Using EMG and an Accelerometer to Capture Essential and Dystonic Tremor in an fMRI Model

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Essential Tremor and Dystonic Tremor are disorders with an involuntary action tremor. Previous studies found that the tremor was linked to the cerebello-thalamo-cortical network. Some of these studies used EMG to uncover the tremor network, but their model did not resolve the issue of high correlation between the task and EMG regressor. The current study aims to find an fMRI model with accelerometer and EMG data, that adequately captures tremor-related brain activity during posture. We looked at 6 potential models, with the winning model containing a blocked task regressor (reflecting posture), a parametric modulation regressor based on accelerometer data (reflecting power over time at peak tremor frequency), two stick regressors with the onsets and offsets of the motor task (reflecting lifting and lowering of the arm) and two noise regressors (averaged signal intensity of each scan and the time course of bilateral ventricles). For the task, onset and offset contrasts we found a convincing motor network. However, with the contrast at the parametric modulation, we could not reproduce the network that was previously found. Results do indicate that tremor-related activity might still be ingrained in the task-regressor. This might have to do with the cut off for the task, the variability of the tremor in the participants, and the signal-to-noise ratio of the equipment. Still, our results have challenged previously reported findings by separating posture from active hand movement. The model provides a base for analysing tremor fMRI data, but could be further optimized with additional tremor information.
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