Literature DB >> 24920632

Learning redundant motor tasks with and without overlapping dimensions: facilitation and interference effects.

Rajiv Ranganathan1, Jon Wieser2, Kristine M Mosier3, Ferdinando A Mussa-Ivaldi4, Robert A Scheidt5.   

Abstract

Prior learning of a motor skill creates motor memories that can facilitate or interfere with learning of new, but related, motor skills. One hypothesis of motor learning posits that for a sensorimotor task with redundant degrees of freedom, the nervous system learns the geometric structure of the task and improves performance by selectively operating within that task space. We tested this hypothesis by examining if transfer of learning between two tasks depends on shared dimensionality between their respective task spaces. Human participants wore a data glove and learned to manipulate a computer cursor by moving their fingers. Separate groups of participants learned two tasks: a prior task that was unique to each group and a criterion task that was common to all groups. We manipulated the mapping between finger motions and cursor positions in the prior task to define task spaces that either shared or did not share the task space dimensions (x-y axes) of the criterion task. We found that if the prior task shared task dimensions with the criterion task, there was an initial facilitation in criterion task performance. However, if the prior task did not share task dimensions with the criterion task, there was prolonged interference in learning the criterion task due to participants finding inefficient task solutions. These results show that the nervous system learns the task space through practice, and that the degree of shared task space dimensionality influences the extent to which prior experience transfers to subsequent learning of related motor skills.
Copyright © 2014 the authors 0270-6474/14/348289-11$15.00/0.

Entities:  

Keywords:  body-machine interface; coordination; finger; structure learning; synergies

Mesh:

Year:  2014        PMID: 24920632      PMCID: PMC4051979          DOI: 10.1523/JNEUROSCI.4455-13.2014

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


  25 in total

1.  Independent learning of internal models for kinematic and dynamic control of reaching.

Authors:  J W Krakauer; M F Ghilardi; C Ghez
Journal:  Nat Neurosci       Date:  1999-11       Impact factor: 24.884

2.  The uncontrolled manifold concept: identifying control variables for a functional task.

Authors:  J P Scholz; G Schöner
Journal:  Exp Brain Res       Date:  1999-06       Impact factor: 1.972

Review 3.  Motor control strategies revealed in the structure of motor variability.

Authors:  Mark L Latash; John P Scholz; Gregor Schöner
Journal:  Exerc Sport Sci Rev       Date:  2002-01       Impact factor: 6.230

Review 4.  Optimality principles in sensorimotor control.

Authors:  Emanuel Todorov
Journal:  Nat Neurosci       Date:  2004-09       Impact factor: 24.884

5.  Remapping hand movements in a novel geometrical environment.

Authors:  Kristine M Mosier; Robert A Scheidt; Santiago Acosta; Ferdinando A Mussa-Ivaldi
Journal:  J Neurophysiol       Date:  2005-09-07       Impact factor: 2.714

6.  Evolution of behavioral attractors with learning: nonequilibrium phase transitions.

Authors:  P G Zanone; J A Kelso
Journal:  J Exp Psychol Hum Percept Perform       Date:  1992-05       Impact factor: 3.332

7.  Facilitation and interference in performance on the modified Mashburn apparatus: I. The effects of varying the amount of original learning.

Authors:  D LEWIS; D E McALLISTER; J A ADAMS
Journal:  J Exp Psychol       Date:  1951-04

8.  Differences in adaptation rates after virtual surgeries provide direct evidence for modularity.

Authors:  Denise J Berger; Reinhard Gentner; Timothy Edmunds; Dinesh K Pai; Andrea d'Avella
Journal:  J Neurosci       Date:  2013-07-24       Impact factor: 6.167

9.  Consolidation in human motor memory.

Authors:  T Brashers-Krug; R Shadmehr; E Bizzi
Journal:  Nature       Date:  1996-07-18       Impact factor: 49.962

10.  Dissociable stages of human memory consolidation and reconsolidation.

Authors:  Matthew P Walker; Tiffany Brakefield; J Allan Hobson; Robert Stickgold
Journal:  Nature       Date:  2003-10-09       Impact factor: 49.962

View more
  18 in total

1.  Learning new gait patterns: Exploratory muscle activity during motor learning is not predicted by motor modules.

Authors:  Rajiv Ranganathan; Chandramouli Krishnan; Yasin Y Dhaher; William Z Rymer
Journal:  J Biomech       Date:  2016-02-10       Impact factor: 2.712

2.  Structural constraints on learning in the neural network.

Authors:  Clarisa A Martinez; Chunji Wang
Journal:  J Neurophysiol       Date:  2015-03-25       Impact factor: 2.714

Review 3.  Computations in Sensorimotor Learning.

Authors:  Daniel M Wolpert
Journal:  Cold Spring Harb Symp Quant Biol       Date:  2015-04-07

4.  A single exercise bout and locomotor learning after stroke: physiological, behavioural, and computational outcomes.

Authors:  Charalambos C Charalambous; Carolina C Alcantara; Margaret A French; Xin Li; Kathleen S Matt; Hyosub E Kim; Susanne M Morton; Darcy S Reisman
Journal:  J Physiol       Date:  2018-04-17       Impact factor: 5.182

Review 5.  Brain-computer interfaces for dissecting cognitive processes underlying sensorimotor control.

Authors:  Matthew D Golub; Steven M Chase; Aaron P Batista; Byron M Yu
Journal:  Curr Opin Neurobiol       Date:  2016-01-19       Impact factor: 6.627

6.  Development of an EMG-Controlled Serious Game for Rehabilitation.

Authors:  Mohammad Ghassemi; Kristen Triandafilou; Alex Barry; Mary Ellen Stoykov; Elliot Roth; Ferdinando A Mussa-Ivaldi; Derek G Kamper; Rajiv Ranganathan
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2019-01-21       Impact factor: 3.802

7.  Sequential motor learning transfers from real to virtual environment.

Authors:  Yuhi Takeo; Masayuki Hara; Yuna Shirakawa; Takashi Ikeda; Hisato Sugata
Journal:  J Neuroeng Rehabil       Date:  2021-06-30       Impact factor: 4.262

8.  Neural Population Dynamics Underlying Motor Learning Transfer.

Authors:  Saurabh Vyas; Nir Even-Chen; Sergey D Stavisky; Stephen I Ryu; Paul Nuyujukian; Krishna V Shenoy
Journal:  Neuron       Date:  2018-02-15       Impact factor: 17.173

9.  Neural constraints on learning.

Authors:  Patrick T Sadtler; Kristin M Quick; Matthew D Golub; Steven M Chase; Stephen I Ryu; Elizabeth C Tyler-Kabara; Byron M Yu; Aaron P Batista
Journal:  Nature       Date:  2014-08-28       Impact factor: 49.962

10.  Structure Learning in Bayesian Sensorimotor Integration.

Authors:  Tim Genewein; Eduard Hez; Zeynab Razzaghpanah; Daniel A Braun
Journal:  PLoS Comput Biol       Date:  2015-08-25       Impact factor: 4.475

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.