Improving fMRI in Parkinson's disease by accounting for realistic motor output

Abstract

In Parkinson's disease (PD), the motor loop functioning and the patients’ motor output are unpredictable, due to brain compensatory mechanisms initiated up to decades before diagnosis. Consequently, the accuracy of motor tasks during fMRI is impeded, and deviations of the movement performance affect results. Kinematic modeling based on simultaneous measurements with MR-compatible gloves has been previously proposed as means to address this problem and outperform conventional boxcar modeling (Standard). Here, we adopted this approach in a larger cohort along with conservative statistics employing family-wise error (FWE) correction at the voxel level (p< 0.05) to be less prone to produce false positives