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Improved Neural Control of Movements Manifests in Expertise-Related Differences in Force Output and Brain Network Dynamics.
- Source :
-
Frontiers in physiology [Front Physiol] 2018 Nov 21; Vol. 9, pp. 1540. Date of Electronic Publication: 2018 Nov 21 (Print Publication: 2018). - Publication Year :
- 2018
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Abstract
- It is well-established that expertise developed through continuous and deliberate practice has the potential to delay age-related decline in fine motor skills. However, less is known about the underlying mechanisms, that is, whether expertise leads to a higher performance level changing the initial status from which age-related decline starts or if expertise-related changes result in qualitatively different motor output and neural processing providing a resource of compensation for age-related changes. Thus, as a first step, this study aims at a better understanding of expertise-related changes in fine motor control with respect to force output and respective electrophysiological correlates. Here, using a multidimensional approach, we investigated fine motor control of experts and novices in precision mechanics during the execution of a dynamic force control task. On the level of force output, we analyzed precision, variability, and complexity. We further used dynamic mode decomposition (DMD) to analyze the electrophysiological correlates of force control to deduce brain network dynamics. Experts' force output was more precise, less variable, and more complex. Task-related DMD mean mode magnitudes within the α-band at electrodes over sensorimotor relevant areas were reduced in experts, and lower DMD mean mode magnitudes related to the force output in novices. Our results provide evidence for expertise dependent central adaptions with distinct and more complex organization and decentralization of sensorimotor subsystems. Results from our multidimensional approach can be seen as a step forward in understanding expertise-related changes and exploiting their potential as resources for healthy aging.
Details
- Language :
- English
- ISSN :
- 1664-042X
- Volume :
- 9
- Database :
- MEDLINE
- Journal :
- Frontiers in physiology
- Publication Type :
- Academic Journal
- Accession number :
- 30519188
- Full Text :
- https://doi.org/10.3389/fphys.2018.01540