Bertollo

Bortoli

Carson

Cheng

Christina

Dave J. Collins

Eaves

Gallagher

Hatfield

Holmes

Howie J. Carson

Loze

MacPherson

Neuper

Smith

Toner

van Schie

Wertheim

Wulf

Frontiers in Human Neuroscience

PubMed

Carson, H.J.,

Collins, D.J.

CLoK

ArticleCommentary: Motor imagery during action observation: A brief review of evidence, theory and future research opportunitiesCarson, H.J., and Collins, D.J.Available at http://clok.uclan.ac.uk/16778/Carson, H.J., and Collins, D.J. (2017) Commentary: Motor imagery during action observation: A brief review of evidence, theory and future research opportunities. Frontiers in Human Neuroscience, 11 . p. 25. ISSN 1662-4548  It is advisable to refer to the publisher’s version if you intend to cite from the work.http://dx.doi.org/10.3389/fnhum.2017.00025For more information about UCLan’s research in this area go to http://www.uclan.ac.uk/researchgroups/ and search for <name of research Group>.For information about Research generally at UCLan please go to http://www.uclan.ac.uk/research/ All outputs in CLoK are protected by Intellectual Property Rights law, includingCopyright law.  Copyright, IPR and Moral Rights for the works on this site are retained by the individual authors and/or other copyright owners. Terms and conditions for use of this material are defined in the http://clok.uclan.ac.uk/policies/CLoKCentral Lancashire online Knowledgewww.clok.uclan.ac.ukGENERAL COMMENTARYpublished: 25 January 2017doi: 10.3389/fnhum.2017.00025Frontiers in Human Neuroscience | www.frontiersin.org 1 January 2017 | Volume 11 | Article 25Edited by:Mikhail Lebedev,Duke University, USAReviewed by:Mar Gonzalez-Franco,Microsoft Research, USAMaurizio Bertollo,University of Chieti-Pescara, Italy*Correspondence:Howie J. Carsonhcarson1@uclan.ac.ukReceived: 07 December 2016Accepted: 12 January 2017Published: 25 January 2017Citation:Carson HJ and Collins DJ (2017)Commentary: Motor Imagery duringAction Observation: A Brief Review ofEvidence, Theory and FutureResearch Opportunities.Front. Hum. Neurosci. 11:25.doi: 10.3389/fnhum.2017.00025Commentary: Motor Imagery duringAction Observation: A Brief Review ofEvidence, Theory and FutureResearch OpportunitiesHowie J. Carson* and Dave J. CollinsInstitute for Coaching and Performance, School of Sport and Wellbeing, University of Central Lancashire, Preston, UKKeywords: motor Imagery, motor control, sport psychology, observational learning, coaching psychologyA commentary onMotor Imagery during Action Observation: A Brief Review of Evidence, Theory and FutureResearch Opportunitiesby Eaves, D. L., Riach, M., Holmes, P. S., and Wright, D. J. (2016). Front. Neurosci. 10:514.doi: 10.3389/fnins.2016.00514Eaves et al. (2016) recently provided an informative review concerning motor imagery duringaction observation. Specifically, they addressed its effectiveness, mechanisms, and future directionsfor study. While there is an apparent scarcity of studies to date, it is clear that much similarity existsin neural activity during action, observation, and imagery, with clear super-additive advantagesfor performing the latter two concurrently. We could not agree more with these authors whenit comes to encouraging practitioners (from our perspective, sport psychologists and coaches)to deploy mental simulation interventions as central pillars to assist a range of motor skillchallenges (e.g., executing under high competitive anxiety, skill acquisition). Notably, the reviewalso provided coverage of motoric factors (Carson and Collins, 2016) to offer an integratedunderstanding, something that has been somewhat neglected in other areas of psychology (e.g.,the anxiety–performance relationship; Cheng et al., 2009). Reflecting this motoric emphasis, thereare a number of interesting links, possibilities, and research directions which accrue from thispaper. As Eaves et al. explain, “AO [action observation] evokes an internal representation of theobserved movement” (p. 1). Accordingly, we raise several issues requiring attention from thetranslational research literature (Christina, 1987) and extend some of the suggestions by Eaveset al. Understandably, article length restrictions may have impacted on Eaves et al. in providingthis necessary detail that we feel warrants additional mention. Therefore, it is not our intention totake away from the quality work presented but rather, to support its desired aims.Firstly, the issue of task difficulty in relation to the nature (i.e., content and automaticity) ofmotoric structures over which the observed and imagined information act. Eaves et al. (2016)discuss a dual-action simulation framework for conceptualizing previous empirical findings.However, such dual-action effects might vary for tasks internalized in different ways, for instancerhythmical window wiping (highly internalized) might show different dual-actions than a complexhigh jump skill (less well-internalized). Toner and Moran (2015) discuss the advantage of high-level athletes purposefully not committing their skills to totally automatic control as a strategy toensure scope for future adaptability. Indeed, applied research from the multi-action plan (MAP)perspective supports this notion. Data show that optimal performances are achieved by elite-levelathletes through both automatic and controlled execution processes (Bortoli et al., 2012), wherebyconsciously controlled motor processing can positively assist performances under psychologicalCarson and Collins Motor Imagery during Action Observationpressure and physical fatigue. Distinction between thesetwo optimal execution modes and their relative processingefficiency, therefore, offers complexity regarding the translationof fundamental, theory-driven research for use with populationssuch as athletes. When a task is so extremely familiar and simple(with limited degrees of freedom involved; e.g., finger pinching)it is possible that the observer quickly extracts sufficient relevantinformation from the model through retinal-dependent feedback(or attention), then switches to a state of intention whereby themotor representation is generated and retrieved through imageryprocesses (Wertheim, 1981; Loze et al., 1999). Of course, thiswould only be possible with a high degree of efficiency if therepresentation was easily accessible and well-established withinlong-term memory. If the skill is less well-established (perhapsdue to its complexity), it might be that the interplay is differentbetween observing and then imaging (e.g., watch–image–watch–image/watch; cf. Smith et al., 1998).As a related but distinct issue, it may also be beneficialto consider the observation-based review of errors, and whatassociated processes can bring to the learning process. Forexample, the generation of efference copy (what the movementshould feel like) which learners’ can then use for intentivecomparison and subsequent, enhanced learning (cf. Gallagher,2000). Of relevance, there is clear evidence that similar neuralmechanisms are involved in error detection for one’s ownmovements or when observing others (van Schie et al., 2004).Whether the case is of a well-known or being-learnt task,however, for observation and imagery to be optimized within theapplied