{"id":141,"date":"2018-01-11T15:59:15","date_gmt":"2018-01-11T06:59:15","guid":{"rendered":"http:\/\/www.cns.atr.jp\/kawato?page_id=141"},"modified":"2026-01-14T10:08:39","modified_gmt":"2026-01-14T01:08:39","slug":"dr-mitsuo-kawato","status":"publish","type":"page","link":"https:\/\/bicr.atr.jp\/kawato\/ja","title":{"rendered":"Top"},"content":{"rendered":"

2025\u5e748\u67088\u65e5 NEW!<\/strong><\/big><\/small><\/big><\/big><\/p>\n

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<\/strong>ATR\u306b\u51fa\u5411\u3057\u3066\u3044\u305fNTT\u306e\u4e94\u5473\u88d5\u7ae0\u3055\u3093\u3089\u3068\u767a\u5c55\u3055\u305b\u305f\u5c0f\u8133\u5185\u90e8\u30e2\u30c7\u30eb[1,2]\u3001ATR\u306b\u79c1\u3092\u62db\u3044\u3066\u4e0b\u3055\u3063\u305f\u4e7e\u654f\u90ce\u5148\u751f\u3068\u63d0\u6848\u3057\u305f\u9806\u9006\u5149\u5b66\u30e2\u30c7\u30eb[3]\u3001Daniel Wolpert\u3055\u3093\u3089\u3068\u63d0\u6848\u3057Neural Networks\u8a8c\u306b\u63b2\u8f09\u3057\u305fMOSAIC[4]\u306a\u3069\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n

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<\/strong>\u30ed\u30dc\u30c3\u30c8\u306b\u8133\u306e\u30e2\u30c7\u30eb\u3092\u57cb\u3081\u8fbc\u3080\u3068\u8a00\u3046\u65ac\u65b0\u306a\u30d1\u30e9\u30c0\u30a4\u30e0\u3092\u3001ERATO\u5b66\u7fd2\u52d5\u614b\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u306e\u30b0\u30eb\u30fc\u30d7\u30ea\u30fc\u30c0\u3092\u52d9\u3081\u3066\u304f\u308c\u305fStefan Schaal\u3055\u3093\u3001ICORP\u8a08\u7b97\u8133\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u306e\u7c73\u56fd\u5074\u306e\u76f8\u65b9\u306eChristopher Atkeson\u3055\u3093\u3068\u30b0\u30eb\u30fc\u30d7\u30ea\u30fc\u30c0\u306eGordon Cheng\u3055\u3093\u7b49\u3068\u69cb\u7bc9\u3057\u307e\u3057\u305f[5]\u3002\u73fe\u5728ATR\u8133\u60c5\u5831\u7814\u7a76\u6240\u30d6\u30ec\u30a4\u30f3\u30ed\u30dc\u30c3\u30c8\u30a4\u30f3\u30bf\u30d5\u30a7\u30fc\u30b9\u7814\u7a76\u5ba4\u30fb\u5ba4\u9577\u306e\u68ee\u672c\u6df3\u3055\u3093\u304cMiguel Nicolelis\u3055\u3093\u3068\u884c\u3063\u305f\u3001Duke\u5927\u5b66\u306e\u30b5\u30eb\u3068ATR\u306e\u30d2\u30e5\u30fc\u30de\u30ce\u30a4\u30c9\u3092\u30a4\u30f3\u30bf\u30fc\u30cd\u30c3\u30c8\u3067\u53cc\u65b9\u5411\u306b\u7e4b\u3044\u3067\u3001\u30d6\u30ec\u30a4\u30f3\u30de\u30b7\u30f3\u30a4\u30f3\u30bf\u30d5\u30a7\u30fc\u30b9\u306b\u3088\u3063\u3066\u6b69\u884c\u3055\u305b\u308b\u5b9f\u9a13\u304c\u5370\u8c61\u6df1\u304b\u3063\u305f\u3067\u3059[6]\u3002<\/p>\n

