[53] Koizumi A & Kawato M: Implicit decoded neurofeedback training as a clinical tool, In Hampson M (eds), FMRI Neurofeedback, Elsevier Ltd., 2021
[52] Taylor JE, Jalon I, Chiba T, Motegi T, Kawato M & Hendler T: Translation to the clinic and other modalities, In Hampson M (eds), FMRI Neurofeedback, Elsevier Ltd., 2021
[51] Kawato M: Brain Machine Interface and Neuroimaging, In Jaeger D, Jung R, Encyclopedia of Computational Neuroscience, pp.441-443, Springer, 2015
[50] Kawato M: Cerebellum: Models, Reference Module in Biomedical Sciences, http://dx.doi.org/10.1016/B978-0-12-801238-3.04545-1, Elsevier Ltd., 2014
[49] Hirata M, Yanagisawa T, Matsushita K, Sugata H, Kamitani Y, Suzuki T, Yokoi H, Goto T, Shayne M, Saito Y, Kishima H, Kawato M, Yoshimine T: Brain-Machine Interface Using Brain Surface Electrodes: Real-Time Robotic Control and a Fully Implantable Wireless System, Biomedical Engineering and Cognitive Neuroscience for Healthcare; Interdisciplinary Applications, IGI GLOBAL, USA, to be released, 2012�@�@�@ �@
[48] Chaminade T, Kawato M: Mutual benefits of using humanoid robots, Handbook of Social Neuroscience, Oxford University Press, USA, to be released, 2011
[47] Oztop E, Kawato M: Models for the control of grasping, In: Nowak D, Hermsdoerfer J (eds.), Sensorimotor Control of Grasping : Physiology and Pathophysiology, Cambridge University Press, 2009
[46] Ogasawara H, Kawato M: Computational models ofcerebellar long-term memory. Systems Biology. In: Nakanishi S, Kageyama R, Watanabe D(eds.) pp.169 -182. Springer, 2009
[45] Kawato M: Reinforcement
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[43] Tanaka H, Kawato M: Theories on motor learning. Encyclopedia of Neuroscience,
part20, pp4056-4060.
Springer-Verlag, Germany, 2008
[42] Oztop E, Babic J, Hale J, Cheng G, Kawato M: From biologically realistic imitation to robot teaching via human motor learning. Neural Information Processing, 4985, 214-221, 2008
[41] In Haggard P, Rossetti Y, Kawato M (Eds.) Sensorimotor foundations of higher cognition, Attention and Performance, XXII, Oxford University Press, UK,pp.1-659, 2008
[40] Ting J, D'Souza A, Yamamoto K, Yoshioka T, Hoffman D, Kakei S, Sergio L, Kalaska J, Kawato M, Strick P, Schaal S: Predicting EMG Data from M1 Neurons with Variational Bayesian Least Squares, In: Weiss Y, Schokopf B, Platt J (eds.), Advances in Neural Information Processing Systems 18, Cambridge, MA: MIT Press, pp.1361-1368, 2005
[39] Wolpert DM, Doya K, Kawato M: A unifying computational
framework for motor control and social interaction. In Frith C, Wolpert
DM (Eds.) The Neuroscience of Social Interaction. Oxford
University Press, Oxford, UK,
[38] Haruno M, Wolpert D, Kawato M: Hierarchical MOSAIC for movement
generation. In Ono T, Matsumoto G, Llinas RR, Berthoz A, Norgren R,
Nishijo H, Tamura R (Eds.) Excepta Medica International Coungress
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[37] Kawato M, Kuroda T, Imamizu H, Nakano E, Miyauchi S, Yoshioka T: Internal
forward models in the cerebellum: fMRI study on grip force and load
force coupling. In Prablanc C, Pelisson D, Rossetti Y (Eds.) Progress
in Brain Research.142 "Neural Control of Space Coding and
Action Production". Elsevier, Amsterdam. The Netherlands,
[36] Kawato M: Cerebellum and motor control. In Arbib M (Ed.) 2nd
Edition of The Handbook of Brain Theory and Neural Networks. MIT
