  In Alzheimer's disease (AD), the progressive atrophy leads to aberrant
network reconfigurations both at structural and functional levels. In such
network reorganization, the core and peripheral nodes appear to be crucial for
the prediction of clinical outcome due to their ability to influence
large-scale functional integration. However, the role of the different types of
brain connectivity in such prediction still remains unclear. Using a multiplex
network approach we integrated information from DWI, fMRI and MEG brain
connectivity to extract an enriched description of the core-periphery structure
in a group of AD patients and age-matched controls. Globally, the regional
coreness - i.e., the probability of a region to be in the multiplex core -
significantly decreased in AD patients as a result of the randomization process
initiated by the neurodegeneration. Locally, the most impacted areas were in
the core of the network - including temporal, parietal and occipital areas -
while we reported compensatory increments for the peripheral regions in the
sensorimotor system. Furthermore, these network changes significantly predicted
the cognitive and memory impairment of patients. Taken together these results
indicate that a more accurate description of neurodegenerative diseases can be
obtained from the multimodal integration of neuroimaging-derived network data.