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<\/strong>\u69d8\u3005\u306a\u8a08\u7b97\u30e2\u30c7\u30eb\u3092\u5b9f\u9a13\u3067\u691c\u8a3c\u3059\u308b\u3053\u3068\u3084\u3001\u7406\u8ad6\u306b\u3082\u3068\u3065\u304f\u5b9f\u9a13\u3092\u884c\u3046\u4e8b\u304c\u51fa\u6765\u307e\u3057\u305f\u3002\u5f53\u6642\u96fb\u7dcf\u7814\u306b\u304a\u3089\u308c\u305f\u6cb3\u91ce\u61b2\u4e8c\u5148\u751f\u306e\u7814\u7a76\u30b0\u30eb\u30fc\u30d7\u3068\u5171\u540c\u3067\u5c0f\u8133\u5185\u90e8\u30e2\u30c7\u30eb\u4eee\u8aac\u3092\u691c\u8a3c\u3059\u308b\u3053\u3068\u304c\u51fa\u6765\u305f\u306e\u306f\u3068\u3066\u3082\u5e78\u904b\u3067\u3057\u305f[7,8]\u3002\u4e94\u5473\u88d5\u7ae0\u3055\u3093\u3001\u5927\u9808\u7406\u82f1\u5b50\u3055\u3093\u3084Etienne Burdet\u3055\u3093\u3089\u3068\u306f\u30ed\u30dc\u30c3\u30c8\u30de\u30cb\u30d4\u30e5\u30e9\u30f3\u30c0\u30e0[9,10]\u3001\u4eca\u6c34\u5bdb\u3055\u3093\u7b49\u3068\u306ffMRI[11]\u3092\u7528\u3044\u305f\u5b9f\u9a13\u306b\u3082\u624b\u3092\u4ed8\u3051\u308b\u3088\u3046\u306b\u306a\u308a\u3001\u5f37\u5316\u5b66\u7fd2\u30e2\u30c7\u30eb\u306b\u57fa\u3065\u304ffMRI\u5b9f\u9a13\u306b\u3064\u3044\u3066\u306f\u3001\u79c1\u3068\u9285\u8c37\u8ce2\u6cbb\u3055\u3093\u3001\u6625\u91ce\u96c5\u5f66\u3055\u3093\u304c\u3001\u4e16\u754c\u3067\u521d\u3081\u3066computational model based neuroimaging\u3068\u8a00\u3046\u7528\u8a9e\u3092\u4f7f\u3044\u307e\u3057\u305f [12,13]\u3002<\/p>\n

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<\/strong>\u8d85\u591a\u6b21\u5143\u306e\u30c7\u30fc\u30bf\u3092\u591a\u6570\u306e\u30b5\u30f3\u30d7\u30eb\u306b\u3064\u3044\u3066\u8a08\u6e2c\u3057\u3001\u6a5f\u68b0\u5b66\u7fd2\u3092\u5fdc\u7528\u3057\u3066\u8133\u79d1\u5b66\u3092\u7cbe\u5bc6\u79d1\u5b66\u306b\u3059\u308b\u3068\u3044\u3046\u65b9\u5411\u6027\u304c\u6709\u671b\u3060\u3068\u611f\u3058\u3066\u3044\u307e\u3059\u3002\u4f8b\u3048\u3070\u5b89\u9759\u6642\u8133\u6d3b\u52d5\u3092\u8907\u6570\u306e\u30e2\u30c0\u30ea\u30c6\u30a3\u30fc\u3067\u9577\u6642\u9593\u8a08\u6e2c\u3059\u308b\u7cbe\u5bc6\u306a\u5b9f\u9a13\u3001\u60a3\u8005\u3055\u3093\u3092\u542b\u30802\u5343\u4eba\u306e\u8133\u30d3\u30c3\u30b0\u30c7\u30fc\u30bf[14]\u3001David Marr\u6d41\u306e\u8a08\u7b97\u7406\u8ad6\u3068\u8133\u30c0\u30a4\u30ca\u30df\u30af\u30b9\u30e2\u30c7\u30eb\u304c\u521d\u3081\u3066\u7d71\u5408\u3055\u308c\u308b\u5146\u3057\u304c\u3042\u308b\u3053\u3068\u3001\u67f4\u7530\u548c\u4e45\u3055\u3093\u3001\u6e21\u908a\u6b66\u90ce\u5148\u751f\u3001\u4f50\u3005\u6728\u7531\u9999\u5148\u751f\u3068\u5171\u540c\u3067\u958b\u767a\u3057\u305fDecoded Neurofeedback[15]\u3084\u3001\u798f\u7530\u3081\u3050\u307f\u3055\u3093\u304c\u4e2d\u5fc3\u306b\u306a\u3063\u3066\u958b\u767a\u3057\u305fFunctional Connectivity Neurofeedback[16]\u306a\u3069\u306e\u65b0\u3057\u3044\u30c4\u30fc\u30eb\u3092\u7528\u3044\u3066\u8133\u6d3b\u52d5\u304b\u3089\u5fc3\u3078\u306e\u56e0\u679c\u95a2\u4fc2\u3092\u660e\u3089\u304b\u306b\u51fa\u6765\u308b\u795e\u7d4c\u79d1\u5b66\u3092\u69cb\u7bc9\u3057\u305f\u3044\u3068\u8003\u3048\u3066\u3044\u307e\u3059[17]\u3002<\/p>\n

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\u53c2\u8003\u6587\u732e
<\/strong>[1] Kawato, M., Furukawa, K., Suzuki, R. (1987): A hierarchical neural-network model for control and learning of voluntary movement, Biological Cybernetics<\/em>, Vol.57<\/strong>, pp.169-185.<\/p>\n

