Abstract

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.

Highlights

  • The brain is a complex network where differently specialized areas are anatomically and functionally connected

  • We considered multiple brain networks derived from diffusion-weighted images (DWI), functional MRI (fMRI), and MEG data recorded in a group of Alzheimer’s disease (AD) patients and age-matched healthy controls

  • Because we do not know a priori the best combination, we derived the optimal c∗ by using a data-driven approach that efficiently explores the parameter space to maximize the difference between AD and healthy agematched control (HC) regional coreness

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Summary

Introduction

The brain is a complex network where differently specialized areas are anatomically and functionally connected. Because of such interconnected structure, focal damages can affect the rest of the network through the interruption of communication pathways. Many neurological disorders affecting language, motor, and sensory abilities are often due to a disconnection syndrome caused by the anatomical connectivity breakdown between the relevant brain areas (Geschwind, 1965; Schmahmann & Pandya, 2008). Empirical evidence has shown that Alzheimer’s disease (AD) patients with severe motor and cognitive impairments exhibited anatomical disconnections among regions between cerebral hemispheres that resemble those observed in split-brain subjects (Delbeuck, Collette, & Van der Linden, 2007; Lakmache, Lassonde, Gauthier, Frigon, & Lepore, 1998). Functional connectivity alterations within and between hemispheres have been reported in both AD (Adler, Brassen, & Jajcevic, 2003; Babiloni et al, 2009; Blinowska et al, 2016; Sankari, 2010) and PD (Dubbelink et al, 2013; Luo et al, 2015), suggesting their potential role in early diagnosis

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