However, this AD-related network disorganization may be modified with disease progression, as demonstrated by two recent longitudinal customer review studies that found that the increased connectivity was present early in the diseases course but declines in later stages [53,54]. 2. Large-scale network analysis Seed-based network detection (such as seed-to-brain connectivity) and ICA-based network detection are limited since they can be used to study specific networks based on a priori knowledge. For this reason, large-scale network analyses are becoming increasingly popular to investigate the functional connectivity across the entire brain in an unbiased fashion.

The simplest large-scale network analyses have used the 116 anatomically defined regions in the Automated Anatomical Labeling (AAL) atlas [55] and estimated correlations between any two regions to obtain a connectivity matrix of 116 ?? 116 that represents connectivity between all gross anatomical regions of the brain (similar to the example shown in Figure ?Figure3).3). Wang and colleagues showed that there is decreased anterior-posterior disconnection in AD on the basis of these 116 ?? 116 correlation matrices [56] and that correlations between 22 of the task-positive and task-negative regions can be used to distinguish patients with AD from CN patients with an accuracy of 83% [57]. Studies have also used these matrices and found patterns of abnormal interregional correlations in widely dispersed brain areas in amnestic MCIs [58,59].

Furthermore, the information in these matrices can be condensed into global connectivity measures by using graph theory and network analysis (as mentioned Cilengitide above) and can be applied to detect the disruption in the organization of the functional brain networks in AD (as presented in [60,61]). Supekar and colleagues [61] found that there is disruption of local connectivity in the brain (specifically, in the hippocampus) reflected by low-clustering coefficients in AD when compared with CN subjects. Sanz-Arigita and colleagues [60] found, on the other hand, that the primary effect of AD was on the decreased long-distance connectivity of the frontal and caudal brain regions. Until recently, anatomically defined selleckbio regions have been used to investigate large-scale networks of the brain. However, using anatomically defined regions has the following drawbacks: (a) the brain has a complex functional architecture and the functional units are smaller in size, making spatial averaging of time courses over large structural anatomy very unreliable; and (b) anatomical regions of interest may not always correspond to the functional organization of networks.