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Computational approaches to sensorimotor transformations

Nature Neuroscience volume 3, pages 1192–1198 (2000)Cite this article

Abstract

Behaviors such as sensing an object and then moving your eyes or your hand toward it require that sensory information be used to help generate a motor command, a process known as a sensorimotor transformation. Here we review models of sensorimotor transformations that use a flexible intermediate representation that relies on basis functions. The use of basis functions as an intermediate is borrowed from the theory of nonlinear function approximation. We show that this approach provides a unifying insight into the neural basis of three crucial aspects of sensorimotor transformations, namely, computation, learning and short-term memory. This mathematical formalism is consistent with the responses of cortical neurons and provides a fresh perspective on the issue of frames of reference in spatial representations.

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Figure 1: Linear and nonlinear functions.
Figure 2: Basis function units.
Figure 3: Learning sensorimotor transformations in neural networks.
Figure 4: One-to-many sensorimotor transformations.
Figure 5: Short-term memory networks for sensorimotor transformations.

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Acknowledgements

A.P. is supported by a Young Investigator Award from ONR and fellowships from the Sloan Foundation and the McDonnell-Pew foundation. L.H.S. is supported by fellowships from the Sloan and Klingenstein foundations, and by NEI. We thank Daphne Bavelier and Suliann Ben Hamed for comments on earlier versions of this manuscript.

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Authors and Affiliations

  1. Department of Brain and Cognitive Sciences, University of Rochester, Rochester, 14627, New York, USA

    Alexandre Pouget

  2. Department of Anatomy and Neurobiology, Washington University, 660 S. Euclid Avenue, St. Louis, 63110, Missouri, USA

    Lawrence H. Snyder

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  1. Alexandre Pouget
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Correspondence to Alexandre Pouget.

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Pouget, A., Snyder, L. Computational approaches to sensorimotor transformations. Nat Neurosci 3 (Suppl 11), 1192–1198 (2000). https://doi.org/10.1038/81469

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