Director, Deputy Director,
independent members &
members at other sections

  • Director: Hidehiko Komine, Ph.D.
  • Deputy Director: Sunao Iwaki, Ph.D.
  • Deputy Director: Nana Itoh, Ph.D.
  • Principal Research Manager: Noriyuki Higo, Ph.D.

Independent members

  • Prime Senior Researcher: Motoyuki Akamatsu, Ph.D.
  • Prime Senior Researcher: Masataka Goto, Ph.D.
  • Chief Senior Researcher: Takanori Shibata, Ph.D.

Members at other sections

Mental and Physical Functions Modeling Group

  • Leader: Kenta Kimura, Ph.D.
This figure shows establishing techniques to evaluate cognitive aging, techniques to predict emotional states and their application to design better products/services, and techniques to assess human-to -human cognitive interaction, by building the quantitative model of mental/physical fitness through analyzing the neuro-cognitive measures, physiological data, and behavioral data obtained in daily life, based on the data science technologies

Mental and Physical Functions Modeling Group (MPFMG) focuses on developing techniques to evaluate mental and physical fitness by integrating neurocognitive measures such as EEG/(f)MRI, physiological data from cardiovascular systems (EEG etc.), and behavioral data acquired in daily life with data science technologies. Our research area includes neuro-behavioral studies of cognitive aging, human emotional processing, and human-to-human communication. We also conduct research to apply our findings to improve quality-of-life of elderly people, to support better products and/or service design, and to understand human-to-human cognitive interaction.

Mathematical Neuroscience Research Group

  • Leader: Narihisa Matsumoto, Ph.D.
This figure shows the research flow of brain data, data analysis, neural network model, and brain-inspired artificial intelligence.

Brain can perform complex information processing tasks such as pattern recognition and learning more flexibly than existent technologies. The aims of this group are to elucidate the mechnisms underlying information processing in the brain by analyzing brain data with mathematical methods like machine learning or sparse modeling, and to develop a brain-inspired artificial intelligence. Furhermore, these methods and models are analyzed by mathematical methods to mesuare their performance limit and generalization performance.

Neurorehabilitation Research Group

  • Leader: Aya Takemura, Ph.D.
This figure shows the research concept of Neurorehabilitation Research Group. The cyclic cooperation among basic brain research using animal models and developments of both evaluation and intervention technologies contributes to the clinical applications.

Neurorehabilitation, which takes into account evidence of the brain's capacity for reorganization, has received attention to ensure maximal functional recovery from brain damage caused by stroke. We are developing innovative neurorehabilitation technologies on the basis of scientific evidences mainly obtained from basic brain research using animals. Our project has three main components: study of brain reorganization that underlies functional recovery after stroke, and development of devices to monitor brain activity during rehabilitative training, and development of intervention methods to promote brain reorganization.

Integrative Neuroscience Research Group

  • Leader: Yasuko Sugase-Miyamoto, Ph.D.
This figure shows neural circuits in the brain and the function of the circuits, for example cognition, learning, motor, and action. Neural circuits that transmit electrical signals and those that deliver chemical signals are illustrated.
Neural mechanisms underlying cognition and behavior
and their practical use

The brain is composed of highly structured neural circuits arranged both in parallel and hierarchical, and both electrical and chemical signals play critical roles in information processing within and across the circuits. Our group is working toward understanding the physiological, molecular biological and anatomical aspects of the brain function including cognition, learning, motor, and more complex behaviors such as social behavior. Our aim is to provide basic research findings and to innovate neuroscience methods for developing techniques that assist information processing and for advancing artificial intelligence technologies.

Physiological System Research Group

  • Leader: Jun Sugawara, Ph.D.
This figure is explained by the following text body.

The mission of research group is to develop technologies that can sustain and improve Quality-of-Life and Wellness of people, including children and older adults with various health conditions. To accomplish our goal, we accumulate and integrate deep knowledge of human's central (e.g., cognitive) and peripheral (e.g., autonomic, cardiorespiratory, physical, and sensory) functions, which consequently becomes the foundation of innovative technologies that we implement our discoveries to the society.

Media Interaction Group

  • Leader: Tomoyasu Nakano, Ph.D.
This figure shows the three web applications;,, and

The Media Interaction Group targets a variety of media content (music, video, text, user activities, physical devices, etc.) and conducts research on media interaction technologies that can enrich people's life. In particular, our group aims to promote content creation and utilization and enhance the creativity of the society by bridging the gap between creators and consumers. Toward this goal, we develop value-creation support technologies that facilitate content creation by complementing knowledge, experience, and technique of creators. We also develop value-enhancement support technologies that provide consumers with various means of appreciation, retrieval, recommendation, and browsing. These media technologies and interaction technologies demand a broad range of basic and applied research. We conduct research on music information processing, singing information processing, human-computer interaction, web services, signal processing, machine learning, retrieval and recommendation, computer graphics and animation, visualization and auralization, crowdsourcing, community analysis and support, large-scale data processing, etc.

Human Behavior Research Group

  • Leader: Ken Kihara, Ph.D.
This figure shows the driving simulator.

We have developed measurement and evaluation methods of human behaviors. Our aims are to investigate the critical factors influencing behaviors during an interaction between the human and the system, to clarify a mechanism of the human behaviors, and to propose new mobility that is adaptive to automated and connected transportation. The team members are researchers focusing on behavior analysis, attention and HMI, stimulus-response compatibility effect, computational modelling, and energy metabolism and lifestyle habit. Our experiments have been conducted in experimental rooms, AIST driving simulator, AIST proving ground, and public roads.

The followings are our research topics:

  • Estimation of driver conditions in automated driving
  • Evaluation of driving skills and cognitive functions of elderly drivers
  • Investigation of driving pleasure while moving and operating

Cognitive Functions Research Group

  • Leader: Motohiro Kimura, Ph.D.
This figure shows the driver waring EEG proves.

In our research group, we investigate cognitive functions, such as perception, attention, memory, learning, decision, and emotion related to human mobility by measuring brain functions, peripheral physiological responses, eye-movements, and behavior. We have developed unique techniques that are available to estimate driver’s attention and driving pleasure depending on electroencephalographic (EEG) signals. By using such techniques, we perform basic and applied researches to reduce the disincentive problems and improve the values in mobility

Advanced Devices of Polymer Materials
Cooperative Research Laboratory

  • Leader: Kensuke Sasai
This figure shows the smart rubber sensor that measures the driver's heartbeat, breathing, body movement, etc.
The driver's heartbeat, breathing, body movement, etc. are detected from the measured pressure change on the seat surface measured by the Smart Rubber (SR) sensor built into the seat or installed on the seat surface with a cushion shape. From the results, we estimate the driver's condition such as fatigue, drowsiness, and signs of sudden illness, and connect it to services such as warning, operation of the driving support system, and notification to the outside.

Sumitomo Riko-AIST Advanced Devices of Polymer Materials Cooperative Research Laboratory was established to contribute to the safety, security, and comfort of people’s life by combining the advanced technology cultivated by Sumitomo Riko with the results of AIST's research and development. Specifically, we will clarify the capability of the estimation of the information and the human state by the experimental research that reproduces actual driving using a vehicle equipped with a sensing device. Among them, we will improve the comprehensive evaluation technology (advanced sensory quantification technology and data analysis technology, technological innovation by fusing existing and digital technology), and establish various technologies under development to add high value. We aim to contribute to the further development of the mobility society by creating product groups and solutions.