Trial-to-trial dynamics and learning in generalized, redundant reaching tasks

Trial-to-trial variability in human movement is often overlooked and averaged out, but useful information can be gleaned on the brain’s control of variability. A task can be defined by a function specifying a solution manifold along which all task variable combinations will lead to goal success – th...

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Main Author: Smallwood, Rachel Fay
Format: Others
Language:English
Published: 2010
Subjects:
Online Access:http://hdl.handle.net/2152/ETD-UT-2010-08-1935
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spelling ndltd-UTEXAS-oai-repositories.lib.utexas.edu-2152-ETD-UT-2010-08-19352015-09-20T16:56:26ZTrial-to-trial dynamics and learning in generalized, redundant reaching tasksSmallwood, Rachel FayLearningMotor controlReachingVariabilityGoal-Equivalent ManifoldTrial-to-trial dynamicsMovementRedundancyTrial-to-trial variability in human movement is often overlooked and averaged out, but useful information can be gleaned on the brain’s control of variability. A task can be defined by a function specifying a solution manifold along which all task variable combinations will lead to goal success – the Goal-Equivalent Manifold (GEM). We selected a reaching task with variables reach Distance (D) and reach Time (T). Two GEMs were selected: a constant D/T and constant D×T. Subjects had no knowledge of the goal prior to the experiments and were instructed only to minimize error. Subjects learned the generalized tasks by reducing errors and consolidated learning from one day to the next, generalized learning from the D×T to the D/T GEM, and had interference of learning from the D/T to the D×T GEM. Variability was structured along each GEM significantly more than perpendicular to it. Deviations resulting in errors were corrected significantly more quickly than any other deviation. Our results indicate that subjects can learn generalized reaching tasks, and the brain exploits redundancy in those tasks.text2010-12-17T20:21:09Z2010-12-17T20:21:15Z2010-12-17T20:21:09Z2010-12-17T20:21:15Z2010-082010-12-17August 20102010-12-17T20:21:15Zthesisapplication/pdfhttp://hdl.handle.net/2152/ETD-UT-2010-08-1935eng
collection NDLTD
language English
format Others
sources NDLTD
topic Learning
Motor control
Reaching
Variability
Goal-Equivalent Manifold
Trial-to-trial dynamics
Movement
Redundancy
spellingShingle Learning
Motor control
Reaching
Variability
Goal-Equivalent Manifold
Trial-to-trial dynamics
Movement
Redundancy
Smallwood, Rachel Fay
Trial-to-trial dynamics and learning in generalized, redundant reaching tasks
description Trial-to-trial variability in human movement is often overlooked and averaged out, but useful information can be gleaned on the brain’s control of variability. A task can be defined by a function specifying a solution manifold along which all task variable combinations will lead to goal success – the Goal-Equivalent Manifold (GEM). We selected a reaching task with variables reach Distance (D) and reach Time (T). Two GEMs were selected: a constant D/T and constant D×T. Subjects had no knowledge of the goal prior to the experiments and were instructed only to minimize error. Subjects learned the generalized tasks by reducing errors and consolidated learning from one day to the next, generalized learning from the D×T to the D/T GEM, and had interference of learning from the D/T to the D×T GEM. Variability was structured along each GEM significantly more than perpendicular to it. Deviations resulting in errors were corrected significantly more quickly than any other deviation. Our results indicate that subjects can learn generalized reaching tasks, and the brain exploits redundancy in those tasks. === text
author Smallwood, Rachel Fay
author_facet Smallwood, Rachel Fay
author_sort Smallwood, Rachel Fay
title Trial-to-trial dynamics and learning in generalized, redundant reaching tasks
title_short Trial-to-trial dynamics and learning in generalized, redundant reaching tasks
title_full Trial-to-trial dynamics and learning in generalized, redundant reaching tasks
title_fullStr Trial-to-trial dynamics and learning in generalized, redundant reaching tasks
title_full_unstemmed Trial-to-trial dynamics and learning in generalized, redundant reaching tasks
title_sort trial-to-trial dynamics and learning in generalized, redundant reaching tasks
publishDate 2010
url http://hdl.handle.net/2152/ETD-UT-2010-08-1935
work_keys_str_mv AT smallwoodrachelfay trialtotrialdynamicsandlearningingeneralizedredundantreachingtasks
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