Computational principles of movement neuroscience - Nature Neuroscience Export

@article{citeulike:709263, abstract = {Unifying principles of movement have emerged from the computational study of motor control. We review several of these principles and show how they apply to processes such as motor planning, control, estimation, prediction and learning. Our goal is to demonstrate how specific models emerging from the computational approach provide a theoretical framework for movement neuroscience.}, author = {Wolpert, Daniel M. and Ghahramani, Zoubin}, citeulike-article-id = {709263}, citeulike-linkout-0 = {http://www.nature.com/neuro/journal/v3/n11s/full/nn1100_1212.html}, citeulike-linkout-1 = {http://dx.doi.org/10.1038/81497}, citeulike-linkout-2 = {http://www.nature.com/neuro/journal/v3/n11s/pdf/nn1100_1212.pdf}, doi = {10.1038/81497}, keywords = {computational, learning, optimal, prediction}, posted-at = {2006-06-23 19:26:16}, priority = {2}, title = {Computational principles of movement neuroscience - Nature Neuroscience}, url = {http://dx.doi.org/10.1038/81497} }

TY - JOUR ID - citeulike:709263 L3 - citeulike-article-id:709263 N2 - Unifying principles of movement have emerged from the computational study of motor control. We review several of these principles and show how they apply to processes such as motor planning, control, estimation, prediction and learning. Our goal is to demonstrate how specific models emerging from the computational approach provide a theoretical framework for movement neuroscience. TI - Computational principles of movement neuroscience - Nature Neuroscience KW - computational KW - learning KW - optimal KW - prediction AU - Wolpert, Daniel AU - Ghahramani, Zoubin UR - http://dx.doi.org/10.1038/81497 ER -