sport setting, a better understanding of these processesacross complex moves are required.A second issue relates to what the observer focusseson during the observation and/or imagery process. This islikely important because studies have demonstrated differentlearning/performance effects when an athlete adopts differentattentional foci. In javelin throwing, MacPherson et al. (2008)found that focusing on holistic-rhythm resulted in a moreconsistent pattern of variability across kinematics whereasfocusing on a single element (e.g., fast arm) lowered thevariability of that component and increased the variability acrossothers; thus disrupting the balance of control. Focusing on“core components” of an action (those that are essential foroptimal performance), as advocated by the MAP, has beenshown to result in optimal performance levels even thoughthey are underpinned by an inefficient (according to the neuralefficiency hypothesis; Hatfield and Kerick, 2007), dissimilar stateof neural assemblies (desynchronized theta/alpha power) whencompared to automatic processing (Bertollo et al., 2016). A keyquestion here, then, is whether the nature of what is imagedwhilst observing changes the extent to which motor regions areactivated in the brain and thus, the representation formed (cf. vanSchie et al., 2004; Neuper et al., 2009). Given that this content willchange with experience, the case of skill refinement (adjusting analready established skill; Carson and Collins, 2011) is a particularcase for further consideration. As one ofmany issues, howwill thepattern of imagery/observation change when moving from well-established but suboptimum components to replace them withnew but comparatively unknown elements.Finally, there has been growing evidence to support thebeneficial impact on mental imagery when employing PETTLEP(Holmes and Collins, 2001) principles. On the basis thatobservation and imagery processes share, at the very least, similarneural pathways, could the benefits already shown by combiningimagery with observation be improved even further by attentionto these important elements? We suggest that examination ofsuch effects would be welcomed andwell-situated to inform othermore prominent areas of research within motor control; namely,that concerning an athlete’s focus of attention (Wulf, 2013).AUTHOR CONTRIBUTIONSHC and DC contributed equally to the ideas and writing of thearticle.REFERENCESBertollo, M., di Fronso, S., Filho, E., Conforto, S., Schmid, M., Bortoli, L., et al.(2016). Proficient brain for optimal performance: the MAP model perspective.PeerJ 4:e2082. doi: 10.7717/peerj.2082Bortoli, L., Bertollo, M., Hanin, Y., and Robazza, C. (2012). Striving for excellence:a multi-action plan intervention model for shooters. Psychol. Sport Exerc. 13,693–701. doi: 10.1016/j.psychsport.2012.04.006Carson, H. J., and Collins, D. (2011). Refining and regaining skills infixation/diversification stage performers: the five-a model. Int. Rev. Sport Exerc.Psychol. 4, 146–167. doi: 10.1080/1750984X.2011.613682Carson, H. J., and Collins, D. (2016). The fourth dimension: a motoric perspectiveon the anxiety–performance relationship. Int. Rev. Sport Exerc. Psychol. 9, 1–21.doi: 10.1080/1750984X.2015.1072231Cheng, W.-N. K., Hardy, L., and Markland, D. (2009). Toward a three-dimensional conceptualization of performance anxiety: rationale andinitial measurement development. Psychol. Sport Exerc. 10, 271–278.doi: 10.1016/j.psychsport.2008.08.001Christina, R. W. (1987). “Motor learning: Future lines of research,” in The CuttingEdge in Physical Education and Exercise Science Research, eds M. J. Safrit and H.M. Eckert (Champaign, IL: Human Kinetics), 26–41.Eaves, D. L., Riach, M., Holmes, P. S., and Wright, D. J. (2016). Motor imageryduring action observation: a brief review of evidence, theory and future researchopportunities. Front. Neurosci. 10:514. doi: 10.3389/fnins.2016.00514Gallagher, S. (2000). Philosophical conceptions of the self:implications for cognitive science. Trends Cogn. Sci. 4, 14–21.doi: 10.1016/S1364-6613(99)01417-5Hatfield, B. D., and Kerick, S. E. (2007). “The psychology of superior sportperformance: A cognitive and affective neuroscience perspective,” inHandbookof Sport Psychology, 3rd Edn., eds R. C. Eklund and G. Tenenbaum (Hoboken,NJ: John Wiley & Sons Inc), 84–109.Holmes, P. S., and Collins, D. J. (2001). The PETTLEP approach to motor imagery:a functional equivalence model for sport psychologists. J. Appl. Sport Psychol.13, 60–83. doi: 10.1080/10413200109339004Loze, G. M., Collins, D., and Shaw, J. C. (1999). EEG alpha rhythm,intention and oculomotor control. Int. J. Psychophysiol. 33, 163–167.doi: 10.1016/S0167-8760(99)00024-0MacPherson, A. C., Collins, D., and Morriss, C. (2008). Is what you think whatyou get? Optimizing mental focus for technical performance. Sport Psychol. 22,288–303. doi: 10.1123/tsp.22.3.288Neuper, C., Scherer, R., Wriessnegger, S., and Pfurtscheller, G. (2009). Motorimagery and action observation: modulation of sensorimotor brain rhythmsFrontiers in Human Neuroscience | www.frontiersin.org 2 January 2017 | Volume 11 | Article 25Carson and Collins Motor Imagery during Action Observationduring mental control of a brain-computer interface. Clin. Neurophysiol. 120,239–247. doi: 10.1016/j.clinph.2008.11.015Smith, D., Collins, D., and Hale, B. (1998). Imagery perspectives and Karateperformance. J. Sport Sci. 16, 103–104.Toner, J., and Moran, A. (2015). Enhancing performance proficiency at the expertlevel: considering the role of ‘somaesthetic awareness’. Psychol. Sport Exerc. 16,110–117. doi: 10.1016/j.psychsport.2014.07.006van Schie, H. T.,Mars, R. B., Coles,M. G.H., and Bekkering, H. (2004).Modulationof activity in medial frontal and motor cortices during error observation. Nat.Neurosci. 7, 549–554. doi: 10.1038/nn1239Wertheim, A. H. (1981). Occipital alpha activity as a measure of retinalinvolvement in oculomotor control. Psychophysiology 18, 432–439.doi: 10.1111/j.1469-8986.1981.tb02476.xWulf, G. (2013). Attentional focus and motor learning: a review of 15 years. Int.Rev. Sport Exerc. Psychol. 6, 77–104. doi: 10.1080/1750984X.2012.723728Conflict of Interest Statement: The authors declare that the research wasconducted in the absence of any commercial or financial relationships that couldbe construed as a potential conflict of interest.Copyright © 2017 Carson and Collins. This is an open-access article distributedunder the terms of the Creative Commons Attribution License (CC BY). The use,distribution or reproduction in other forums is permitted, provided the originalauthor(s) or licensor are credited and that the original publication in this journalis cited, in accordance with accepted academic practice. No use, distribution orreproduction is permitted which does not comply with these terms.Frontiers in Human Neuroscience | www.frontiersin.org 3 January 2017 | Volume 11 | Article 25

Commentary: Motor imagery during action observation: A brief review of evidence, theory and future research opportunities

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Commentary: Motor Imagery during Action Observation: A Brief Review of Evidence, Theory and Future Research Opportunities

Carson, Howie J.

