Age- and Expertise-Related Differences of Sensorimotor Network Dynamics during Force Control. (15th September 2018)

• Record Type: Journal Article
• Authors: Vieluf, Solveig; Mora, Karin; Gölz, Christian; Reuter, Eva-Maria; Godde, Ben; Dellnitz, Michael; Reinsberger, Claus; Voelcker-Rehage, Claudia
• Is Part Of: Neuroscience. Volume 388(2018)
• Page Start: 203
• Page End: 213
• Publication Date: 2018-09-15
• Subjects: DMD dynamic mode decomposition -- FFT fast Fourier transform -- MSE multi-scale entropy -- PCA principal component analysis -- YN young novices -- LMN late middle-aged novices -- LME late middle-aged experts -- MVC maximum voluntary contraction; aging -- fine motor expertise -- variability -- sensorimotor maps -- dynamic mode decomposition -- attentional networks; Neurochemistry -- Periodicals; Neurophysiology -- Periodicals; Neurology -- Periodicals; Neurochimie -- Périodiques; Neurophysiologie -- Périodiques; Neurochemistry; Neurophysiology; Electronic journals; Periodicals; Electronic journals; 612.8
• DOI: 10.1016/j.neuroscience.2018.07.025
• Languages: English
• ISSNs: 0306-4522

Abstract

Highlights: Experts were less variable and more complex than novices of their age. EEG-data indicated that young novices specifically activate sensorimotor network. Older novices relied more on interrelation of several networks. DMD analysis suggests that experts more efficiently use and integrate information. 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.