  Emerging evidence shows that cognitive deficits in Alzheimer disease (AD) are
associated with disruptions in brain functional connectivity. Thus, the
identification of alterations in AD functional networks has become a topic of
increasing interest. However, to what extent AD induces disruption of the
balance of local and global information processing in the human brain remains
elusive. The main objective of this study is to explore the dynamic topological
changes of AD networks in terms of brain network segregation and integration.
We used electroencephalography (EEG) data recorded from 20 participants (10 AD
patients and 10 healthy controls) during resting state. Functional brain
networks were reconstructed using EEG source connectivity computed in different
frequency bands. Graph theoretical analyses were performed assess differences
between both groups. Results revealed that AD networks, compared to networks of
age matched healthy controls, are characterized by lower global information
processing (integration) and higher local information processing (segregation).
Results showed also significant correlation between the alterations in the AD
patients functional brain networks and their cognitive scores. These findings
may contribute to the development of EEG network-based test that could
strengthen results obtained from currently used neurophysiological tests in
neurodegenerative diseases.