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     Edinburgh Research Explorer                                      Commentary: Motor imagery during action observationCitation for published version:Carson, HJ & Collins, DJ 2017, 'Commentary: Motor imagery during action observation: A brief review ofevidence, theory and future research opportunities', Frontiers in Human Neuroscience, vol. 11, 25, pp. 1-3.https://doi.org/10.3389/fnhum.2017.00025Digital Object Identifier (DOI):10.3389/fnhum.2017.00025Link:Link to publication record in Edinburgh Research ExplorerDocument Version:Publisher's PDF, also known as Version of recordPublished In:Frontiers in Human NeuroscienceGeneral rightsCopyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s)and / or other copyright owners and it is a condition of accessing these publications that users recognise andabide by the legal requirements associated with these rights.Take down policyThe University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorercontent complies with UK legislation. If you believe that the public display of this file breaches copyright pleasecontact openaccess@ed.ac.uk providing details, and we will remove access to the work immediately andinvestigate your claim.Download date: 26. Sep. 2019GENERAL COMMENTARYpublished: 25 January 2017doi: 10.3389/fnhum.2017.00025Frontiers in Human Neuroscience | www.frontiersin.org 1 January 2017 | Volume 11 | Article 25Edited by:Mikhail Lebedev,Duke University, USAReviewed by:Mar Gonzalez-Franco,Microsoft Research, USAMaurizio Bertollo,University of Chieti-Pescara, Italy*Correspondence:Howie J. Carsonhcarson1@uclan.ac.ukReceived: 07 December 2016Accepted: 12 January 2017Published: 25 January 2017Citation:Carson HJ and Collins DJ (2017)Commentary: Motor Imagery duringAction Observation: A Brief Review ofEvidence, Theory and FutureResearch Opportunities.Front. Hum. Neurosci. 11:25.doi: 10.3389/fnhum.2017.00025Commentary: Motor Imagery duringAction Observation: A Brief Review ofEvidence, Theory and FutureResearch OpportunitiesHowie J. Carson* and Dave J. CollinsInstitute for Coaching and Performance, School of Sport and Wellbeing, University of Central Lancashire, Preston, UKKeywords: motor Imagery, motor control, sport psychology, observational learning, coaching psychologyA commentary onMotor Imagery during Action Observation: A Brief Review of Evidence, Theory and FutureResearch Opportunitiesby Eaves, D. L., Riach, M., Holmes, P. S., and Wright, D. J. (2016). Front. Neurosci. 10:514.doi: 10.3389/fnins.2016.00514Eaves et al. (2016) recently provided an informative review concerning motor imagery duringaction observation. Specifically, they addressed its effectiveness, mechanisms, and future directionsfor study. While there is an apparent scarcity of studies to date, it is clear that much similarity existsin neural activity during action, observation, and imagery, with clear super-additive advantagesfor performing the latter two concurrently. We could not agree more with these authors whenit comes to encouraging practitioners (from our perspective, sport psychologists and coaches)to deploy mental simulation interventions as central pillars to assist a range of motor skillchallenges (e.g., executing under high competitive anxiety, skill acquisition). Notably, the reviewalso provided coverage of motoric factors (Carson and Collins, 2016) to offer an integratedunderstanding, something that has been somewhat neglected in other areas of psychology (e.g.,the anxiety–performance relationship; Cheng et al., 2009). Reflecting this motoric emphasis, thereare a number of interesting links, possibilities, and research directions which accrue from thispaper. As Eaves et al. explain, “AO [action observation] evokes an internal representation of theobserved movement” (p. 1). Accordingly, we raise several issues requiring attention from thetranslational research literature (Christina, 1987) and extend some of the suggestions by Eaveset al. Understandably, article length restrictions may have impacted on Eaves et al. in providingthis necessary detail that we feel warrants additional mention. Therefore, it is not our intention totake away from the quality work presented but rather, to support its desired aims.Firstly, the issue of task difficulty in relation to the nature (i.e., content and automaticity) ofmotoric structures over which the observed and imagined information act. Eaves et al. (2016)discuss a dual-action simulation framework for conceptualizing previous empirical findings.However, such dual-action effects might vary for tasks internalized in different ways, for instancerhythmical window wiping (highly internalized) might show different dual-actions than a complexhigh jump skill (less well-internalized). Toner and Moran (2015) discuss the advantage of high-level athletes purposefully not committing their skills to totally automatic control as a strategy toensure scope for future adaptability. Indeed, applied research from the multi-action plan (MAP)perspective supports this notion. Data show that optimal performances are achieved by elite-levelathletes through both automatic and controlled execution processes (Bortoli et al., 2012), wherebyconsciously controlled motor processing can positively assist performances under psychologicalCarson and Collins Motor Imagery during Action Observationpressure and physical fatigue. Distinction between thesetwo optimal execution modes and their relative processingefficiency, therefore, offers complexity regarding the translationof fundamental, theory-driven research for use with populationssuch as athletes. When a task is so extremely familiar and simple(with limited degrees of freedom involved; e.g., finger pinching)it is possible that the observer quickly extracts sufficient relevantinformation from the model through retinal-dependent feedback(or attention), then switches to a state of intention whereby themotor representation is generated and retrieved through imageryprocesses (Wertheim, 1981; Loze et al., 1999). Of course, thiswould only be possible with a high degree of efficiency if therepresentation was easily accessible and well-established withinlong-term memory. If the skill is less well-established (perhapsdue to its complexity), it might be that the interplay is differentbetween observing and then imaging (e.g., watch–image–watch–image/watch; cf. Smith et al., 1998).As a related but distinct issue, it may also be beneficialto consider the observation-based review of errors, and whatassociated processes can bring to the learning process. Forexample, the generation of efference copy (what the movementshould feel like) which learners’ can then use for intentivecomparison and subsequent, enhanced learning (cf. Gallagher,2000). Of relevance, there is clear evidence that similar neuralmechanisms are involved in error detection for one’s ownmovements or when observing others (van Schie et al., 2004).Whether the case is of a well-known or