Literature DB >> 28143961

Motor Learning Enhances Use-Dependent Plasticity.

Firas Mawase1, Shintaro Uehara1,2, Amy J Bastian3,4, Pablo Celnik5,3,6.   

Abstract

Motor behaviors are shaped not only by current sensory signals but also by the history of recent experiences. For instance, repeated movements toward a particular target bias the subsequent movements toward that target direction. This process, called use-dependent plasticity (UDP), is considered a basic and goal-independent way of forming motor memories. Most studies consider movement history as the critical component that leads to UDP (Classen et al., 1998; Verstynen and Sabes, 2011). However, the effects of learning (i.e., improved performance) on UDP during movement repetition have not been investigated. Here, we used transcranial magnetic stimulation in two experiments to assess plasticity changes occurring in the primary motor cortex after individuals repeated reinforced and nonreinforced actions. The first experiment assessed whether learning a skill task modulates UDP. We found that a group that successfully learned the skill task showed greater UDP than a group that did not accumulate learning, but made comparable repeated actions. The second experiment aimed to understand the role of reinforcement learning in UDP while controlling for reward magnitude and action kinematics. We found that providing subjects with a binary reward without visual feedback of the cursor led to increased UDP effects. Subjects in the group that received comparable reward not associated with their actions maintained the previously induced UDP. Our findings illustrate how reinforcing consistent actions strengthens use-dependent memories and provide insight into operant mechanisms that modulate plastic changes in the motor cortex.SIGNIFICANCE STATEMENT Performing consistent motor actions induces use-dependent plastic changes in the motor cortex. This plasticity reflects one of the basic forms of human motor learning. Past studies assumed that this form of learning is exclusively affected by repetition of actions. However, here we showed that success-based reinforcement signals could affect the human use-dependent plasticity (UDP) process. Our results indicate that learning augments and interacts with UDP. This effect is important to the understanding of the interplay between the different forms of motor learning and suggests that reinforcement is not only important to learning new behaviors, but can shape our subsequent behavior via its interaction with UDP.
Copyright © 2017 the authors 0270-6474/17/372673-13$15.00/0.

Entities:  

Keywords:  TMS; noninvasive brain stimulation; reinforcement; skill learning; use-dependent learning

Mesh:

Year:  2017        PMID: 28143961      PMCID: PMC5354321          DOI: 10.1523/JNEUROSCI.3303-16.2017

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


  49 in total

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2.  Noninvasive cortical stimulation enhances motor skill acquisition over multiple days through an effect on consolidation.

Authors:  Janine Reis; Heidi M Schambra; Leonardo G Cohen; Ethan R Buch; Brita Fritsch; Eric Zarahn; Pablo A Celnik; John W Krakauer
Journal:  Proc Natl Acad Sci U S A       Date:  2009-01-21       Impact factor: 11.205

3.  Early neural responses to strength training.

Authors:  Victor S Selvanayagam; Stephan Riek; Timothy J Carroll
Journal:  J Appl Physiol (1985)       Date:  2011-05-05

4.  Probing for hemispheric specialization for motor skill learning: a transcranial direct current stimulation study.

Authors:  Heidi M Schambra; Mitsunari Abe; David A Luckenbaugh; Janine Reis; John W Krakauer; Leonardo G Cohen
Journal:  J Neurophysiol       Date:  2011-05-25       Impact factor: 2.714

5.  Rapid plasticity of human cortical movement representation induced by practice.

Authors:  J Classen; J Liepert; S P Wise; M Hallett; L G Cohen
Journal:  J Neurophysiol       Date:  1998-02       Impact factor: 2.714

Review 6.  The acquisition of skilled motor performance: fast and slow experience-driven changes in primary motor cortex.

Authors:  A Karni; G Meyer; C Rey-Hipolito; P Jezzard; M M Adams; R Turner; L G Ungerleider
Journal:  Proc Natl Acad Sci U S A       Date:  1998-02-03       Impact factor: 11.205

7.  Explicit knowledge enhances motor vigor and performance: motivation versus practice in sequence tasks.

Authors:  Aaron L Wong; Martin A Lindquist; Adrian M Haith; John W Krakauer
Journal:  J Neurophysiol       Date:  2015-04-22       Impact factor: 2.714

8.  Motor cortex is required for learning but not for executing a motor skill.

Authors:  Risa Kawai; Timothy Markman; Rajesh Poddar; Raymond Ko; Antoniu L Fantana; Ashesh K Dhawale; Adam R Kampff; Bence P Ölveczky
Journal:  Neuron       Date:  2015-04-16       Impact factor: 17.173

9.  Overcoming motor "forgetting" through reinforcement of learned actions.

Authors:  Lior Shmuelof; Vincent S Huang; Adrian M Haith; Raymond J Delnicki; Pietro Mazzoni; John W Krakauer
Journal:  J Neurosci       Date:  2012-10-17       Impact factor: 6.167

Review 10.  Structure learning in action.

Authors:  Daniel A Braun; Carsten Mehring; Daniel M Wolpert
Journal:  Behav Brain Res       Date:  2009-08-29       Impact factor: 3.332

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  33 in total

1.  Disruption of M1 Activity during Performance Plateau Impairs Consolidation of Motor Memories.

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2.  Tracking the corticospinal responses to strength training.

Authors:  Joel Mason; Ashlyn K Frazer; Janne Avela; Alan J Pearce; Glyn Howatson; Dawson J Kidgell
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3.  Reciprocal intralimb transfer of skilled isometric force production.

Authors:  Vikram A Rajan; Robert M Hardwick; Pablo A Celnik
Journal:  J Neurophysiol       Date:  2019-05-01       Impact factor: 2.714

4.  Interactions between motor exploration and reinforcement learning.

Authors:  Shintaro Uehara; Firas Mawase; Amanda S Therrien; Kendra M Cherry-Allen; Pablo Celnik
Journal:  J Neurophysiol       Date:  2019-06-26       Impact factor: 2.714

5.  Learning Similar Actions by Reinforcement or Sensory-Prediction Errors Rely on Distinct Physiological Mechanisms.

Authors:  Shintaro Uehara; Firas Mawase; Pablo Celnik
Journal:  Cereb Cortex       Date:  2018-10-01       Impact factor: 5.357

6.  Use of Pelvic Corrective Force With Visual Feedback Improves Paretic Leg Muscle Activities and Gait Performance After Stroke.

Authors:  Chao-Jung Hsu; Janis Kim; Elliot J Roth; William Z Rymer; Ming Wu
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2019-10-29       Impact factor: 3.802

7.  Neuromuscular Electrical Stimulation Primes Feedback Control During a Novel Single Leg Task.

Authors:  Michael Petrie; Kristin Johnson; Patrick McCue; Richard K Shields
Journal:  J Mot Behav       Date:  2020-07-07       Impact factor: 1.328

8.  Use of explicit processes during a visually guided locomotor learning task predicts 24-h retention after stroke.

Authors:  Margaret A French; Susanne M Morton; Darcy S Reisman
Journal:  J Neurophysiol       Date:  2020-11-11       Impact factor: 2.714

Review 9.  The Psychology of Reaching: Action Selection, Movement Implementation, and Sensorimotor Learning.

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Review 10.  Multiple Motor Learning Processes in Humans: Defining Their Neurophysiological Bases.

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