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<\/p>\n[2] Kawato, M., Gomi, H. (1992): A computational model of four regions of the cerebellum based on feedback-error-learning, Biological Cybernetics<\/em>, Vol.68<\/strong>, pp.95-103.<\/p>\n

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<\/p>\n[3] Kawato, M., Hayakawa, H., Inui, T. (1993): A forward-inverse optics model of reciprocal connections between visual cortical areas, Network:Computation in Neural systems<\/em>, Vol.4<\/strong>, pp.415-422.<\/p>\n

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<\/p>\n[4] Wolpert, D., Kawato, M. (1998): Multiple paired forward and inverse models for motor control, Neural Networks<\/em>, Vol.11,<\/strong> pp.1317-1329.<\/p>\n

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<\/p>\n[5] Atkeson, CG., Hale, J., Pollick, F., Riley, M., Kotosaka, S., Schaal, S., Shibata, T., Tevatia, G., Vijayakumar, S., Ude, A., Kawato, M. (2000): Using humanoid robots to study human behavior, IEEE Intelligent Systems: Special Issue on Humanoid Robotics<\/em>, Vol.15<\/strong>, pp.46-56.<\/p>\n

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<\/p>\n[6] Morimoto, J., Kawato, M. (2015): Creating the brain and interacting with the brain: an integrated approach to understanding the brain, Journal of the Royal Society Interface<\/em>, Vol.12<\/strong>, 20141250.<\/p>\n

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<\/p>\n[7] Shidara, M., Kawano, K., Gomi, H., Kawato, M. (1993): Inverse-dynamics model eye movement control by purkinje cells in the cerebellum, Nature<\/em>, Vol.365<\/strong>, pp.50-52.<\/p>\n

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<\/p>\n[8] Kawato, M. (1999): Internal models for motor control and trajectory planning, Current Opinion in Neurobiology<\/em>, Vol.9<\/strong>, pp.718-727.<\/p>\n

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<\/p>\n[9] Gomi, H., Kawato, M. (1996): Equilibrium-point control hypothesis examined by measured arm-stiffness during multijoint movement, Science<\/em>, Vol.272<\/strong>, pp.117-120.<\/p>\n

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<\/p>\n[10] Burdet, E., Osu, R., Franklin, D., Milner, T., Kawato, M. (2001): The central nervous system stabilizes unstable dynamics by learning optimal impedance, Nature<\/em>, Vol.414<\/strong>, pp.446-449.<\/p>\n

<\/p>\n

<\/p>\n[11] 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 new tool, Nature<\/em>, Vol.403<\/strong>, pp.192-195.<\/p>\n

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<\/p>\n[12] Haruno, M., Kuroda, T., Doya, K., Toyama, K., Kimura, M., Samejima, K., Imamizu, H., Kawato, M. (2004): A neural correlate of reward-based behavioral learning in caudate nucleus: a functional magnetic resonance imaging study of a stochastic decision task, Journal of Neuroscience<\/em>, Vol.24<\/strong>, pp.1660-1665.<\/p>\n

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<\/p>\n[13] Haruno, M., Kawato, M. (2006): Different neural correlates of reward expectation and reward expectation error in the putamen and caudate nucleus during stimulus-action-reward association learning, Journal of Neurophysiology<\/em>, Vol.95<\/strong>, pp.948-959.<\/p>\n

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<\/p>\n[14] Yahata, N., Morimoto, J., Hashimoto, R., Lisi, G., Shibata, K., Kawakubo, Y., Kuwabara, H., Kuroda, M., Yamada, T., Megumi, F., Imamizu, H., Nanez, JE.,\u00a0Takahashi, H., Okamoto, Y., Kasai, K., Kato, N., Sasaki, Y., Watanabe, T., Kawato, M. (2016): A small number of abnormal brain connections predicts adult autism spectrum disorder, Nature Communications<\/em>, Vol.7<\/strong>, p.11254.<\/p>\n

<\/p>\n

<\/p>\n[15] Shibata, K., Watanabe, T., Sasaki, Y., Kawato, M. (2011): Perceptual learning incepted by decoded fMRI neurofeedback without stimulus presentation, Science<\/em>, Vol.334<\/strong>, No.6061, pp.1413-1415<\/p>\n

<\/p>\n

<\/p>\n[16] Megumi, F., Yamashita, A., Kawato, M., Imamizu, H. (2015): Functional MRI neurofeedback training on connectivity between two regions induces long-lasting changes in intrinsic functional network, Frontiers in Human Neuroscience<\/em>, Vol.9<\/strong>, p.160.<\/p>\n

<\/p>\n

<\/p>\n[17] Watanabe, T., Sasaki, Y., Shibata, K., Kawato, M. (2017): Advances in fMRI real-time neurofeedback,\u00a0Trends in Cognitive Sciences<\/em>, Vol.21<\/strong>, pp.997-1010<\/p>\n

<\/p>\n

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