Press, Cambridge, Massachusetts,
[35] Miyamoto H, Wolpert DM, Kawato M: Computing the optimal trajectory
of arm movement:
the TOPS(Task Optimization in the Presence of Signal-dependent nose)
model. Duro RJ, Santos J, Grana M (Eds.) Studies in Fuzziness and
Soft Computing. 109 Springer-Verlag,
[34] Munhall KG, Kawato M, Bateson EV: Coarticulation and physical
models of speech production. Broe MB, Pierrehumbert JB (Eds.) Papers
in Laboratory Phonology V: Acquisition and the Lexicon Cambridge
University Press, Cambridge, U.S.A.,
[33] Kawato M: A bi-directional theory approach to prerational
intelligence. Ritter H, Cruse H, Dean J (Eds.) Prerational
Intelligence: Adaptive Behavior and Intelligent Systems without Symbols
and Logic 2. Kluwer Academic Publishers, Dordrecht, The
Netherlands,
[32] Koike Y, Kawato M: Estimation of movement from surface EMG signals
using a neural network model. Winters JM, Crago P (Eds.) Biomechanics
and Neural Control of Posture and Movement Springer-Verlag, New
York, U.S.A,
[31] Kawato M: Robotics as a tool for neuroscience: cerebellar internal
models for robotics and cognition. Hollerbach MH, Koditschek DE (Eds.) Robotics
Research, The Ninth International Symposium Springer-Verlag,
London,
[30] Haruno M, Wolpert D, Kawato M: Multiple paired forward-inverse
models for human motor learning and control. Advances in Neural
Information Processing Systems. 11. MIT Press, Cambridge,
Massachusetts,
[29] Kawato M, Wolpert D: Internal models for motor control. Glickstein
M (Ed.) Sensory Guidance of Movement. John Wiley & Sons
Ltd., Chichester, Sussex,
[28] Kawato M: Bidirectional theory approach to consciousness. Ito M,
Miyashita Y, ET Rolls(Eds.) Cognition, Computation and
Consciousness. Oxford University Press, Oxford,
[27] Kawato M: Internal models and thinking. Ito M(Ed.) Concept
Formation, Thinking and Their Development. IIAS Reports
1997-004. IIAS, Kyoto,
[26] Kawato M: Trajectory formation in arm movements: minimization
principles and procedures. In Zelaznik HN (Ed.) Advances in Motor
Learning and Control. Human Kinetics Publishers, Chanpaign
Illinois,
[25] Kawato M: Bi-directional theory approach to integration. In Inui
T, McClelland J (Eds.) Attention and Performance, XVI. MIT
Press, Cambridge, Massachusetts,
[24] Kawato M: Learning internal models of the motor apparatus. In
Bloedel JR, Ebner TJ, Wise SP(Eds.) The Acquisition of Motor
Behavior in Vertebrates. MIT Press, Cambridge, Massachusetts,
[23] Kawato M: A bi-directional theory approach to prerational
intelligence. Proceedings of the Conference on Prerational
Intelligence in Robotics: From Sensorimotor Intelligence to Collective
Behavior. Universitat Bielefeld, Bielefeld,
[22] Kawato M: Celebellum and motor control. In Arbib M (Ed.) The
Handbook of Brain Theory and Neural Networks. MIT Press,
Cambridge, Massachusetts,
[21] Kawato M: Unidirectional versus bi-directional theory for
trajectory planning and control. In Hida T (Ed.) Mathematical
Approach To Fluctuations: Complexity and Nonlinearity 2.
World Scientific Ltd, Singapore,
[20] Uno Y, Kawato M: Optimal control of reaching movement. In Bennett
KMB, Castiello U (Ed.) Insights into the Reach to Grasp Movements.
Elsevier, Amsterdam,
[19] Wada Y, Koike Y, Bateson EV, Kawato M: A computational model for
cursive handwriting based on the minimization principle. In Hanson SJ
(Eds.) Advances in Neural Information Processing Systems 6.
