2000
DOI: 10.1038/81497
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Computational principles of movement neuroscience

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.

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Cited by 1,739 publications
(1,188 citation statements)
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References 48 publications
(36 reference statements)
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“…On this view the sense of agency is generated by processes dedicated to the control of voluntary action. Optimal motor control and learning require predictions of both the future states of the motor system and the sensory consequences of movement (Wolpert & Ghahramani, 2000). These predictions are derived from internal forward models, of which there are two classes: forward dynamic and forward sensory.…”
Section: Prediction and Retrospective Inferencementioning
confidence: 99%
“…On this view the sense of agency is generated by processes dedicated to the control of voluntary action. Optimal motor control and learning require predictions of both the future states of the motor system and the sensory consequences of movement (Wolpert & Ghahramani, 2000). These predictions are derived from internal forward models, of which there are two classes: forward dynamic and forward sensory.…”
Section: Prediction and Retrospective Inferencementioning
confidence: 99%
“…Neuroscience research has shown that our brains use all available sensory feedback, including sound, to keep track of the changing structure and position of the body in space (Botvinick & Cohen, 1998;De Vignemont, Ehrsson, & Haggard, 2005) and to adjust actions (Wolpert & Ghahramani, 2000). For instance, the sound of tapping with an object on one's hand provides information about hand position, arm length (Tajadura-Jiménez et al, 2012), and force applied (Tajadura-Jiménez, Furfaro, BianchiBerthouze, & Bevilacqua, in press), or the timing of steps when walking (Menzer et al, 2010).…”
Section: Sonification For Representing Understanding and Motivatingmentioning
confidence: 99%
“…These feed-forward predictions are thought to update multi-sensory estimates of the state of the body (e.g. posture of the upper limbs), represented in the parietal cortex (particularly the SPL) [13,15]. An interesting possibility is that these same predictive mechanisms might play a role in forecasting the longrange consequences of response alternatives [5,16,17].…”
Section: Introductionmentioning
confidence: 99%
“…An emerging view is that the cerebellum supports forward internal models that predict the likely sensory consequences of a motor command slightly in advance of the actual sensory feedback that accompanies movement [13,14]. These feed-forward predictions are thought to update multi-sensory estimates of the state of the body (e.g.…”
Section: Introductionmentioning
confidence: 99%