Advertisement

How Cerebral and Cerebellar Plasticities May Cooperate During Arm Reaching Movement Learning: A Neural Network Model

  • Alexander A. Frolov
  • Michel Dufossé
Chapter
  • 3.3k Downloads

Abstract

Learning process results from synaptic plasticities that occur in various sites of the brain. For arm reaching movement, three sites have been particularly studied: the cortico-cortical synapses of the cerebral cortex, the parallel fibre-Purkinje cell synapses of the cerebellar cortex and the cerebello-thalamo-cortical pathway. We intended to understand how these three adaptive processes cooperate for optimal performance. A neural network model was developed based on two main prerequisites: the columnar organisation of the cerebral cortex and the Marr-Albus-Ito theory of cerebellar learning. The adaptive rules incorporated in the model simulate the synaptic plasticities observed at the three sites. The model analytically demonstrates that 1) the adaptive processes that take place in different sites of the cerebral cortex and the cerebellum do not interfere but complement each other during learning of arm reaching movement, and 2) any linear combination of the cerebral motor commands may generate olivary signals able to drive the cerebellar learning processes.

Keywords

motor learning plasticity cerebellum inferior olive cerebro-cerebellar interaction 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Albus J.A. (1971) A theory of cerebellar function. Math. Biosci. 10: 25–61.CrossRefGoogle Scholar
  2. Arbib M.A., Érdi P., Szentagothai J. (1988) Neural organization. A Bradford book, Cambridge MA, MIT press.Google Scholar
  3. Baraduc P., Guigon E., Burnod Y. (2001) Recoding arm position to learn visuomotor transformations. Cerebral Cortex 11(10): 906–917.PubMedCrossRefGoogle Scholar
  4. Baranyi A., Feher O. (1978) Conditioned changes of synaptic transmission in the motor cortex of the cat. Exp. Brain Res. 33: 283–298.PubMedCrossRefGoogle Scholar
  5. Burnod Y. (1989) An adaptive neural networks: the cerebral cortex, Masson, Paris.Google Scholar
  6. Crépel F., Jaillard D. (1991) Pairing of pre-and postsynaptic activities in cerebellar Purkinje cells induce long-term changes in synaptic efficacy. J. Physiol. (London) 432: 123–141.PubMedGoogle Scholar
  7. Daniel H., Levenes C., Crépel F. (1998) Cellular mechanisms of cerebellar LTD. Trends in Neurosci. 21: 401–407.CrossRefGoogle Scholar
  8. De Zeeuw C.I., Simpson J.I., Hoogenraad C.C., Galjart N., Koekkoek S.K.E., Ruigrok T.J.H. (1998) Microcircuitry and function of the inferior olive. Trends in Neurosci. 21: 391–400.CrossRefGoogle Scholar
  9. Dufossé M., Ito M., Jastreboff P. J., Miyashita Y. (1978) A neuronal correlate in rabbit’s cerebellum to adaptive modification of the vestibulo-ocular reflex. Brain Res. 150: 611–616.PubMedCrossRefGoogle Scholar
  10. Dufossé M., Kaladjian A., Grandguillaume P. (1997) Origin of error signals during cerebellar learning of motor sequences. Behav. Brain Sci. 20(2): 249–250.CrossRefGoogle Scholar
  11. Feldman A.G. (1966) Functional tuning of the nervous structures during control of movement or maintenance of a steady posture: II. Controllable parameters of the muscle. Biophysics 11: 565–578.Google Scholar
  12. Flash T., Hogan N. (1985) The coordination of arm movements: An experimentally confirmed mathematical model. J. Neurosci. 5(7): 1688–1703.PubMedGoogle Scholar
  13. Frolov A.A., Dufossé M., Rizek S., Kaladjian A. (2000) On the possibility of linear modelling the human neuromuscular apparatus. Biol. Cybern. 82(6): 499–515.PubMedCrossRefGoogle Scholar
  14. Frolov A.A., Řízek S. (1995) Model of neurocontrol of redundant systems. J. Comput. Appl. Math. 63: 465–473.CrossRefGoogle Scholar
  15. Georgopoulos A.P., Caminiti R., Kalaska J.F. (1984) Static spatial effects in motor cortex and area 5: quantitative relations in a two-dimensional space. Exp. Brain Res. 54: 447–454.CrossRefGoogle Scholar
  16. Gilbert P.F.C., Thach W.T. (1977) Purkinje cell activity during motor learning. Brain Res. 128: 309–328.PubMedCrossRefGoogle Scholar
  17. Gribble P.L., Ostry D.J., Sanguineti V., Laboissiére R. (1998) Are complex control signals required for human arm movement? J Neurophysiol 79:1409–1424.PubMedGoogle Scholar
  18. Golub G.H., Van Loan C.F. (1996) Matrix compputations. The John Hopkins University Press. Baltimore and London.Google Scholar
