Abstract
Brain imaging of cerebral blood flow and glucose metabolism has been playing key roles in describing pathophysiology of Parkinson's disease (PD) and Huntington's disease (HD), respectively. Many biomarkers have been developed in recent years to investigate the abnormality in molecular substrate, track the time course of disease progression, and evaluate the efficacy of novel experimental therapeutics. A growing body of literature has emerged on neurobiology of these two movement disorders in resting states and in response to brain activation tasks. In this paper, we review the latest applications of these approaches in patients and normal volunteers at rest conditions. The discussions focus on brain mapping studies with univariate and multivariate statistical analyses on a voxel basis. In particular, we present data to validate the reproducibility and reliability of unique spatial covariance patterns related with PD and HD.
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