| dc.description.abstract | In this study, we aim to examine age-related network changes in terms of the motor network architecture and the frequency content of the ensuring dynamics using Dynamic Causal Modelling for induced responses. In particular, we wanted to test whether there are any differences with aging in force modulation in the motor network, comprising bilateral primary motor areas (M1), premotor areas (PM), and supplemental motor area (SMA) when performing 15% and 45% of Maximum Voluntary Contraction (MVC) of hand grips.
14 healthy right-handed subjects, 8 for the younger group and 6 for the older group, with the average age of 23.25±2.05 and 71.17±9.79 years old, respectively, were recruited in this study. Before the experiment, subjects were asked to generate their own MVC for the determination of subject-specific 15% and 45% force levels. 50 times practice for each force level was performed with the visual feedback of grip level for them to memorize the force level. During the experiment the subjects were asked to perform 100 times grips both two levels of force without visual feedback which was paced by visual cue of randomized order of force level. In this session, only 10% force error was permitted. The inter-movement interval is 2±0.5 seconds to avoid the anticipating effect and for each trial there has 3 seconds break to avoid muscle fatigue. 12 channels electroencephalogram (EEG) with 2000 Hz sampling rate and right-handed grip force with 40 Hz sampling rate were recorded during the task. The EEG data were epoched form -1500 to +1000 ms where the time zero indicated the grip force level at 5% MVC. The epoched data were processes by Independent Component Analysis (ICA) method and Empirical Mode Decomposition (EMD) and filtered with 0.1~35 Hz band-pass filter to remove the EOG artifact. The EOG-free data then entered into DCM of induced responses analysis.
Behavior result showed older subjects had longer reaction and duration time (P<0.01). Older subjects have increase coupling strength and more complex coupling than younger subjects in the motor network. The Inter-regional communications of older brain tend to use more frequency band. When executing grip task the motor cortex activity became more symmetric in elders while the youngers tend to have more activation in the left brain. Force modulation has significant effect in the coupling between supplemental motor area and primary motor cortex. Specifically, the communication from supplemental motor area to primary motor cortex engaged more Beta to low Gamma band when force level increases.
In conclusion, we first engineered a new method that combines ICA and EMD to remove artifact more accurately. In addition, we observed the impact of aging on force modulation of motor network. We believe that the outcome of this study could benefit the studies of motor recovery during rehabilitation after stroke in the future.
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