  19. Inhoff A.W., Diener H.C., Rafal R.D., Ivry R. (1989) The role of cerebellar structures in the execution of serial movements. Brain 112: 565–581.PubMedGoogle Scholar
  20. Iriki A., Pavlides C., Keller A., Asanuma H. (1989) Longterm potentation in the motor cortex. Science 245: 1385–1387.PubMedGoogle Scholar
  21. Ito M. (1984) The cerebellum and neural control. Raven Press. New York.Google Scholar
  22. Ito M., Sakurai M., Tongroach P. (1982) Climbing fibre induce depression of both mossy fibre responsiveness and glutamate sensitivity of cerebellar Purkinje cells. J. Physiol. (Lond.) 324: 113–134.PubMedGoogle Scholar
  23. Jordan M.I., Rumelhart D.E. (1992) Forward models: supervised learning with a distal teacher. Cognitive Sci., 16: 307–354.CrossRefGoogle Scholar
  24. Kawato M. (1999) Internal models and trajectory planning. Curr. Op. Neurobiol. 9(6): 718–727.PubMedCrossRefGoogle Scholar
  25. Kawato M., Furukawa K., Suzuki R. (1987) A hierarchical neural-network model for control and learning of voluntary movement. Biol. Cybern. 57: 169–185.PubMedCrossRefGoogle Scholar
  26. Kawato M., Maeda Y., Uno Y., Suzuki R. (1990) Trajectory formation of arm movement by cascade neural network model based on minimum torque-change criterion. Biol. Cybern. 62: 275–288.PubMedCrossRefGoogle Scholar
  27. Kitazawa S., Kimura T., Yin P.B. (1988) Cerebellar complex spikes encode both destinations and errors in arm movements. Nature 392: 494–497.CrossRefGoogle Scholar
  28. Klein C., Huang C.H. (1983) Review of pseudo-inverse control for kinematically redundant manipulators. IEEE Trans. SMC-13: 245–250.Google Scholar
  29. Kuperstein M. (1988) Neural model for adaptive hand-eye coordination for single postures. Science, 239:1308–1311.PubMedGoogle Scholar
  30. Leiner H.C., Leiner A.L., Dow R.S. (1986) Does the cerebellum contribute to mental skills? Behav. Neurosci. 100: 443–454.PubMedCrossRefGoogle Scholar
  31. Mano N.L., Kanazawa I., Yamamoto K.I. (1986) Complex-spike activity of cellular Purkinje cells related to wrist tracking movement in monkey. J. Neurophysiol 56: 137–158PubMedGoogle Scholar
  32. Marr D. (1969) A theory of cerebellar cortex. J. Physiol. (London) 202: 437–470.PubMedGoogle Scholar
  33. Meftah E.M., Rispal-Padel L. (1992) Synaptic plasticity in the thalamo-cortical pathway as one of the neurophysiological correlates of forelimb flexion conditioning: electrophysiological investication in the cat. J. Neurophysiol. 68: 908–926.PubMedGoogle Scholar
  34. Nakano E., Imamizu H., Osu R., Uno Y., Gomi H., Yoshioka T., Kawato M. (1999) Quantitative examinations of internal representations for arm trajectory planning: minimum commanded torque change model. J. Neurophysiol. 81: 2140–2155.PubMedGoogle Scholar
  35. Oyama E., MacDorman K.F., Agah A., Maedo T., Tachi S. (2001) Coordination transformation learning of hand position feedback controller with time delay. Neurocomputing, 38–40: 1503–1509.CrossRefGoogle Scholar
  36. Pananceau M., Rispal-Padel L., Meftah E.M. (1996) Synaptic plasticity in the interpositorubral pathway functionally related to forelimb flexion movements. J. Neurophysiol. 75: 2542–2561.PubMedGoogle Scholar
  37. Saint-Cyr J.A., Courville J. (1980) Projections from the motor cortex, midbrain and vestibular nuclei to the inferior olive in tha cat: anatomical organization and functional correlates. In: The inferior olivary nucleus (pp 97–124). J. Courville, C. deMontigny and Y. Lamarre (Eds). Raven press, New York.Google Scholar
  38. Schweighofer N., Arbib M.A., Kawato M. (1998) Role of cerebellum in reaching movements in humans. II. A neural model of the intermediate cerebellum. Europ. J. Neurosci. 10: 95–105.CrossRefGoogle Scholar
  39. Uno Y., Kawato M., Suzuki R. (1989) Formation and control of optimal trajectory in human multijoint arm movement. Biol. Cybern. 61: 89–101.PubMedCrossRefGoogle Scholar
  40. Wolpert D.M., Miall R.C., Kawato M. (1998) Internal models in the cerebellum. Trends in Cogn. Sci. 2(9): 338–347.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, Inc. 2006

Authors and Affiliations

  • Alexander A. Frolov
    • 1
  • Michel Dufossé
    • 2
  1. 1.Institute of Higher Nervous Activities and NeurophysiologyRussian Academy of SciencesMoscowRussia
  2. 2.INSERM U483Université Pierre and Marie Curie, CP-23ParisFrance

Personalised recommendations