Resting metabolic connectivity in Alzheimer's disease

Metabolic connectivity analysis of resting ¹⁸F-FDG PET is based on the assumption that brain regions whose metabolism is significantly correlated at rest are functionally associated and that the strength of the association is proportional to the magnitude of the correlation coefficient. Therefore, this method could be used to evaluate connectivity networks independently on the basis of performance in specific tasks. Published studies have provided evidence that metabolic connectivity substantially overlaps underlying anatomical pathways and depends on the location of the analyzed regions, but is not influenced by their size. The present review focuses on the methods and meaning of resting inter-regional correlation analysis of cerebral metabolic rate of glucose consumption in Alzheimer's disease. Accordingly, we describe the evolution of analytical tools from the correlation with a single region of interest to a voxel-based statistical parametric mapping-based approach. We also discuss the pathophysiological implications of metabolic connectivity studies both for Alzheimer-related disconnection syndrome and for default-mode network impairment and compensation mechanisms.