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A graph theory approach to detect age and Alzheimer’s disease related changes to structural neural networks

Changes to the structural and functional integrity of brain systems are a prominent feature of both Alzheimer’s disease (AD) and the normal ageing process. Recently, research in human brain connectomics has seen many studies adopting graph theoretical methods to explore brain network topology. However, conflicting evidence surrounding disease‐related alterations in structural covariance networks, leaves a gap in our understanding of how system level structural changes may distinguish healthy ageing from disease. The present study, therefore, aimed to establish differences in structural network topology between the stages of healthy ageing and in differing types and severities of cognitive decline.