Learning and Modularity

No matter what the answer to the question posed in the preceding section turns out to be, it seems certain that the neural regulation of movement involves inverse dynamic and forward dynamic models, be they distributed or implemented in well-defined anatomical loci. Furthermore, it seems certain that these models are shaped by experience and by learning. This question has received considerable attention in recent years, and it has been shown that humans and nonhuman primates have a remarkable capacity to adapt to altered environments. For example, subjects can readily adapt to manipulations of visual input imposed by displacing prisms and they can also adapt to experimentally induced changes in kinematic or kinetic transformations. Specifically, subjects have been shown to gradually adapt when they are asked to make directional movements against a variety of force fields.

Adaptation is usually restricted to the particular movement on which subjects were trained or to movements that are very similar. This observation has led to the conclusion that movement regulation is achieved in a modular fashion. Taken to the extreme, this viewpoint holds that there is one internal model (with inverse and forward components) for each movement. Such an arrangement would make learning feasible because only the parameters of one module would need to be modified. There are several reasons to be skeptical of this hypothesis. Although it would simplify learning, the complexities are shifted to the process of selecting the appropriate module, interactions among them, and the amount of memory required to store them all. Furthermore, there does not seem to be any compelling evidence for such an arrangement.

Nevertheless, learning does appear to be modular. For example, subjects trained to make a movement in one direction in a novel force field will adapt so that movements in that direction and in neighboring directions are correct but movements in directions far from the one in which they train will be unaffected. Similarly, the vestibuloocular reflex can be adapted in a wide variety of ways, even to generate vertical eye movements in response to head rotations in the horizontal plane. However, this adaptation is frequency specific, being greatest at the frequency at which the subject oscillated.

The apparent modularity of learning is not inconsistent with a system in which information processing is widely distributed. The apparent contradiction can be resolved by considering the tuning characteristics of individual neurons. For example, as mentioned previously, motor cortical neurons are tuned to the direction of a movement. If one supposes that adaptation is restricted to circuits only involving neurons whose best direction is similar to the direction at which subjects are being adapted, then one can readily imagine a scenario of modular adaptation.

In conclusion, although the general form of the scheme by which the nervous system regulates and controls movement is known (Fig. 3), many of the details of the implementation of this scheme are not.

See Also the Following Articles

APRAXIA • BASAL GANGLIA • BIOFEEDBACK • CEREBRAL PALSY • EPILEPSY • HAND MOVEMENTS • MOTION PROCESSING

Suggested Reading

Buneo, C. A., Soechting, J. F., and Flanders, M. (1997). Postural dependence of muscle actions: Implications for neural control. J. Neurosci. 17, 2128-2142.

Flanders, M., and Herrmann, U. (1992). Two components of muscle activation: Scaling with the speed of arm movement. J. Neurophysiol. 67, 931-943.

Flanders, M., Helms Tillery, S. I., and Soechting, J. F. (1992). Early stages in a sensorimotor transformation. Behav. Brain Sci. 15, 309-362.

Georgopoulos, A. P. (1991). Higher order motor control. Annu. Rev. Neurosci. 14, 361-377.

Ghez, C., Gordon, J., Ghilardi, M. F., Christakos, C. N., and Cooper, S. E. (1990). Roles of proprioceptive input in the programming of arm trajectories. Cold Spring Harbor Symp. Quant. Biol. 55, 837-847.

Hasan, Z. (1991). Biomechanics and the study of multijoint movements. In Motor Control: Concepts and Issues (D. R. Humphrey and H.-J. Freund, Eds.), pp. 75-84. Wiley, Chiche-ster, UK.

Herrmann, U., and Flanders, M. (1998). Directional tuning of single motor units. J. Neurosci. 18, 8402-8416.

Kakei, S., Hoffman, D. S., and Strick, P. L. (1999). Muscle and movement representations in the primary motor cortex. Science 285, 2136-2139.

Kawato,M. (1999). Internal models for motor control and trajectory planning. Curr. Opin. Neurobiol. 9, 718-727.

Macpherson, J. M. (1991). How flexible are muscle synergies? In Motor Control: Concepts and Issues (D. R. Humphrey and H.-J. Freund, Eds.), pp. 33-48. Wiley, Chichester, UK.

Mussa-Ivaldi, F. A. (1999). Modular features of motor control and learning. Curr. Opin. Neurobiol. 9, 713-717.

Soechting, J. F. (1989). Elements of coordinated arm movements in three-dimensional space. In Perspectives on the Coordination of Movement (S. A. Wallace, Ed.), pp. 47-83. North-Holland, New York.

Soechting, J. F., and Flanders, M. (1992). Moving in three-dimensional space: frames of reference, vectors and coordinate systems. Annu. Rev. Neurosci. 15, 167-191.

Soechting, J. F., Buneo, C. A., Herrmann, U., and Flanders, M. (1995). Moving effortlessly in three dimensions: Does Donders' law apply to arm movement? J. Neurosci. 15, 6271-6280.

Wolpert, D. M., and Kawato, M. (1998). Multiple paired forward and inverse models for motor control. Neural Networks 11, 1317-1329.

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