Brain-Machine Interface Technology
Main Lab Location:
Visiting Professors of
Nara Institute of Science and Technology, Computational Neuroscience Laboratory
Kyoto University, Graduate School of Informatics
Toyama Prefectural University
Kanazawa Institute of Technology, Human Information System Laboratories
Osaka University, Graduate School of Frontier Biosciences
National Institute for Physiological Sciences
National Institute of Informatics
The University of Tokyo, Graduate School of Information Science and Technology,
Tokyo Institute of Technology, Precision and Intelligence Laboratory
Tamagawa University, Brain Science Institute
2-2-2 Hikaridai Seika-cho, Soraku-gun, Kyoto 619-0288 Japan
My lab develops brain machine interfaces for human care and advanced communications.
Japan’s low birthrate and greying population is leading to a large expansion in health care requirements. The predicted impact of increasing numbers of elderly people with medical (e.g. stroke) and psychiatric (e.g. depression and anxiety) mean that one third of Japan’s workforce are estimated to be caregivers by 2030. Therefore we urgently need to develop new care-giving options, including technologies and services that can supplement and replace humans.
We are focusing on brain-machine interface technology (BMI) that can achieve sophisticated human care by research into and applications of neuroscience. For example, we are designing robots that can be controlled by the users brain signals to aid in simple tasks such as nursing care.
In addition, we investigate the use of BMI and robot technology in information and communication technologies, to develop communications systems where a machine can intuit a user’s feelings and thoughts in way people do when interacting with one another. A further ambitious goal is to use BMI technology in inter-personal communications by decoding information from one brain (decipher and extract) and encoding it to another (code and approach).
Our research is built on an organic approach that combines neuroscience, biophysics, and information technology along with new measuring devices. This should enable BMI technology to revolutionize healthcare and welfare, while at the same time advancing our understanding of the neurosciences and information and communication sciences.
Shibata K, Watanabe T, Sasaki Y, Kawato M (2011). Perceptual learning incepted by decoded fMRI neurofeedback without stimulus presentation, Science, 334(6061), 1413-1415
Sugimoto N, Morimoto J, Hyon SH, Kawato M (2012). The eMOSAIC model for humanoid robot control. Neural Netw. 2012 May;29-30, 8-19.
Imamizu H., Miyauchi S., Tamada,T., Sasaki Y., Takino R., Puetz B., Yoshioka T., Kawato M. (2000). Human cerebellar activity reflecting an acquired internal model of a novel tool. Nature, 403, 192-195
see ATR homepage below.