Abstract
Theories of motor control postulate that the brain uses internal models of the body to control movements accurately. Internal models are neural representations of how, for instance, the arm would respond to a neural command, given its current position and velocity1,2,3,4,5,6. Previous studies have shown that the cerebellar cortex can acquire internal models through motor learning7,8,9,10,11. Because the human cerebellum is involved in higher cognitive function12,13,14,15 as well as in motor control, we propose a coherent computational theory in which the phylogenetically newer part of the cerebellum similarly acquires internal models of objects in the external world. While human subjects learned to use a new tool (a computer mouse with a novel rotational transformation), cerebellar activity was measured by functional magnetic resonance imaging. As predicted by our theory, two types of activity were observed. One was spread over wide areas of the cerebellum and was precisely proportional to the error signal that guides the acquisition of internal models during learning. The other was confined to the area near the posterior superior fissure and remained even after learning, when the error levels had been equalized, thus probably reflecting an acquired internal model of the new tool.
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References
Kawato, M., Furukawa, K. & Suzuki, R. A hierarchical neural-network model for control and learning of voluntary movement. Biol. Cybern. 57, 169–185 (1987).
Lackner, J. R. & Dizio, P. Rapid adaptation to Coriolis force perturbations of arm trajectory. J. Neurophysiol. 72, 299–313 (1994).
Shadmehr, R. & Mussa-Ivaldi, F. A. Adaptive representation of dynamics during learning of a motor task. J. Neurosci. 14, 3208–3224 (1994).
Wolpert, D. M., Ghahramani, Z. & Jordan, M. I. An internal model for sensorimotor integration. Science 269, 1880–1882 ( 1995).
Imamizu, H., Uno, Y. & Kawato, M. Internal representations of the motor apparatus: implications from generalization in visuomotor learning. J. Exp. Psychol. Hum. Percept. Perform. 21, 1174–1198 ( 1995).
Gomi, H. & Kawato, M. Equilibrium-point control hypothesis examined by measured arm stiffness during multijoint movement. Science 272, 117–120 ( 1996).
Kawato, M. & Gomi, H. A computational model of four regions of the cerebellum based on feedback-error learning. Biol. Cybern. 68, 95–103 ( 1992).
Shidara, M., Kawano, K., Gomi, H. & Kawato, M. Inverse-dynamics model of eye movement control by Purkinje cells in the cerebellum. Nature 365, 50–52 ( 1993).
Gomi, H. et al. Temporal firing patterns of Purkinje cells in the cerebellar ventral paraflocculus during ocular following responses in monkeys I. Simple spikes. J. Neurophysiol. 80, 818– 831 (1998).
Kobayashi, Y. et al. Temporal firing patterns of Purkinje cells in the cerebellar ventral paraflocculus during ocular following responses in monkeys II. Complex spikes. J. Neurophysiol. 80, 832– 848 (1998).
Kitazawa, S., Kimura, T. & Yin, P. B. Cerebellar complex spikes encode both destinations and errors in arm movements. Nature 392, 494 –497 (1998).
Raichle, M. E. et al. Practice-related changes in human brain functional anatomy during nonmotor learning. Cereb. Cortex 4, 8–26 (1994).
Kim, S. G., Ugurbil, K. & Strick, P. L. Activation of a cerebellar output nucleus during cognitive processing. Science 265, 949– 951 (1994).
Allen, G., Buxton, R. B., Wong, E. C. & Courchesne, E. Attentional activation of the cerebellum independent of motor involvement. Science 275, 1940–1943 ( 1997).
Thach, W. T. On the specific role of the cerebellum in motor learning and cognition: Clues from PET activation and lesion studies in man. Behav. Brain Sci. 19, 411–431 ( 1996).
Friston, K. J., Frith, C. D., Passingham, R. E., Liddle, P. F. & Frackowiak, R. S. Motor practice and neurophysiological adaptation in the cerebellum: a positron tomography study. Proc. R. Soc. Lond. B Biol. Sci. 248, 223– 228 (1992).
Grafton, S. T., Woods, R. P. & Tyszka, M. Functional imaging of procedural motor learning: relating cerebral blood flow with individual subject performance. Hum. Brain Mapp. 1, 221–234 ( 1994).
Seitz, R. J. et al. Successive roles of the cerebellum and premotor cortices in trajectorial learning. NeuroReport 5, 2541 –2544 (1994).
Flament, D., Ellermann, J. M., Kim, S. G., Ugurbil, K. & Ebner, T. J. Functional magnetic resonance imaging of cerebellar activation during the learning of a visuomotor dissociation task. Hum. Brain Mapp. 4, 210– 226 (1996).
Marr, D. A theory of cerebellar cortex. J. Physiol. (Lond.) 202 , 437–470 (1969).
Albus, J. S. A theory of cerebellar function. Math. Biosci. 10, 25–61 (1971).
Ito, M. Cerebellar control of the vestibulo-ocular reflex—around the flocculus hypothesis. Annu. Rev. Neurosci. 5, 275– 296 (1982).
Wolpert, D. M. & Kawato, M. Multiple paired forward and inverse models for motor control. Neural Netw. 11, 1317–1329 (1998).
Sasaki, K. et al. Mossy fibre and climbing fibre responses produced in the cerebellar cortex by stimulation of the cerebral cortex in monkeys. Exp. Brain Res. 29, 419–428 ( 1977).
Roland, P. E., Eriksson, L., Widen, L. & Stone-Elander, S. Changes in regional cerebral oxidative metabolism induced by tactile learning and recognition in man. Eur. J. Neurosci. 1, 3– 18 (1988).
Oldfield, R. C. The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia 9, 97–113 (1971).
Woods, R. P., Grafton, S. T., Holmes, C. J., Cherry, S. R. & Mazziotta, J. C. Automated image registration: I. General methods and intrasubject, intramodality validation. J. Comput. Assist. Tomogr. 22, 139– 152 (1998).
Bandettini, P. A., Jesmanowicz, A., Wong, E. C. & Hyde, J. S. Processing strategies for time-course data sets in functional MRI of the human brain. Magn. Reson. Med. 30, 161– 173 (1993).
Tamada, T., Miyauchi, S., Imamizu, H., Yoshioka, T. & Kawato, M. Cerebro-cerebellar functional connectivity revealed by the laterality index in tool-use learning. NeuroReport 10, 325–331 (1999).
Worsley, K. J. & Friston, K. J. Analysis of fMRI time-series revisited—again. Neuroimage 2, 173–181 (1995).
Acknowledgements
We thank D. Wolpert, C. Miall, M. Honda, K. Sakai and S. Kitazawa for comments on the manuscript. Supported by Human Frontier Science Projects, and Special Coordination Fund to Brain Science.
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Imamizu, H., Miyauchi, S., Tamada, T. et al. Human cerebellar activity reflecting an acquired internal model of a new tool. Nature 403, 192–195 (2000). https://doi.org/10.1038/35003194
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DOI: https://doi.org/10.1038/35003194
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