Computational approaches to sensorimotor transformations.

by: A Pouget, LH Snyder

Nat Neurosci, Vol. 3 Suppl (November 2000), pp. 1192-1198.

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摘要

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.

@article{citeulike:90456, 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.}, address = {Department of Brain and Cognitive Sciences, University of Rochester, New York 14627, USA. alex@bcs.rochester.edu}, author = {Pouget, A. and Snyder, L. H. }, citeulike-article-id = {90456}, doi = {10.1038/81469}, issn = {1097-6256}, journal = {Nat Neurosci}, month = {November}, pages = {1192--1198}, posted-at = {2005-12-12 20:41:06}, priority = {2}, title = {Computational approaches to sensorimotor transformations.}, url = {http://dx.doi.org/10.1038/81469}, volume = {3 Suppl}, year = {2000} }

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TY - JOUR ID - citeulike:90456 L3 - citeulike-article-id:90456 TI - Computational approaches to sensorimotor transformations. JF - Nat Neurosci VL - 3 Suppl SP - 1192 EP - 1198 AD - Department of Brain and Cognitive Sciences, University of Rochester, New York 14627, USA. alex@bcs.rochester.edu SN - 1097-6256 N2 - 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. AU - Pouget, A AU - Snyder, LH PY - 2000/11// UR - http://dx.doi.org/10.1038/81469 ER -

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