Literature DB >> 28566463

Functional connectivity between somatosensory and motor brain areas predicts individual differences in motor learning by observing.

Heather R McGregor1,2, Paul L Gribble3,4,5.   

Abstract

Action observation can facilitate the acquisition of novel motor skills; however, there is considerable individual variability in the extent to which observation promotes motor learning. Here we tested the hypothesis that individual differences in brain function or structure can predict subsequent observation-related gains in motor learning. Subjects underwent an anatomical MRI scan and resting-state fMRI scans to assess preobservation gray matter volume and preobservation resting-state functional connectivity (FC), respectively. On the following day, subjects observed a video of a tutor adapting her reaches to a novel force field. After observation, subjects performed reaches in a force field as a behavioral assessment of gains in motor learning resulting from observation. We found that individual differences in resting-state FC, but not gray matter volume, predicted postobservation gains in motor learning. Preobservation resting-state FC between left primary somatosensory cortex and bilateral dorsal premotor cortex, primary motor cortex, and primary somatosensory cortex and left superior parietal lobule was positively correlated with behavioral measures of postobservation motor learning. Sensory-motor resting-state FC can thus predict the extent to which observation will promote subsequent motor learning.NEW & NOTEWORTHY We show that individual differences in preobservation brain function can predict subsequent observation-related gains in motor learning. Preobservation resting-state functional connectivity within a sensory-motor network may be used as a biomarker for the extent to which observation promotes motor learning. This kind of information may be useful if observation is to be used as a way to boost neuroplasticity and sensory-motor recovery for patients undergoing rehabilitation for diseases that impair movement such as stroke.
Copyright © 2017 the American Physiological Society.

Entities:  

Keywords:  action observation; human; individual differences; motor learning; resting-state fMRI

Mesh:

Year:  2017        PMID: 28566463      PMCID: PMC5547259          DOI: 10.1152/jn.00275.2017

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  30 in total

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Authors:  Alexandra Williams; Paul L Gribble
Journal:  J Neurophysiol       Date:  2011-12-21       Impact factor: 2.714

2.  Individual variability in functional connectivity predicts performance of a perceptual task.

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3.  Specific increases within global decreases: a functional magnetic resonance imaging investigation of five days of motor sequence learning.

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Journal:  J Neurosci       Date:  2010-06-16       Impact factor: 6.167

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Journal:  Lancet Neurol       Date:  2010-10-27       Impact factor: 44.182

Review 5.  Predispositions and plasticity in music and speech learning: neural correlates and implications.

Authors:  Robert J Zatorre
Journal:  Science       Date:  2013-11-01       Impact factor: 47.728

6.  Changes in visual and sensory-motor resting-state functional connectivity support motor learning by observing.

Authors:  Heather R McGregor; Paul L Gribble
Journal:  J Neurophysiol       Date:  2015-05-20       Impact factor: 2.714

7.  Functional Plasticity in Somatosensory Cortex Supports Motor Learning by Observing.

Authors:  Heather R McGregor; Joshua G A Cashaback; Paul L Gribble
Journal:  Curr Biol       Date:  2016-03-10       Impact factor: 10.834

8.  Individual differences in intrinsic brain connectivity predict decision strategy.

Authors:  Kelly Anne Barnes; Kevin M Anderson; Mark Plitt; Alex Martin
Journal:  J Neurophysiol       Date:  2014-07-16       Impact factor: 2.714

9.  The resting human brain and motor learning.

Authors:  Neil B Albert; Edwin M Robertson; R Chris Miall
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Review 10.  A quantitative meta-analysis and review of motor learning in the human brain.

Authors:  Robert M Hardwick; Claudia Rottschy; R Chris Miall; Simon B Eickhoff
Journal:  Neuroimage       Date:  2012-11-27       Impact factor: 6.556

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  7 in total

1.  Somatosensory perceptual training enhances motor learning by observing.

Authors:  Heather R McGregor; Joshua G A Cashaback; Paul L Gribble
Journal:  J Neurophysiol       Date:  2018-09-19       Impact factor: 2.714

Review 2.  A tale of too many tasks: task fragmentation in motor learning and a call for model task paradigms.

Authors:  Rajiv Ranganathan; Aimee D Tomlinson; Rakshith Lokesh; Tzu-Hsiang Lin; Priya Patel
Journal:  Exp Brain Res       Date:  2020-11-10       Impact factor: 1.972

3.  Motor learning without movement.

Authors:  Olivia A Kim; Alexander D Forrence; Samuel D McDougle
Journal:  Proc Natl Acad Sci U S A       Date:  2022-07-19       Impact factor: 12.779

4.  Changes in corticospinal excitability associated with motor learning by observing.

Authors:  Heather R McGregor; Michael Vesia; Cricia Rinchon; Robert Chen; Paul L Gribble
Journal:  Exp Brain Res       Date:  2018-07-21       Impact factor: 1.972

5.  Decreased thalamo-cortico connectivity during an implicit sequence motor learning task and 7 days escitalopram intake.

Authors:  Julia Sacher; Karsten Mueller; Eóin N Molloy; Rachel G Zsido; Fabian A Piecha; Nathalie Beinhölzl; Ulrike Scharrer; Gergana Zheleva; Ralf Regenthal; Bernhard Sehm; Vadim V Nikulin; Harald E Möller; Arno Villringer
Journal:  Sci Rep       Date:  2021-07-23       Impact factor: 4.379

6.  Network Brain-Computer Interface (nBCI): An Alternative Approach for Cognitive Prosthetics.

Authors:  Vivek P Buch; Andrew G Richardson; Cameron Brandon; Jennifer Stiso; Monica N Khattak; Danielle S Bassett; Timothy H Lucas
Journal:  Front Neurosci       Date:  2018-11-01       Impact factor: 4.677

7.  Brain Functional Networks Study of Subacute Stroke Patients With Upper Limb Dysfunction After Comprehensive Rehabilitation Including BCI Training.

Authors:  Qiong Wu; Zan Yue; Yunxiang Ge; Di Ma; Hang Yin; Hongliang Zhao; Gang Liu; Jing Wang; Weibei Dou; Yu Pan
Journal:  Front Neurol       Date:  2020-01-27       Impact factor: 4.003

  7 in total

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