being-learnt task,however, for observation and imagery to be optimized within theapplied sport setting, a better understanding of these processesacross complex moves are required.A second issue relates to what the observer focusseson during the observation and/or imagery process. This islikely important because studies have demonstrated differentlearning/performance effects when an athlete adopts differentattentional foci. In javelin throwing, MacPherson et al. (2008)found that focusing on holistic-rhythm resulted in a moreconsistent pattern of variability across kinematics whereasfocusing on a single element (e.g., fast arm) lowered thevariability of that component and increased the variability acrossothers; thus disrupting the balance of control. Focusing on“core components” of an action (those that are essential foroptimal performance), as advocated by the MAP, has beenshown to result in optimal performance levels even thoughthey are underpinned by an inefficient (according to the neuralefficiency hypothesis; Hatfield and Kerick, 2007), dissimilar stateof neural assemblies (desynchronized theta/alpha power) whencompared to automatic processing (Bertollo et al., 2016). A keyquestion here, then, is whether the nature of what is imagedwhilst observing changes the extent to which motor regions areactivated in the brain and thus, the representation formed (cf. vanSchie et al., 2004; Neuper et al., 2009). Given that this content willchange with experience, the case of skill refinement (adjusting analready established skill; Carson and Collins, 2011) is a particularcase for further consideration. As one ofmany issues, howwill thepattern of imagery/observation change when moving from well-established but suboptimum components to replace them withnew but comparatively unknown elements.Finally, there has been growing evidence to support thebeneficial impact on mental imagery when employing PETTLEP(Holmes and Collins, 2001) principles. On the basis thatobservation and imagery processes share, at the very least, similarneural pathways, could the benefits already shown by combiningimagery with observation be improved even further by attentionto these important elements? We suggest that examination ofsuch effects would be welcomed andwell-situated to inform othermore prominent areas of research within motor control; namely,that concerning an athlete’s focus of attention (Wulf, 2013).AUTHOR CONTRIBUTIONSHC and DC contributed equally to the ideas and writing of thearticle.REFERENCESBertollo, M., di Fronso, S., Filho, E., Conforto, S., Schmid, M., Bortoli, L., et al.(2016). Proficient brain for optimal performance: the MAP model perspective.PeerJ 4:e2082. doi: 10.7717/peerj.2082Bortoli, L., Bertollo, M., Hanin, Y., and Robazza, C. (2012). Striving for excellence:a multi-action plan intervention model for shooters. Psychol. Sport Exerc. 13,693–701. doi: 10.1016/j.psychsport.2012.04.006Carson, H. J., and Collins, D. (2011). Refining and regaining skills infixation/diversification stage performers: the five-a model. Int. Rev. Sport Exerc.Psychol. 4, 146–167. doi: 10.1080/1750984X.2011.613682Carson, H. J., and Collins, D. (2016). The fourth dimension: a motoric perspectiveon the anxiety–performance relationship. Int. Rev. Sport Exerc. Psychol. 9, 1–21.doi: 10.1080/1750984X.2015.1072231Cheng, W.-N. K., Hardy, L., and Markland, D. (2009). Toward a three-dimensional conceptualization of performance anxiety: rationale andinitial measurement development. Psychol. Sport Exerc. 10, 271–278.doi: 10.1016/j.psychsport.2008.08.001Christina, R. W. (1987). “Motor learning: Future lines of research,” in The CuttingEdge in Physical Education and Exercise Science Research, eds M. J. Safrit and H.M. Eckert (Champaign, IL: Human Kinetics), 26–41.Eaves, D. L., Riach, M., Holmes, P. S., and Wright, D. J. (2016). Motor imageryduring action observation: a brief review of evidence, theory and future researchopportunities. Front. Neurosci. 10:514. doi: 10.3389/fnins.2016.00514Gallagher, S. (2000). Philosophical conceptions of the self:implications for cognitive science. Trends Cogn. Sci. 4, 14–21.doi: 10.1016/S1364-6613(99)01417-5Hatfield, B. D., and Kerick, S. E. (2007). “The psychology of superior sportperformance: A cognitive and affective neuroscience perspective,” inHandbookof Sport Psychology, 3rd Edn., eds R. C. Eklund and G. Tenenbaum (Hoboken,NJ: John Wiley & Sons Inc), 84–109.Holmes, P. S., and Collins, D. J. (2001). The PETTLEP approach to motor imagery:a functional equivalence model for sport psychologists. J. Appl. Sport Psychol.13, 60–83. doi: 10.1080/10413200109339004Loze, G. M., Collins, D., and Shaw, J. C. (1999). EEG alpha rhythm,intention and oculomotor control. Int. J. Psychophysiol. 33, 163–167.doi: 10.1016/S0167-8760(99)00024-0MacPherson, A. C., Collins, D., and Morriss, C. (2008). Is what you think whatyou get? Optimizing mental focus for technical performance. Sport Psychol. 22,288–303. doi: 10.1123/tsp.22.3.288Neuper, C., Scherer, R., Wriessnegger, S., and Pfurtscheller, G. (2009). Motorimagery and action observation: modulation of sensorimotor brain rhythmsFrontiers in Human Neuroscience | www.frontiersin.org 2 January 2017 | Volume 11 | Article 25Carson and Collins Motor Imagery during Action Observationduring mental control of a brain-computer interface. Clin. Neurophysiol. 120,239–247. doi: 10.1016/j.clinph.2008.11.015Smith, D., Collins, D., and Hale, B. (1998). Imagery perspectives and Karateperformance. J. Sport Sci. 16, 103–104.Toner, J., and Moran, A. (2015). Enhancing performance proficiency at the expertlevel: considering the role of ‘somaesthetic awareness’. Psychol. Sport Exerc. 16,110–117. doi: 10.1016/j.psychsport.2014.07.006van Schie, H. T.,Mars, R. B., Coles,M. G.H., and Bekkering, H. (2004).Modulationof activity in medial frontal and motor cortices during error observation. Nat.Neurosci. 7, 549–554. doi: 10.1038/nn1239Wertheim, A. H. (1981). Occipital alpha activity as a measure of retinalinvolvement in oculomotor control. Psychophysiology 18, 432–439.doi: 10.1111/j.1469-8986.1981.tb02476.xWulf, G. (2013). Attentional focus and motor learning: a review of 15 years. Int.Rev. Sport Exerc. Psychol. 6, 77–104. doi: 10.1080/1750984X.2012.723728Conflict of Interest Statement: The authors declare that the research wasconducted in the absence of any commercial or financial relationships that couldbe construed as a potential conflict of interest.Copyright © 2017 Carson and Collins. This is an open-access article distributedunder the terms of the Creative Commons Attribution License (CC BY). The use,distribution or reproduction in other forums is permitted, provided the originalauthor(s) or licensor are credited and that the original publication in this journalis cited, in accordance with accepted academic practice. No use, distribution orreproduction is permitted which does not comply with these terms.Frontiers in Human Neuroscience | www.frontiersin.org 3 January 2017 | Volume 11 | Article 25

