[Network analyses in neuroimaging studies].

Neurons are anatomically and physiologically connected to each other, and these connections are involved in various neuronal functions. Multiple important neural networks involved in neurodegenerative diseases can be detected using network analyses in functional neuroimaging. First, the basic methods and theories of voxel-based network analyses, such as principal component analysis, independent component analysis, and seed-based analysis, are described. Disease- and symptom-specific brain networks have been identified using glucose metabolism images in patients with Parkinson's disease. These networks enable us to objectively evaluate individual patients and serve as diagnostic tools as well as biomarkers for therapeutic interventions. Many functional MRI studies have shown that "hub" brain regions, such as the posterior cingulate cortex and medial prefrontal cortex, are deactivated by externally driven cognitive tasks; such brain regions form the "default mode network." Recent studies have shown that this default mode network is disrupted from the preclinical phase of Alzheimer's disease and is associated with amyloid deposition in the brain. Some recent studies have shown that the default mode network is also impaired in Parkinson's disease, whereas other studies have shown inconsistent results. These incongruent results could be due to the heterogeneous pharmacological status, differences in mesocortical dopaminergic impairment status, and concomitant amyloid deposition. Future neuroimaging network analysis studies will reveal novel and interesting findings that will uncover the pathomechanisms of neurological and psychiatric disorders.