Literature DB >> 12427820

Transfer of motor learning across arm configurations.

Nicole Malfait1, Douglas M Shiller, David J Ostry.   

Abstract

It has been suggested that the learning of new dynamics occurs in intrinsic coordinates. However, it has also been suggested that elements that encode hand velocity, and hence act in an extrinsic frame of reference, play a role in the acquisition of dynamics. To reconcile claims regarding the coordinate system involved in the representation of dynamics, we have used a procedure involving the transfer of force-field learning between two workspace locations. Subjects made point-to-point movements while holding a two-link manipulandum. Subjects were first trained to make movements in a single direction at the left of the workspace. They were then tested for transfer of learning at the right of the workspace. Two groups of subjects were defined. For the subjects in group j, movements at the left and right workspace locations were matched in terms of joint displacements. For the subjects in group h, movements in the two locations had the same hand displacements. Workspace locations were chosen such that for group j, the paths (for training and testing) that were identical in joint space were orthogonal in hand space. The subjects in group j showed good transfer between workspace locations, whereas the subjects in group h showed poor transfer. These results are in agreement with the idea that new dynamics are encoded in intrinsic coordinates and that this learning has a limited range of generalization across joint velocities.

Mesh:

Year:  2002        PMID: 12427820      PMCID: PMC6757833     

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  54 in total

1.  Shoulder and elbow joint power differ as a general feature of vertical arm movements.

Authors:  J C Galloway; A Bhat; J C Heathcock; K Manal
Journal:  Exp Brain Res       Date:  2004-06-26       Impact factor: 1.972

2.  Generalization properties of a "saccadic-like" hand-reaching adaptation along a single degree of freedom.

Authors:  Damien Laurent; Olivier Sillan; Claude Prablanc
Journal:  Exp Brain Res       Date:  2011-12-06       Impact factor: 1.972

3.  Generalization of dynamics learning across changes in movement amplitude.

Authors:  Andrew A G Mattar; David J Ostry
Journal:  J Neurophysiol       Date:  2010-05-12       Impact factor: 2.714

4.  Linear hypergeneralization of learned dynamics across movement speeds reveals anisotropic, gain-encoding primitives for motor adaptation.

Authors:  Wilsaan M Joiner; Obafunso Ajayi; Gary C Sing; Maurice A Smith
Journal:  J Neurophysiol       Date:  2010-09-29       Impact factor: 2.714

5.  Generalization as a behavioral window to the neural mechanisms of learning internal models.

Authors:  Reza Shadmehr
Journal:  Hum Mov Sci       Date:  2004-11       Impact factor: 2.161

6.  Adaptation to a novel multi-force environment.

Authors:  Isaac Kurtzer; Paul A DiZio; James R Lackner
Journal:  Exp Brain Res       Date:  2005-04-16       Impact factor: 1.972

Review 7.  The internal model and the leading joint hypothesis: implications for control of multi-joint movements.

Authors:  Natalia Dounskaia
Journal:  Exp Brain Res       Date:  2005-08-13       Impact factor: 1.972

Review 8.  Internal models of limb dynamics and the encoding of limb state.

Authors:  Eun Jung Hwang; Reza Shadmehr
Journal:  J Neural Eng       Date:  2005-08-31       Impact factor: 5.379

9.  Transfer and durability of acquired patterns of human arm stiffness.

Authors:  Mohammad Darainy; Nicole Malfait; Farzad Towhidkhah; David J Ostry
Journal:  Exp Brain Res       Date:  2005-11-19       Impact factor: 1.972

10.  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

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