Commentary: Motor imagery during action observation:A brief review of evidence, theory and future research opportunities

GENERAL COMMENTARY
published: 25 January 2017
doi: 10.3389/fnhum.2017.00025
Frontiers in Human Neuroscience | www.frontiersin.org 1 January 2017 | Volume 11 | Article 25
Edited by:
Mikhail Lebedev,
Duke University, USA
Reviewed by:
Mar Gonzalez-Franco,
Microsoft Research, USA
Maurizio Bertollo,
University of Chieti-Pescara, Italy
*Correspondence:
Howie J. Carson
hcarson1@uclan.ac.uk
Received: 07 December 2016
Accepted: 12 January 2017
Published: 25 January 2017
Citation:
Carson HJ and Collins DJ (2017)
Commentary: Motor Imagery during
Action Observation: A Brief Review of
Evidence, Theory and Future
Research Opportunities.
Front. Hum. Neurosci. 11:25.
doi: 10.3389/fnhum.2017.00025
Commentary: Motor Imagery during
Action Observation: A Brief Review of
Evidence, Theory and Future
Research Opportunities
Howie J. Carson* and Dave J. Collins
Institute for Coaching and Performance, School of Sport and Wellbeing, University of Central Lancashire, Preston, UK
Keywords: motor Imagery, motor control, sport psychology, observational learning, coaching psychology
A commentary on
Motor Imagery during Action Observation: A Brief Review of Evidence, Theory and Future
Research Opportunities
by Eaves, D. L., Riach, M., Holmes, P. S., and Wright, D. J. (2016). Front. Neurosci. 10:514.
doi: 10.3389/fnins.2016.00514
Eaves et al. (2016) recently provided an informative review concerning motor imagery during
action observation. Specifically, they addressed its effectiveness, mechanisms, and future directions
for study. While there is an apparent scarcity of studies to date, it is clear that much similarity exists
in neural activity during action, observation, and imagery, with clear super-additive advantages
for performing the latter two concurrently. We could not agree more with these authors when
it comes to encouraging practitioners (from our perspective, sport psychologists and coaches)
to deploy mental simulation interventions as central pillars to assist a range of motor skill
challenges (e.g., executing under high competitive anxiety, skill acquisition). Notably, the review
also provided coverage of motoric factors (Carson and Collins, 2016) to offer an integrated
understanding, something that has been somewhat neglected in other areas of psychology (e.g.,
the anxiety–performance relationship; Cheng et al., 2009). Reflecting this motoric emphasis, there
are a number of interesting links, possibilities, and research directions which accrue from this
paper. As Eaves et al. explain, “AO [action observation] evokes an internal representation of the
observed movement” (p. 1). Accordingly, we raise several issues requiring attention from the
translational research literature (Christina, 1987) and extend some of the suggestions by Eaves
et al. Understandably, article length restrictions may have impacted on Eaves et al. in providing
this necessary detail that we feel warrants additional mention. Therefore, it is not our intention to
take away from the quality work presented but rather, to support its desired aims.
Firstly, the issue of task difficulty in relation to the nature (i.e., content and automaticity) of
motoric structures over which the observed and imagined information act. Eaves et al. (2016)
discuss a dual-action simulation framework for conceptualizing previous empirical findings.
However, such dual-action effects might vary for tasks internalized in different ways, for instance
rhythmical window wiping (highly internalized) might show different dual-actions than a complex
high jump skill (less well-internalized). Toner and Moran (2015) discuss the advantage of high-
level athletes purposefully not committing their skills to totally automatic control as a strategy to
ensure scope for future adaptability. Indeed, applied research from the multi-action plan (MAP)
perspective supports this notion. Data show that optimal performances are achieved by elite-level
athletes through both automatic and controlled execution processes (Bortoli et al., 2012), whereby
consciously controlled motor processing can positively assist performances under psychological
Carson and Collins Motor Imagery during Action Observation
pressure and physical fatigue. Distinction between these
two optimal execution modes and their relative processing
efficiency, therefore, offers complexity regarding the translation
of fundamental, theory-driven research for use with populations
such as athletes. When a task is so extremely familiar and simple
(with limited degrees of freedom involved; e.g., finger pinching)
it is possible that the observer quickly extracts sufficient relevant
information from the model through retinal-dependent feedback
(or attention), then switches to a state of intention whereby the
motor representation is generated and retrieved through imagery
processes (Wertheim, 1981; Loze et al., 1999). Of course, this
would only be possible with a high degree of efficiency if the
representation was easily accessible and well-established within
long-term memory. If the skill is less well-established (perhaps
due to its complexity), it might be that the interplay is different
between observing and then imaging (e.g., watch–image–watch–
image/watch; cf. Smith et al., 1998).
As a related but distinct issue, it may also be beneficial
to consider the observation-based review of errors, and what
associated processes can bring to the learning process. For
example, the generation of efference copy (what the movement
should feel like) which learners’ can then use for intentive
comparison and subsequent, enhanced learning (cf. Gallagher,
2000). Of relevance, there is clear evidence that similar neural
mechanisms are involved in error detection for one’s own
movements or when observing others (van Schie et al., 2004).
Whether the case is of a well-known or being-learnt task,
however, for observation and imagery to be optimized within the
applied sport setting, a better understanding of these processes
across complex moves are required.
A second issue relates to what the observer focusses
on during the observation and/or imagery process. This is
likely important because studies have demonstrated different
learning/performance effects when an athlete adopts different
attentional foci. In javelin throwing, MacPherson et al. (2008)
found that focusing on holistic-rhythm resulted in a more
consistent pattern of variability across kinematics whereas
