered Research Group

A01 Perception and prediction

Using recurrent neural networks to study neural computations in cortical networks

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

Novel architecture and learning rules inspired by cortical microcircuits

Imaging learning rule from neural and molecular activity

Deep stacked independent component analysis and its application to brain science

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

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

Inferring networks from neuronal signals and predicting emergent activity patterns

Decoding of complex neural representations in prefrontal cortex

Development of novel artificial intelligence using ECoG big data

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

A02 Motor control and behaviors

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

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

Parallel deep reinforcement learning

A03 Cognition and sociality

Dialogue between the predictive coding and brain mechanism for active inference

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

Computational and neural mechanisms underlying structure learning

Development of computational assay for psychiatric disorders using deep learning

Management Group Organization

Project Leader

Organizing committee

Training promotion committee

Public relations comittee

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