Morgan Kaufmann, San Mateo,
[18] Hirayama M, Bateson EV, Kawato M: Inverse dynamics of speech motor
control. In Hanson SJ (Eds.) Advances in Neural Information
Processing Systems 6. Morgan Kaufmann, San Mateo,
[17] Kawato M, Gomi H: Feedback-error-learning model of cerebellar
motor control. In Mano N (Ed.) Role of the Cerebellum and Basal
Ganglia in Voluntary Movements. Elsevier Science Publishers,
North-Holland,
[16] Uno Y, Fukumura N, Suzuki R, Kawato M: Integration of visual and
somatosensory information for preshaping hand in grasping movements. In
Hanson SJ (Eds.) Advances in Neural Information Processing Systems
5. Morgan Kaufmann, San Mateo,
[15] Hirayama M, Bateson EV, Honda K, Koike Y, Kawato M:
Physiologically based speech synthesis. In Hanson SJ (Eds.) Advances
in Neural Information Processing Systems 5. Morgan
Kaufmann, San Mateo,
[14] Kawato M, Gomi H, Katayama M, Koike Y: Supervised learning for
coordinative motor control. In Baum EB (Eds.) Computational
Learning \& Cognition, SIAM Frontier Series. Society for
Industrial and Applied Mathematics, Philadelphia,
[13] Optimization and learning in neural networks for formation and
control of coordinated movement. In Meyer D, Kornblum S (Eds.) Attention
and Performance, XIV. MIT Press, Cambridge, Massachusetts,
[12] Gomi H, Kawato M: Recognition of manipulated objects by motor
learning. In Moody JE, Hanson SJ, Lippmann RP (Eds.) Advances in
Neural Information Processing Systems 4. Morgan Kaufmann,
San Mateo,
[11] Hirayama M, V-Bateson E, Kawato M, Jordan MI: Forward dynamics
modeling of speech motor control using physiological data. In Moody JE,
Hanson SJ, Lippmann RP (Eds.) Advances in Neural Information
Processing Systems 4. Morgan Kaufmann, San Mateo,
[10] Dornay M, Uno Y, Kawato M, Suzuki R: Simulation of optimal
movements using the minimum-muscle-tension-change model. In Moody JE,
Hanson SJ and Lippmann RP (Eds.) Advances in Neural Information
Processing Systems 4. Morgan Kaufmann, San Mateo,
[9] Katayama M, Kawato M: Learning trajectory and force control of
an artificial muscle arm by parallel-hierarchical neural network model.
In Lippmann RP, Moody JE, Touretzky DS (Eds.) Advances in Neural
Information Processing Systems 3. Morgan Kaufmann, San
Mateo,
[8] Kawato M: Feedback-error-learning
neural network for supervised
motor learning. In Eckmiller R (Ed.) Advanced Neural Computers.
Elsevier, North-Holland,
[7] Kawato M: Computational schemes and neural network models for
formation and control of multijoint arm trajectory. In Miller T, Sutton
RS, Werbos PJ (Eds.) Neural Networks for Control. MIT Press,
Cambridge, Massachusetts,
[6] Okamoto T, Kawato M, Inui T, Miyake S: Model based image
compression and adaptive data representation by interacting filter
banks. In Touretzky DS (Ed.) Advances in Neural Information
Processing Systems 2. Morgan Kaufmann, San Mateo,
[5] Kawato M, Isobe M, Suzuki R: Hierarchical learning of voluntary
movement by cerebellum and sensory association cortex. In Arbib MA,
Amari S (Eds.) Dynamic Interaction in Neural Networks: Models and
Data. Springer-Verlag, Berlin, Heidelberg, New York,
[4] Kawato M: Neural network models for formation and control of
multijoint arm trajectory. In Ito M (Ed.) Neural Programming.
Scientific Societies Press, Tokyo, Japan,
[3] Kawato M: Phase response curves of complex pacemaker. In Hiroshige
T, Honma K (Eds.) Circadian Clocks and Zeitgevers. Hokkaido
Univ Press, Sapporo,
[2] Tsukahara N, Kawato M: Dynamic and plastic properties of the brain
stem neuronal networks as the possible neuronal basis of learning and
memory. In Amari S,Arbib MA(Eds.) Lecture Notes in Biomathematics
45. Competition and Cooperation in Neural Nets.
Springer-Verlag, Berlin, Heidelberg, New York,
[1] Suzuki R, Kawato M, Tatsumi H: Mathematical and phenomenological
studies of biological rhythms. In Trappl R(Ed.) Cybernetics and
Systems Research. North-Holland Publishing Company,