focusing on a single element (e.g., fast arm) lowered the
variability of that component and increased the variability across
others; thus disrupting the balance of control. Focusing on
“core components” of an action (those that are essential for
optimal performance), as advocated by the MAP, has been
shown to result in optimal performance levels even though
they are underpinned by an inefficient (according to the neural
efficiency hypothesis; Hatfield and Kerick, 2007), dissimilar state
of neural assemblies (desynchronized theta/alpha power) when
compared to automatic processing (Bertollo et al., 2016). A key
question here, then, is whether the nature of what is imaged
whilst observing changes the extent to which motor regions are
activated in the brain and thus, the representation formed (cf. van
Schie et al., 2004; Neuper et al., 2009). Given that this content will
change with experience, the case of skill refinement (adjusting an
already established skill; Carson and Collins, 2011) is a particular
case for further consideration. As one ofmany issues, howwill the
pattern of imagery/observation change when moving from well-
established but suboptimum components to replace them with
new but comparatively unknown elements.
Finally, there has been growing evidence to support the
beneficial impact on mental imagery when employing PETTLEP
(Holmes and Collins, 2001) principles. On the basis that
observation and imagery processes share, at the very least, similar
neural pathways, could the benefits already shown by combining
imagery with observation be improved even further by attention
to these important elements? We suggest that examination of
such effects would be welcomed andwell-situated to inform other
more prominent areas of research within motor control; namely,
that concerning an athlete’s focus of attention (Wulf, 2013).
AUTHOR CONTRIBUTIONS
HC and DC contributed equally to the ideas and writing of the
article.
REFERENCES
Bertollo, M., di Fronso, S., Filho, E., Conforto, S., Schmid, M., Bortoli, L., et al.
(2016). Proficient brain for optimal performance: the MAP model perspective.
PeerJ 4:e2082. doi: 10.7717/peerj.2082
Bortoli, L., Bertollo, M., Hanin, Y., and Robazza, C. (2012). Striving for excellence:
a multi-action plan intervention model for shooters. Psychol. Sport Exerc. 13,
693–701. doi: 10.1016/j.psychsport.2012.04.006
Carson, H. J., and Collins, D. (2011). Refining and regaining skills in
fixation/diversification stage performers: the five-a model. Int. Rev. Sport Exerc.
Psychol. 4, 146–167. doi: 10.1080/1750984X.2011.613682
Carson, H. J., and Collins, D. (2016). The fourth dimension: a motoric perspective
on the anxiety–performance relationship. Int. Rev. Sport Exerc. Psychol. 9, 1–21.
doi: 10.1080/1750984X.2015.1072231
Cheng, W.-N. K., Hardy, L., and Markland, D. (2009). Toward a three-
dimensional conceptualization of performance anxiety: rationale and
initial measurement development. Psychol. Sport Exerc. 10, 271–278.
doi: 10.1016/j.psychsport.2008.08.001
Christina, R. W. (1987). “Motor learning: Future lines of research,” in The Cutting
Edge in Physical Education and Exercise Science Research, eds M. J. Safrit and H.
M. Eckert (Champaign, IL: Human Kinetics), 26–41.
Eaves, D. L., Riach, M., Holmes, P. S., and Wright, D. J. (2016). Motor imagery
during action observation: a brief review of evidence, theory and future research
opportunities. Front. Neurosci. 10:514. doi: 10.3389/fnins.2016.00514
Gallagher, S. (2000). Philosophical conceptions of the self:
implications for cognitive science. Trends Cogn. Sci. 4, 14–21.
doi: 10.1016/S1364-6613(99)01417-5
Hatfield, B. D., and Kerick, S. E. (2007). “The psychology of superior sport
performance: A cognitive and affective neuroscience perspective,” inHandbook
of Sport Psychology, 3rd Edn., eds R. C. Eklund and G. Tenenbaum (Hoboken,
NJ: John Wiley & Sons Inc), 84–109.
Holmes, P. S., and Collins, D. J. (2001). The PETTLEP approach to motor imagery:
a functional equivalence model for sport psychologists. J. Appl. Sport Psychol.
13, 60–83. doi: 10.1080/10413200109339004
Loze, G. M., Collins, D., and Shaw, J. C. (1999). EEG alpha rhythm,
intention and oculomotor control. Int. J. Psychophysiol. 33, 163–167.
doi: 10.1016/S0167-8760(99)00024-0
MacPherson, A. C., Collins, D., and Morriss, C. (2008). Is what you think what
you get? Optimizing mental focus for technical performance. Sport Psychol. 22,
288–303. doi: 10.1123/tsp.22.3.288
Neuper, C., Scherer, R., Wriessnegger, S., and Pfurtscheller, G. (2009). Motor
imagery and action observation: modulation of sensorimotor brain rhythms
Frontiers in Human Neuroscience | www.frontiersin.org 2 January 2017 | Volume 11 | Article 25
Carson and Collins Motor Imagery during Action Observation
during mental control of a brain-computer interface. Clin. Neurophysiol. 120,
239–247. doi: 10.1016/j.clinph.2008.11.015
Smith, D., Collins, D., and Hale, B. (1998). Imagery perspectives and Karate
performance. J. Sport Sci. 16, 103–104.
Toner, J., and Moran, A. (2015). Enhancing performance proficiency at the expert
level: considering the role of ‘somaesthetic awareness’. Psychol. Sport Exerc. 16,
110–117. doi: 10.1016/j.psychsport.2014.07.006
van Schie, H. T.,Mars, R. B., Coles,M. G.H., and Bekkering, H. (2004).Modulation
of activity in medial frontal and motor cortices during error observation. Nat.
Neurosci. 7, 549–554. doi: 10.1038/nn1239
Wertheim, A. H. (1981). Occipital alpha activity as a measure of retinal
involvement in oculomotor control. Psychophysiology 18, 432–439.
doi: 10.1111/j.1469-8986.1981.tb02476.x
Wulf, G. (2013). Attentional focus and motor learning: a review of 15 years. Int.
Rev. Sport Exerc. Psychol. 6, 77–104. doi: 10.1080/1750984X.2012.723728
Conflict of Interest Statement: The authors declare that the research was
conducted in the absence of any commercial or financial relationships that could
be construed as a potential conflict of interest.
Copyright © 2017 Carson and Collins. This is an open-access article distributed
under the terms of the Creative Commons Attribution License (CC BY). The use,
distribution or reproduction in other forums is permitted, provided the original
author(s) or licensor are credited and that the original publication in this journal
is cited, in accordance with accepted academic practice. No use, distribution or
reproduction is permitted which does not comply with these terms.
Frontiers in Human Neuroscience | www.frontiersin.org 3 January 2017 | Volume 11 | Article 25


