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Characterization of the default mode functional connectivity in normal aging and Alzheimer's disease: An approach combining entropy-based and graph theoretical measurements

We have investigated functional connectivity of the default mode network (DMN) in normal aging and Alzheimer's disease (AD) using resting state fMRI at 3T. Images from young and elderly controls, and patients with AD were processed using spatial independent component analysis to identify the DMN. Functional connectivity was quantified using integration and indices derived from graph theory. Four DMN sub-systems were identified: Frontal (medial frontal, superior frontal), Parietal (precuneus-posterior cingulate, lateral parietal), Temporal (medial temporal cortices), and Hippocampal (left and right). There was a decrease in antero-posterior interactions (lower global efficiency), but increased interactions within the Frontal and Parietal sub-systems (higher local clustering) in elderly compared to young controls. The decreased antero-posterior integration was more pronounced in AD patients compared to elderly controls, particularly in the precuneus-posterior cingulate region. The approach allows for a complete characterization of connectivity changes and could be applied to other resting state networks and pathologies.