Literature DB >> 15793578

Flexible strategies for sensory integration during motor planning.

Samuel J Sober1, Philip N Sabes.   

Abstract

When planning target-directed reaching movements, human subjects combine visual and proprioceptive feedback to form two estimates of the arm's position: one to plan the reach direction, and another to convert that direction into a motor command. These position estimates are based on the same sensory signals but rely on different combinations of visual and proprioceptive input, suggesting that the brain weights sensory inputs differently depending on the computation being performed. Here we show that the relative weighting of vision and proprioception depends both on the sensory modality of the target and on the information content of the visual feedback, and that these factors affect the two stages of planning independently. The observed diversity of weightings demonstrates the flexibility of sensory integration and suggests a unifying principle by which the brain chooses sensory inputs so as to minimize errors arising from the transformation of sensory signals between coordinate frames.

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Mesh:

Year:  2005        PMID: 15793578      PMCID: PMC2538489          DOI: 10.1038/nn1427

Source DB:  PubMed          Journal:  Nat Neurosci        ISSN: 1097-6256            Impact factor:   24.884


  29 in total

1.  The effect of visuomotor displacements on arm movement paths.

Authors:  S J Goodbody; D M Wolpert
Journal:  Exp Brain Res       Date:  1999-07       Impact factor: 1.972

2.  Where is my arm? The relative role of vision and proprioception in the neuronal representation of limb position.

Authors:  M S Graziano
Journal:  Proc Natl Acad Sci U S A       Date:  1999-08-31       Impact factor: 11.205

3.  Optimal integration of texture and motion cues to depth.

Authors:  R A Jacobs
Journal:  Vision Res       Date:  1999-10       Impact factor: 1.886

4.  Integration of proprioceptive and visual position-information: An experimentally supported model.

Authors:  R J van Beers; A C Sittig; J J Gon
Journal:  J Neurophysiol       Date:  1999-03       Impact factor: 2.714

5.  Coding the location of the arm by sight.

Authors:  M S Graziano; D F Cooke; C S Taylor
Journal:  Science       Date:  2000-12-01       Impact factor: 47.728

6.  Interlimb transfer of visuomotor rotations: independence of direction and final position information.

Authors:  Robert L Sainburg; Jinsung Wang
Journal:  Exp Brain Res       Date:  2002-06-26       Impact factor: 1.972

7.  Humans integrate visual and haptic information in a statistically optimal fashion.

Authors:  Marc O Ernst; Martin S Banks
Journal:  Nature       Date:  2002-01-24       Impact factor: 49.962

Review 8.  Multimodal representation of space in the posterior parietal cortex and its use in planning movements.

Authors:  R A Andersen; L H Snyder; D C Bradley; J Xing
Journal:  Annu Rev Neurosci       Date:  1997       Impact factor: 12.449

9.  Variables affecting the intermanual transfer and decay of prism adaptation.

Authors:  C S Choe; R B Welch
Journal:  J Exp Psychol       Date:  1974-06

10.  Analysis of pointing errors reveals properties of data representations and coordinate transformations within the central nervous system.

Authors:  J McIntyre; F Stratta; J Droulez; F Lacquaniti
Journal:  Neural Comput       Date:  2000-12       Impact factor: 2.026

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  161 in total

1.  Integration of target and hand position signals in the posterior parietal cortex: effects of workspace and hand vision.

Authors:  Christopher A Buneo; Richard A Andersen
Journal:  J Neurophysiol       Date:  2012-03-28       Impact factor: 2.714

Review 2.  Specialization of reach function in human posterior parietal cortex.

Authors:  Michael Vesia; J Douglas Crawford
Journal:  Exp Brain Res       Date:  2012-07-10       Impact factor: 1.972

3.  Integration of anatomical and external response mappings explains crossing effects in tactile localization: A probabilistic modeling approach.

Authors:  Stephanie Badde; Tobias Heed; Brigitte Röder
Journal:  Psychon Bull Rev       Date:  2016-04

4.  The generalization of visuomotor learning to untrained movements and movement sequences based on movement vector and goal location remapping.

Authors:  Howard G Wu; Maurice A Smith
Journal:  J Neurosci       Date:  2013-06-26       Impact factor: 6.167

5.  Neuronal activity in primary motor cortex differs when monkeys perform somatosensory and visually guided wrist movements.

Authors:  Yu Liu; John M Denton; Randall J Nelson
Journal:  Exp Brain Res       Date:  2005-08-03       Impact factor: 1.972

6.  Dissociable effects of the implicit and explicit memory systems on learning control of reaching.

Authors:  Eun Jung Hwang; Maurice A Smith; Reza Shadmehr
Journal:  Exp Brain Res       Date:  2006-02-28       Impact factor: 1.972

7.  The effect of target modality on visual and proprioceptive contributions to the control of movement distance.

Authors:  Fabrice R Sarlegna; Robert L Sainburg
Journal:  Exp Brain Res       Date:  2007-01       Impact factor: 1.972

8.  Did I do that? Detecting a perturbation to visual feedback in a reaching task.

Authors:  Elon Gaffin-Cahn; Todd E Hudson; Michael S Landy
Journal:  J Vis       Date:  2019-01-02       Impact factor: 2.240

9.  Using a compound gain field to compute a reach plan.

Authors:  Steve W C Chang; Charalampos Papadimitriou; Lawrence H Snyder
Journal:  Neuron       Date:  2009-12-10       Impact factor: 17.173

10.  Separation of visual and motor workspaces during targeted reaching results in limited generalization of visuomotor adaptation.

Authors:  Yuming Lei; Michelle J Johnson; Jinsung Wang
Journal:  Neurosci Lett       Date:  2013-03-07       Impact factor: 3.046

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