Computational aspects of motor control and motor learning by Jordan M.

By Jordan M.

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The use of control system analysis in the neurophysiology of eye movements. Annual Review of Neuroscience, 4, 463-503. Rosenblatt, F. 1962. Principles of neurodynamics. New York: Spartan. Rumelhart, D. , Hinton, G. , Williams, R. J. 1986. Learning internal representations by error propagation. In D. E. Rumelhart & J. L. , Parallel distributed processing: Volume 1, 318-363. Cambridge, MA: MIT Press. Saltzman, E. L. 1979. Levels of sensorimotor representation. Journal of Mathematical Psychology, 20, 91-163.

For example, the problem of learning by imitation can be treated as the problem of learning from an external reference model. The reference model provides only the desired behavior; it does not provide the control signals needed to perform the desired behavior. Conclusions If there is any theme that unites the various techniques that we have discussed, it is the important role of internal dynamical models in control systems. The two varieties of internal models|inverse models and forward models|play complementary roles in the implementation of sophisticated control strategies.

A general regression neural network. IEEE Transactions on Neural Networks, 2, 568-576. Turvey, M. , Shaw, R. , & Mace, W. 1978. Issues in the theory of action: Degrees of freedom, coordinative structures and coalitions. In J. , Attention and Performance, VII. Hillsdale, NJ: Erlbaum. 63 Wahba, G. 1990. Spline models for observational data. Philadelphia, PA: SIAM. Werbos, P. 1974.

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