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Electrophysiological evidence for cortical plasticity with movement repetition

Authors

  • Pascal Halder,

    1. Department of Child and Adolescent Psychiatry, Brain Mapping Research, University of Zurich, Neumünsterallee 9/Fach, CH-8032 Zurich, Switzerland
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  • Annette Sterr,

    1. Department of Child and Adolescent Psychiatry, Brain Mapping Research, University of Zurich, Neumünsterallee 9/Fach, CH-8032 Zurich, Switzerland
    2. School of Human Sciences, University of Surrey, Guildford GU2 7XH, Surrey, UK
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  • Silvia Brem,

    1. Department of Child and Adolescent Psychiatry, Brain Mapping Research, University of Zurich, Neumünsterallee 9/Fach, CH-8032 Zurich, Switzerland
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  • Kerstin Bucher,

    1. MR-Center, Department of Diagnostic Imaging, University Children's Hospital, Zurich, Switzerland
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  • Spyros Kollias,

    1. Institute of Neuroradiology, University Hospital Zurich, Zurich, Switzerland
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  • Daniel Brandeis

    1. Department of Child and Adolescent Psychiatry, Brain Mapping Research, University of Zurich, Neumünsterallee 9/Fach, CH-8032 Zurich, Switzerland
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Dr Daniel Brandeis, as above.
E-mail: brandeis@kjpd.unizh.ch

Abstract

The role of movement repetition and practice has been extensively studied as an aspect of motor skill learning but has rarely been investigated in its own right. As practice is considered a prerequisite for motor learning we expected that even the repetitive execution of a simple movement would rapidly induce changes in neural activations without changing performance. We used 64-channel event-related potential mapping to investigate these effects of movement repetition on corresponding brain activity in humans. Ten healthy right-handed young adults performed a power grip task under visual force control to ensure constant behaviour during the experimental session. The session consisted of two parts intersected by a break. For analysis each part was subdivided into two runs to control for potential attention or fatigue effects, which would be expected to disappear during the break. Microstate analysis revealed that distinct topographies and source configurations during movement preparation, movement execution and feedback integration are responsive to repetition. The observed patterns of changes differed for the three microstates, suggesting that different, repetition-sensitive neural mechanisms are involved. Moreover, this study clearly confirms that movement repetition, in the absence of skill learning, is capable of inducing changes in neural networks.

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