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2. 2.1. 3.1.1. 3 (1) (2) () (4) (5) 3.1.2. 3.1.4. 1970 1984 Doya K. What are the computations of the cerebellum, the basal ganglia, and the cerebral cortex. Neural Networks,12,961-974,1999JNNSJapanese Neural Network Society 2000 3

3.1.3 3 2 3.1.4. 20 Kawato, M., et al., Biol. Cybern.,57, 169-185,1987 1 1 Functional Magnetic Resonance Imaging fmri fmri fmri 2000 1 Nature Imamizu H., et al., Human cerebellar activity reflecting an acquired internal model of a new tool, Nature, 403(6766), 192-195, JAN13, 2000 3.1.5. 2 2001 Nature Burdet E. et al., The central nervous system stabilizes unstable dynamics by learning optimal impedance, Nature, 414(6862), 446-449, NOV22, 2001 4

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BMIBrain Machine Interface fmri BMI fmri MEGMagnetoencephalography NIRSnear-infrared spectroscopic imaging EEGElectroencephalogram ATR 400 MEG NIRS EEG 3.2.4. LTDLong Term Depression Kuroda, S., et al., J. Neurosci., 21, 5693-5702, 2001) LTD 18 CREST 18 3.2.5. H18 SCOPE-S 20062009 3.2.6. DB Computational Brain CBICORP2004.12009.1 7

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2000 4.3.2 2006 DB DB 2001 8 31 2001 National Geographic Discovery Channel TIME 2004 6 14 Rise of the Machines 4 1 (1999 11 17 ) fmri fmri MEG NIRS MEG fmri BMI 1 4.1.3. IEEEThe Institute of Electrical and Electronics Engineers, Inc.Humanoid Robots International Conference 2001 OIST 2004 2004 Bayesian Brain 2006 Computing Neurons6/267/7 ERATO 2004 200920052010 fmri Stem Cell() 7 9

2006 3 13 99 3.2. 4.2.1. (1) (2) (3) (4) BMI 4.2.2. (1) fmri fmri MEG NIRS MEG fmri BMI 1 (2) ERATO CREST 1999-2004 20032008 (3) 10

H18 SCOPE-S (4) 1980 ATR 20Kg 2Kg ERATO 4.2.2. ATR ICORP ATR BMI fmri MEGMagnetoencephalography NIRSnear-infrared spectroscopic imaging MEG fmri MEG ATR 400 MEGMagnetoencephalography 11

4.2.3. BMIBrain Machine Interface ATR http://www.atr.co.jp/html/topics/press_060526_j.html HR ATR 2006 5 24 fmrifunctional Magnetic Resonance Imaging MRI BMIBrain Machine Interface 3.3. 4.3.1. 1 No. Vol/No/P Schaal, S., et al. Wolpert, DM., et al. Wolpert, DM., et al. Schweighofe r, N., et al. Schweighofe r, N., et al. Schaal, S. Doya K. Constructive Incremental Learning from Only Local Information Neural Computation 1998 10/ /2047-2084 Multiple paired forward and inverse models Neural Networks 1998 11/7/1317-1 for motor control 329 Internal models in the cerebellum Trends in 1998 2/9/338-347 Cognitive Sciences Role of the cerebellum in reaching movements Eur. J. 1998 10/1/86-94 in humans.. Distributed inverse dynamics Neuroscience control Role of the cerebellum in reaching movements Eur. J. 1998 10/1/95-105 in humans.. A neural model of the Neuroscience intermediate cerebellum Is imitation learning the route to humanoid Trends in 1999 13/6/233-24 robots? Cognitive Sciences 2 What are the computations of the cerebellum, Neural Networks 1999 12/ the basal ganglia, and the cerebral cortex? /961-974 Kawato M. Internal models for motor control and Current Opinion 1999 9/ /718-727 trajectory planning in Neurobiology Imamizu H., Human Cerebellar activity reflecting an Nature 2000 403/6766/1 et al. acquired internal model of a new tool 92-195 Doya K. Complementary roles of basal ganglia and Current Opinion 2000 10/6/732-73 12

21 cerebellum in learning and motor control in Neurobiology 9 Burdet,E., The central nervous system stabilizes unstable Nature 2001 414/6862/4 et al. dynamics by learning optimal impedance 46-449 Haruno,M., MOSAIC model for sensorimotor learning and Neural 2001 13/10/2201- et al. control Computation 2220 Servos P., The neural substrates of biological motion Cerebral Cortex 2002 12/7/772-78 et al., perception: An fmri study 2 Doya K. Metalearning and neuromodulation Neural Networks 2002 15/4-5/495-506 Wolpert DM., et al. A unifying computational framework for motor control and social interaction Imamizu H., Modular organization of internal models of et al. tools in the human cerebellum Haruno M., A neural correlate of reward-based behavioral et al., learning in caudate nucleus:a fmri study of a stochastic decision task Tananaka Prediction of immediate and future rewards SC., et al., differentially recruits cortico-basal ganglia loops Cairhness,G Failure to consolidate the consolidation theory., et al., of learning for sensorimotor adaptation task S. Schaal, et Rhythmic arm movement is not discrete al. Samejima Representation of action-specific reward K., et al., values in the striatum 2 Phil. Tras. R. Soc. 2003 358/1431/5 Lon. Ser.B Bio. 93-602 Sci. Proc. Nat. Aca. 2003 100/9/5461- Sci. USA 5466 J. Neuroscience 2004 24/7/1660-1 665 Nature 2004 7/8/887-893 Neuroscience J. Neuroscience 2004 24/40/8662-8671 Nature 2004 7/10/1137-1 Neuroscience 144 Science 2005 310/5752/1 337-1340 13

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4 2006 4.3.4 1996 1996 10 1997 6 1998 2001 3 2004 ATR IEICE Fellow 2005 2006 2007 APNNA Outstanding Achievement Award 1996 2000 2003 2005 2006 2007 Neuroimage 21 1996 1997 1998 17 AVIRG 18

2003 2002 2004 2007 ICONIP Best Paper Award Schaal, S. 2002 2005 IEEE Robotics and Automation Society Best Paper Award 2002 16 2002 2007 2006 Neuroscience Research Excellent Paper Award 3.4. 4.4.1 35 40 19 4 19

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