Alzheimer＇s disease （AD） is the most common type of dementia, comprising an estimated 60-80% of all dementia cases. It is clinically characterized by impairments of memory and other cognitive functions. Previous studies have demonstrated that these impairments are associated with abnormal structural and functional connections among brain regions, leading to a disconnection concept of AD. With the advent of a combination of non-invasive neuroimaging （structural magnetic resonance imaging （MRI）, diffusion MRI, and functional MRI） and neurophysiological techniques （electroencephalography and magnetoencephaJography） with graph theoretical analysis, recent studies have shown that patients with AD and mild cognitive impairment （MCI）, the prodromal stage of AD, exhibit disrupted topological organization in large-scale brain networks （i.e., connectomics） and that this disruption is significantly correlated with the decline of cognitive functions. In this review, we summarize the recent progress of brain connectomics in AD and MCI, focusing on the changes in the topological organization of large-scale structural and functional brain networks using graph theoretical approaches. Based on the two different perspectives of information segregation and integration, the literature reviewed here suggests that AD and MCI are associated with disrupted segregation and integration in brain networks. Thus, these connectomics studies open up a new window for understanding the pathophysiological mechanisms of AD and demonstrate the potential to uncover imaging biomarkers for clinical diagnosis and treatment evaluation for this disease.
