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Motor Control and LearningHumans adapt to multiple environments and skillfully control our movements and tools. Our aim is to understand control and learning mechanisms of our motor system, and elucidate their neural substrates. We hope to develop new rehabilitation techniques based on the acquired results. Research Topics1. Impedance Control (How to deal with instability?)To manipulate objects or to use tools, we must compensate for forces arising from interaction with the physical environments. However, many common tasks are intrinsically unstable (using a screwdriver, carving on a convex surface, cutting round fruits with a knife etc). One way to deal with instability is controlling the mechanical impedance. We have developed a method to measure human arm impedance during movements and demonstrated that humans learn to stabilize unstable dynamics using the skilful and energy-efficient strategy of selective control of impedance geometry.
 Stiffness geometry (a red ellipse) expanded in the direction of instability (blue arrows), measured using PFM (parallel-link direct-drive air and magnet floating manipulandum) 2. Learning Internal Models (How to adapt to novel environments?)We investigate how humans adapt to novel environments by generating novel force fields using a PFM (see above), single joint manipulandum, and functional electric stimulation (FES) etc. 3. Neural Substrate of Motor Control and LearningWe are also interested in the neural substrate of motor control
and learning, especially the loci of internal models and impedance
control. We are now developing a magnet - free haptic interface that
can be used in the fMRI. People Involved in the above Topics- Rieko Osu Collaborators PublicationsOsu R, Kamimura N, Iwasaki H, Nakano E, Harris CM, Wada Y, Kawato M: Optimal impedance control for task achievement in the presence of signal-dependent noise. Journal of Neurophysiology (in press) Osu R, Hirai S, Yoshioka T, Kawato M: Random presentation enables subjects to adapt to two opposing forces on the hand. Nature Neuroscience, 7, 111-112 (2004) Franklin DW, Osu R, Burdet E, Kawato M, Milner TE: Adaptation to stable and unstable environments achieved by combined impedance control and inverse dynamics model. Journal of Neurophysiology, 90, 3270-3282 (2003) Osu R, Burdet E, Franklin DW, Milner TE, Kawato M: Different mechanisms involved in adaptation to stable and unstable dynamics. Journal of Neurophysiology, 90, 3255-3269 (2003) Franklin DW, Burdet E, Osu R, Kawato M, Milner TE: Functional significance of stiffness in adaptation of multijoint arm movements to stable and unstable dynamics. Experimental Brain Research , 151, 145-157 (2003) Wada Y, Kawabata Y, Kotosaka S, Yamamoto S, Kitazawa S, Kawato M: Acquisition and contextual switching of multiple internal models for different viscous force fields. Neuroscience Research, 46, 319-331 (2003) Osu R, Franklin DW, Kato H, Gomi H, Domen K, Yoshioka T, Kawato M: Short- and long-term changes in joint co-contraction associated with motor learning as revealed from surface EMG. Journal of Neurophysiology, 88, 991-1004 (2002) Servos P, Osu R, Santi A, Kawato M: The neural substrates of biological motion perception: an fMRI study. Cerebral Cortex, 12, 772-782 (2002) Yoshida N, Domen K, Koike Y, Kawato M: A method for estimating torque-vector directions of shoulder muscles using surface EMGs. Biological Cybernetics, 86 167-177 (2002). Burdet E, Osu R, Franklin D, Milner T, Kawato M: The central nervous system stabilizes unstable dynamics by learning optimal impedance. Nature, 414 446-449 (2001). Wada Y, Kaneko Y, Nakano E, Osu R, Kawato M: Quantitative examinations for multi joint arm trajectory planning -- using a robust calculation algorithm of the minimum commanded torque change trajectory --. Neural Networks, 14 381-393 (2001). Burdet E, Osu R, Franklin D, Milner TE, Kawato M: A method for
measuring endpoint stiffness during multi-joint arm movements. Journal
of Biomechanics, 33, 1705-1709 (2000). Conference abstractsBurdet, E., Tee, K.P., Chew, C.M., Franklin, D.W., Osu, R., Kawato, M., Milner, T.E. (2001) Stability and learning in human arm movements, International Conference on Computational Intelligence, Robotics and Autonomous Systems, Singapore. Wada, Y., Kaneko, Y., Nakano, E., Osu, R., Kawato, M. (2001) Multi joint armtrajectory formation based on the minimization principle using the Euler-Poisson equation, International Conference on Artificial Neural Networks 2001 (ICANN 2001), Vienna, Austria. Schaal, S., Sternad, D., Osu, R.,, Kawato, M. (2001) Rhythmic Movement Is Not Discrete Society for Neuroscience 31st Annual Meeting. Osu, R., Kawato, M. (2001) A new method to estimate multi-joint stiffness from EMG through torque estimation in isometric condition, The First International Symposium on Measurement, Analysis and Modeling of Human Functions, Sapporo, Japan. Franklin, D., Osu, R., Burdet, E., Kawato, M., Milner, T.E. (2000), Learning Impedance to Stabilize Unstable Dynamics: iii) EMG Correlates, Abstract of the Society for Neuroscience 30th Annual Meeting, New Orleans, Louisiana, USA. Burdet, E., Osu, R., Franklin, D., Milner, T.E., Kawato, M. (2000) Learning Impedance to Stabilize Unstable Dynamics: ii) Direct Evidence in Multijoint Movements, Abstract of the Society for Neuroscience 30th Annual Meeting, New Orleans, Louisiana, USA. Osu, R., Burdet, E., Franklin, D., Milner, T.E., Kawato, M. (2000) Learning Impedance to Stabilize Unstable Dynamics: i) Contrast with Learning an Internal Dynamic Model, Abstract of the Society for Neuroscience 30th Annual Meeting, New Orleans, Louisiana, USA. Servos, P., Osu, R., Kawato, M. (2000) The Neural Substrates of
Biological Motion Perception; An fMRI study, Canadian Society for
Brain, Behavior, and Cognitive Science, Cambridge, England. |