Crossref

     Edinburgh Research Explorer                                      Commentary: Motor imagery during action observationA brief review of evidence, theory and future research opportunitiesCitation for published version:Carson, HJ & Collins, DJ 2017, 'Commentary: Motor imagery during action observation: A brief review ofevidence, theory and future research opportunities', Frontiers in Human Neuroscience, vol. 11, 25, pp. 1-3.https://doi.org/10.3389/fnhum.2017.00025Digital Object Identifier (DOI):10.3389/fnhum.2017.00025Link:Link to publication record in Edinburgh Research ExplorerDocument Version:Publisher's PDF, also known as Version of recordPublished In:Frontiers in Human NeuroscienceGeneral rightsCopyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s)and / or other copyright owners and it is a condition of accessing these publications that users recognise andabide by the legal requirements associated with these rights.Take down policyThe University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorercontent complies with UK legislation. If you believe that the public display of this file breaches copyright pleasecontact openaccess@ed.ac.uk providing details, and we will remove access to the work immediately andinvestigate your claim.Download date: 26. Nov. 2025GENERAL COMMENTARYpublished: 25 January 2017doi: 10.3389/fnhum.2017.00025Frontiers in Human Neuroscience | www.frontiersin.org 1 January 2017 | Volume 11 | Article 25Edited by:Mikhail Lebedev,Duke University, USAReviewed by:Mar Gonzalez-Franco,Microsoft Research, USAMaurizio Bertollo,University of Chieti-Pescara, Italy*Correspondence:Howie J. Carsonhcarson1@uclan.ac.ukReceived: 07 December 2016Accepted: 12 January 2017Published: 25 January 2017Citation:Carson HJ and Collins DJ (2017)Commentary: Motor Imagery duringAction Observation: A Brief Review ofEvidence, Theory and FutureResearch Opportunities.Front. Hum. Neurosci. 11:25.doi: 10.3389/fnhum.2017.00025Commentary: Motor Imagery duringAction Observation: A Brief Review ofEvidence, Theory and FutureResearch OpportunitiesHowie J. Carson* and Dave J. CollinsInstitute for Coaching and Performance, School of Sport and Wellbeing, University of Central Lancashire, Preston, UKKeywords: motor Imagery, motor control, sport psychology, observational learning, coaching psychologyA commentary onMotor Imagery during Action Observation: A Brief Review of Evidence, Theory and FutureResearch Opportunitiesby Eaves, D. L., Riach, M., Holmes, P. S., and Wright, D. J. (2016). Front. Neurosci. 10:514.doi: 10.3389/fnins.2016.00514Eaves et al. (2016) recently provided an informative review concerning motor imagery duringaction observation. Specifically, they addressed its effectiveness, mechanisms, and future directionsfor study. While there is an apparent scarcity of studies to date, it is clear that much similarity existsin neural activity during action, observation, and imagery, with clear super-additive advantagesfor performing the latter two concurrently. We could not agree more with these authors whenit comes to encouraging practitioners (from our perspective, sport psychologists and coaches)to deploy mental simulation interventions as central pillars to assist a range of motor skillchallenges (e.g., executing under high competitive anxiety, skill acquisition). Notably, the reviewalso provided coverage of motoric factors (Carson and Collins, 2016) to offer an integratedunderstanding, something that has been somewhat neglected in other areas of psychology (e.g.,the anxiety–performance relationship; Cheng et al., 2009). Reflecting this motoric emphasis, thereare a number of interesting links, possibilities, and research directions which accrue from thispaper. As Eaves et al. explain, “AO [action observation] evokes an internal representation of theobserved movement” (p. 1). Accordingly, we raise several issues requiring attention from thetranslational research literature (Christina, 1987) and extend some of the suggestions by Eaveset al. Understandably, article length restrictions may have impacted on Eaves et al. in providingthis necessary detail that we feel warrants additional mention. Therefore, it is not our intention totake away from the quality work presented but rather, to support its desired aims.Firstly, the issue of task difficulty in relation to the nature (i.e., content and automaticity) ofmotoric structures over which the observed and imagined information act. Eaves et al. (2016)discuss a dual-action simulation framework for conceptualizing previous empirical findings.However, such dual-action effects might vary for tasks internalized in different ways, for instancerhythmical window wiping (highly internalized) might show different dual-actions than a complexhigh jump skill (less well-internalized). Toner and Moran (2015) discuss the advantage of high-level athletes purposefully not committing their skills to totally automatic control as a strategy toensure scope for future adaptability. Indeed, applied research from the multi-action plan (MAP)perspective supports this notion. Data show that optimal performances are achieved by elite-levelathletes through both automatic and controlled execution processes (Bortoli et al., 2012), wherebyconsciously controlled motor processing can positively assist performances under psychologicalCarson and Collins Motor Imagery during Action Observationpressure and physical fatigue. Distinction between thesetwo optimal execution modes and their relative processingefficiency, therefore, offers complexity regarding the translationof fundamental, theory-driven research for use with populationssuch as athletes. When a task is so extremely familiar and simple(with limited degrees of freedom involved; e.g., finger pinching)it is possible that the observer quickly extracts sufficient relevantinformation from the model through retinal-dependent feedback(or attention), then switches to a state of intention whereby themotor representation is generated and retrieved through imageryprocesses (Wertheim, 1981; Loze et al., 1999). Of course, thiswould only be possible with a high degree of efficiency if therepresentation was easily accessible and well-established withinlong-term memory. If the skill is less well-established (perhapsdue to its complexity), it might be that the interplay is differentbetween observing and then imaging (e.g., watch–image–watch–image/watch; cf. Smith et al., 1998).As a related but distinct issue, it may also be beneficialto consider the observation-based review of errors, and whatassociated processes can bring to the learning process. Forexample, the generation of efference copy (what the movementshould feel like) which learners’ can then use for intentivecomparison and subsequent, enhanced learning (cf. Gallagher,2000). Of relevance, there is clear evidence that similar neuralmechanisms are involved in error detection for one’s ownmovements or when observing others (van Schie et al., 2004).Whether the case is of a well-known or being-learnt