With the advent of new methods of network analysis, we have utilized metabolic data acquired through positron emission tomography (PET) to identify disease-related patterns of functional pathology in the movement disorders. In Parkinson's disease (PD), we have used [(18)F]-fluorodeoxyglucose (FDG)/PET to identify a disease-related regional metabolic covariance pattern characterized by lentiform and thalamic hypermetabolism associated with regional metabolic decrements in the lateral premotor cortex, the supplementary motor area, the dorsolateral prefrontal cortex, and the parieto-occipital association regions. The expression of this network is modulated in a predictable fashion by levodopa therapy and by stereotaxic interventions for PD.We have extended this network analytical approach from studies of glucose metabolism in the resting state to dynamic studies of brain activation during motor performance. These PET studies utilized [(15)O]-water (H(2) (15)O) to measure cerebral blood flow activation responses during the execution of simple and complex motor tasks. In addition to the modulation of abnormal resting metabolic networks, effective PD therapy can enhance brain activation responses during motor execution, with specific regional associations with improvements in timing and spatial accuracy.This approach is also useful in identifying specific brain networks mediating the learning of sequential information. We have found that the normal relationship between brain networks and learning performance are altered in the earliest stages of PD with a functional shift from striatal to cortical processing. Brain activation PET studies during therapeutic interventions for PD demonstrate how normal brain-behavior relationships can be restored with successful therapy. Thus, functional brain imaging with network analysis can provide insights into the mechanistic basis of basal ganglia disorders and their treatment.