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Age- and Expertise-Related Differences of Sensorimotor Network Dynamics during Force Control.
- Source :
-
Neuroscience [Neuroscience] 2018 Sep 15; Vol. 388, pp. 203-213. Date of Electronic Publication: 2018 Jul 24. - Publication Year :
- 2018
-
Abstract
- Age-related deterioration of force control is evident on behavioral and neural levels. Extensive and deliberate practice can decrease these changes. This study focused on detecting electrophysiological correlates of age- and expertise-related differences in force control. We examined young (20-27 years) and late middle-aged (57-67 years) novices as well as late middle-aged experts in the field of fine motor control. Therefore, EEG data were recorded while participants performed a force maintenance task. Variability and complexity of force data were analyzed. To detect electrophysiological correlates, dynamic mode decomposition (DMD) was applied to EEG data. DMD allows assessing brain network dynamics by extracting electrode interrelations and their dynamics. Defining clusters of electrodes, we focused on sensorimotor and attentional networks. We confirmed that force control in late middle-aged novices was more variable and less complex than in other groups. Analysis of task-related overall network characteristics, showed a decrease within the α band and increase within low β, high β, and θ band. Compared to the other groups young novices presented a decreased α magnitude. High β magnitude was lower in late middle-aged novices than for other groups. Comparing left and right hands' performance, young novices showed higher low β magnitude for the left hand. Late middle-aged novices showed high values for both hands while late middle-aged experts showed higher values for the right than for their left hand. Activation of attentional networks was lower in late middle-aged experts compared to novices. These results may relate to different control strategies of the three groups.<br /> (Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 1873-7544
- Volume :
- 388
- Database :
- MEDLINE
- Journal :
- Neuroscience
- Publication Type :
- Academic Journal
- Accession number :
- 30048784
- Full Text :
- https://doi.org/10.1016/j.neuroscience.2018.07.025