Mitsuo Kawato

Title: Towards Manipulative Neuorscience based on Brain-Network-Interface

Bio sketch: Prof. Kawato received the B.S. degree in physics from Tokyo University in 1976 and the M.E. and Ph. D. degrees in biophysical engineering from Osaka University in 1978 and 1981, respectively. From 1981 to 1988, he was a faculty member and lecturer at Osaka University. Professor Kawato has served as a director of ATR computational Neuroscience Laboratories and a research supervisor of JST, ICORP Computational Brain Project. He is now concurrently working as a visiting professor at Kanazawa Institute of Technology, Nara Institute of Science and Technology, Osaka University, the National Institute for Physiological Sciences and Kyoto Prefectural University of Medicine.  He has been appointed Toyama Prefectural University as a Specially Appointed Visiting Professor. He was awarded the Yonezawa founder's medal memorial special award of The Institute of Electronics, Information and Communication Engineers, in 1991, the outstanding research award of the International Neural Network Society in 1992, the Osaka Science Prize in 1993, the 10th Tsukahara Naka-akira Memorial Award in 1996, the Tokizane Toshihiko Memorial Award in 2001, IEICE fellow in 2004, the Chunichi Cultural Award and the Shida Rinzaburo Award in 2005, the Asahi Prize in 2007.  He is a governing board member of the Japanese Society of Neuroscience and a Member of American Physiologica Society. He is currently serving as an Editor of HFSP Journal.

For the last 15 years he has been working in computational neuroscience and neural network modeling.  He published about 200 papers, reviews and books.  Research topics include simulation study of dendritic spines, feedback-error-learning model and its applications to industrial robot manipulators, movement trajectory formation, bi-directional theory for interactions between cortical areas, cerebellar internal models, and teaching by demonstration for robots.

Professor Kawato’s work focuses on constructing a brain in order to understand the brain, through building a brain to the extent that we can build a brain. More concretely, he has been investigating the information processing of the brain with the long-term goal that machines, either computer programs or robots, could solve the same computational problems as those that the human brain solves, while using essentially the same principles. With these general approaches, he has greatly contributed in elucidating visual information processing, optimal control principles for arm trajectory planning, internal models in the cerebellum, teaching by demonstration for robots, human interfaces based on electoromyogram, and applications in rehabilitation medicine. Recently, he proposes a new experimental paradigm; manipulative neuroscience.