task,however, for observation and imagery to be optimized within theapplied sport setting, a better understanding of these processesacross complex moves are required.A second issue relates to what the observer focusseson during the observation and/or imagery process. This islikely important because studies have demonstrated differentlearning/performance effects when an athlete adopts differentattentional foci. In javelin throwing, MacPherson et al. (2008)found that focusing on holistic-rhythm resulted in a moreconsistent pattern of variability across kinematics whereasfocusing on a single element (e.g., fast arm) lowered thevariability of that component and increased the variability acrossothers; thus disrupting the balance of control. Focusing on“core components” of an action (those that are essential foroptimal performance), as advocated by the MAP, has beenshown to result in optimal performance levels even thoughthey are underpinned by an inefficient (according to the neuralefficiency hypothesis; Hatfield and Kerick, 2007), dissimilar stateof neural assemblies (desynchronized theta/alpha power) whencompared to automatic processing (Bertollo et al., 2016). A keyquestion here, then, is whether the nature of what is imagedwhilst observing changes the extent to which motor regions areactivated in the brain and thus, the representation formed (cf. vanSchie et al., 2004; Neuper et al., 2009). Given that this content willchange with experience, the case of skill refinement (adjusting analready established skill; Carson and Collins, 2011) is a particularcase for further consideration. As one ofmany issues, howwill thepattern of imagery/observation change when moving from well-established but suboptimum components to replace them withnew but comparatively unknown elements.Finally, there has been growing evidence to support thebeneficial impact on mental imagery when employing PETTLEP(Holmes and Collins, 2001) principles. On the basis thatobservation and imagery processes share, at the very least, similarneural pathways, could the benefits already shown by combiningimagery with observation be improved even further by attentionto these important elements? We suggest that examination ofsuch effects would be welcomed andwell-situated to inform othermore prominent areas of research within motor control; namely,that concerning an athlete’s focus of attention (Wulf, 2013).AUTHOR CONTRIBUTIONSHC and DC contributed equally to the ideas and writing of thearticle.REFERENCESBertollo, M., di Fronso, S., Filho, E., Conforto, S., Schmid, M., Bortoli, L., et al.(2016). Proficient brain for optimal performance: the MAP model perspective.PeerJ 4:e2082. doi: 10.7717/peerj.2082Bortoli, L., Bertollo, M., Hanin, Y., and Robazza, C. (2012). Striving for excellence:a multi-action plan intervention model for shooters. Psychol. Sport Exerc. 13,693–701. doi: 10.1016/j.psychsport.2012.04.006Carson, H. J., and Collins, D. (2011). Refining and regaining skills infixation/diversification stage performers: the five-a model. Int. Rev. Sport Exerc.Psychol. 4, 146–167. doi: 10.1080/1750984X.2011.613682Carson, H. J., and Collins, D. (2016). The fourth dimension: a motoric perspectiveon the anxiety–performance relationship. Int. Rev. Sport Exerc. Psychol. 9, 1–21.doi: 10.1080/1750984X.2015.1072231Cheng, W.-N. K., Hardy, L., and Markland, D. (2009). Toward a three-dimensional conceptualization of performance anxiety: rationale andinitial measurement development. Psychol. Sport Exerc. 10, 271–278.doi: 10.1016/j.psychsport.2008.08.001Christina, R. W. (1987). “Motor learning: Future lines of research,” in The CuttingEdge in Physical Education and Exercise Science Research, eds M. J. Safrit and H.M. Eckert (Champaign, IL: Human Kinetics), 26–41.Eaves, D. L., Riach, M., Holmes, P. S., and Wright, D. J. (2016). Motor imageryduring action observation: a brief review of evidence, theory and future researchopportunities. Front. Neurosci. 10:514. doi: 10.3389/fnins.2016.00514Gallagher, S. (2000). Philosophical conceptions of the self:implications for cognitive science. Trends Cogn. Sci. 4, 14–21.doi: 10.1016/S1364-6613(99)01417-5Hatfield, B. D., and Kerick, S. E. (2007). “The psychology of superior sportperformance: A cognitive and affective neuroscience perspective,” inHandbookof Sport Psychology, 3rd Edn., eds R. C. Eklund and G. Tenenbaum (Hoboken,NJ: John Wiley & Sons Inc), 84–109.Holmes, P. S., and Collins, D. J. (2001). The PETTLEP approach to motor imagery:a functional equivalence model for sport psychologists. J. Appl. Sport Psychol.13, 60–83. doi: 10.1080/10413200109339004Loze, G. M., Collins, D., and Shaw, J. C. (1999). EEG alpha rhythm,intention and oculomotor control. Int. J. Psychophysiol. 33, 163–167.doi: 10.1016/S0167-8760(99)00024-0MacPherson, A. C., Collins, D., and Morriss, C. (2008). Is what you think whatyou get? Optimizing mental focus for technical performance. Sport Psychol. 22,288–303. doi: 10.1123/tsp.22.3.288Neuper, C., Scherer, R., Wriessnegger, S., and Pfurtscheller, G. (2009). Motorimagery and action observation: modulation of sensorimotor brain rhythmsFrontiers in Human Neuroscience | www.frontiersin.org 2 January 2017 | Volume 11 | Article 25Carson and Collins Motor Imagery during Action Observationduring mental control of a brain-computer interface. Clin. Neurophysiol. 120,239–247. doi: 10.1016/j.clinph.2008.11.015Smith, D., Collins, D., and Hale, B. (1998). Imagery perspectives and Karateperformance. J. Sport Sci. 16, 103–104.Toner, J., and Moran, A. (2015). Enhancing performance proficiency at the expertlevel: considering the role of ‘somaesthetic awareness’. Psychol. Sport Exerc. 16,110–117. doi: 10.1016/j.psychsport.2014.07.006van Schie, H. T.,Mars, R. B., Coles,M. G.H., and Bekkering, H. (2004).Modulationof activity in medial frontal and motor cortices during error observation. Nat.Neurosci. 7, 549–554. doi: 10.1038/nn1239Wertheim, A. H. (1981). Occipital alpha activity as a measure of retinalinvolvement in oculomotor control. Psychophysiology 18, 432–439.doi: 10.1111/j.1469-8986.1981.tb02476.xWulf, G. (2013). Attentional focus and motor learning: a review of 15 years. Int.Rev. Sport Exerc. Psychol. 6, 77–104. doi: 10.1080/1750984X.2012.723728Conflict of Interest Statement: The authors declare that the research wasconducted in the absence of any commercial or financial relationships that couldbe construed as a potential conflict of interest.Copyright © 2017 Carson and Collins. This is an open-access article distributedunder the terms of the Creative Commons Attribution License (CC BY). The use,distribution or reproduction in other forums is permitted, provided the originalauthor(s) or licensor are credited and that the original publication in this journalis cited, in accordance with accepted academic practice. No use, distribution orreproduction is permitted which does not comply with these terms.Frontiers in Human Neuroscience | www.frontiersin.org 3 January 2017 | Volume 11 | Article 25

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