The representation of motor (inter)action, states of action, and learning: Three perspectives on motor learning by way of imagery and execution

Frank C, Schack T (2017)
Frontiers in Psychology 8: 678.

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Zeitschriftenaufsatz | Veröffentlicht | Englisch
Abstract / Bemerkung
Learning in intelligent systems is a result of direct and indirect interaction with the environment. While humans can learn by way of different states of (inter)action such as the execution or the imagery of an action, their unique potential to induce brain- and mind-related changes in the motor action system is still being debated. The systematic repetition of different states of action (e.g., physical and/or mental practice) and their contribution to the learning of complex motor actions has traditionally been approached by way of performance improvements. More recently, approaches highlighting the role of action representation in the learning of complex motor actions have evolved and may provide additional insight into the learning process. In the present perspective paper, we build on brain-related findings and sketch recent research on learning by way of imagery and execution from a hierarchical, perceptual-cognitive approach to motor control and learning. These findings provide insights into the learning of intelligent systems from a perceptual-cognitive, representation-based perspective and as such add to our current understanding of action representation in memory and its changes with practice. Future research should build bridges between approaches in order to more thoroughly understand functional changes throughout the learning process and to facilitate motor learning, which may have particular importance for cognitive systems research in robotics, rehabilitation, and sports.
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Zeitschriftentitel
Frontiers in Psychology
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8
Artikelnummer
678
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Article Processing Charge funded by the Deutsche Forschungsgemeinschaft and the Open Access Publication Fund of Bielefeld University.
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Frank C, Schack T. The representation of motor (inter)action, states of action, and learning: Three perspectives on motor learning by way of imagery and execution. Frontiers in Psychology. 2017;8: 678.
Frank, C., & Schack, T. (2017). The representation of motor (inter)action, states of action, and learning: Three perspectives on motor learning by way of imagery and execution. Frontiers in Psychology, 8, 678. doi:10.3389/fpsyg.2017.00678
Frank, C., and Schack, T. (2017). The representation of motor (inter)action, states of action, and learning: Three perspectives on motor learning by way of imagery and execution. Frontiers in Psychology 8:678.
Frank, C., & Schack, T., 2017. The representation of motor (inter)action, states of action, and learning: Three perspectives on motor learning by way of imagery and execution. Frontiers in Psychology, 8: 678.
C. Frank and T. Schack, “The representation of motor (inter)action, states of action, and learning: Three perspectives on motor learning by way of imagery and execution”, Frontiers in Psychology, vol. 8, 2017, : 678.
Frank, C., Schack, T.: The representation of motor (inter)action, states of action, and learning: Three perspectives on motor learning by way of imagery and execution. Frontiers in Psychology. 8, : 678 (2017).
Frank, Cornelia, and Schack, Thomas. “The representation of motor (inter)action, states of action, and learning: Three perspectives on motor learning by way of imagery and execution”. Frontiers in Psychology 8 (2017): 678.
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94 References

Daten bereitgestellt von Europe PubMed Central.

Representation and learning in motor action: bridges between experimental research and cognitive robotics.
Schack T., Ritter H.., 2013
The influence of visual feedback on the mental representation of gait in patients with THR: a new approach for an experimental rehabilitation strategy.
Schega L, Bertram D, Folsch C, Hamacher D, Hamacher D., Appl Psychophysiol Biofeedback 39(1), 2014
PMID: 24442243

Schmidt R., Wrisberg C.., 2008

Schmidt R., Lee T.., 2011
The mental representation of the human gait in young and older adults.
Stockel T, Jacksteit R, Behrens M, Skripitz R, Bader R, Mau-Moeller A., Front Psychol 6(), 2015
PMID: 26236249
MEG Multivariate Analysis Reveals Early Abstract Action Representations in the Lateral Occipitotemporal Cortex.
Tucciarelli R, Turella L, Oosterhof NN, Weisz N, Lingnau A., J. Neurosci. 35(49), 2015
PMID: 26658857
Hierarchical organization of action encoding within the human brain.
Turella L., Rumiati R., Lingnau A.., 2016
Imaging brain plasticity during motor skill learning.
Ungerleider LG, Doyon J, Karni A., Neurobiol Learn Mem 78(3), 2002
PMID: 12559834
Gaze control in putting.
Vickers JN., Perception 21(1), 1992
PMID: 1528699
Visual control when aiming at a far target.
Vickers J.., 1996
“Motor skill learning and its neurophysiology,” in
Wadden K., Borich M., Boyd L.., 2012
Functional equivalence or behavioural matching: a critical reflection on 15 years of research using the PETTLEP model of motor imagery.
Wakefield C., Smith D., Moran A., Holmes P.., 2013
Principles of sensorimotor learning.
Wolpert DM, Diedrichsen J, Flanagan JR., Nat. Rev. Neurosci. 12(12), 2011
PMID: 22033537
Decoding actions at different levels of abstraction.
Wurm MF, Lingnau A., J. Neurosci. 35(20), 2015
PMID: 25995462
Imagined and executed actions in the human motor system: testing neural similarity between execution and imagery of actions with a multivariate approach.
Zabicki A., de B., Zentgraf K., Stark R., Munzert J., Krüger B.., 2016
Motor imagery learning modulates functional connectivity of multiple brain systems in resting state.
Zhang H, Long Z, Ge R, Xu L, Jin Z, Yao L, Liu Y., PLoS ONE 9(1), 2014
PMID: 24465577
Parallel alterations of functional connectivity during execution and imagination after motor imagery learning.
Zhang H, Xu L, Zhang R, Hui M, Long Z, Zhao X, Yao L., PLoS ONE 7(5), 2012
PMID: 22629308

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