TY - JOUR
T1 - Disrupted core-periphery structure of multimodal brain networks in Alzheimer’s disease
AU - Guillon, Jeremy
AU - Chavez, Mario
AU - Battiston, Federico
AU - Attal, Yohan
AU - La Corte, Valentina
AU - de Schotten, Michel Thiebaut
AU - Dubois, Bruno
AU - Schwartz, Denis
AU - Colliot, Olivier
AU - Fallani, Fabrizio De Vico
N1 - Publisher Copyright:
© 2019 Massachusetts Institute of Technology Published under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
PY - 2019/1/1
Y1 - 2019/1/1
N2 - 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 because of 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—that is, the probability of a region to be in the multiplex core—significantly decreased in AD patients as result of a random disconnection 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.
AB - 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 because of 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—that is, the probability of a region to be in the multiplex core—significantly decreased in AD patients as result of a random disconnection 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.
KW - Brain connectivity
KW - DWI
KW - FMRI
KW - MEG
KW - Multilayer network theory
KW - Neurodegenerative diseases
UR - http://www.scopus.com/inward/record.url?scp=85082860818&partnerID=8YFLogxK
U2 - 10.1162/netn_a_00087
DO - 10.1162/netn_a_00087
M3 - Article
AN - SCOPUS:85082860818
SN - 2472-1751
VL - 3
SP - 635
EP - 652
JO - Network Neuroscience
JF - Network Neuroscience
IS - 2
ER -