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Multilayer Approach to Brain Connectivity in Alzheimer’s Disease

Jérémy Guillon 1
1 ARAMIS - Algorithms, models and methods for images and signals of the human brain
SU - Sorbonne Université, Inria de Paris, ICM - Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute
Abstract : Alzheimer’s disease causes alterations of the brain networks structure and function that can be modelized by a brain connectivity analyse. We proposed a multi-layer approach to analyse multi-frequency and multimodal brain networks built from magnetoencephalographic (MEG) recordings, functional (fMRI) or diffusion-weighted magnetic resonance imaging (DWI). Main results showed the existence of previously undefined type of hubs that are inter-frequency hubs; identified thanks to their multi-participation coefficient (MPC) computed from a brain connectivity network with a multi-frequency multiplex topology. These hubs are impacted by Alzheimer’s disease, which reduces their naturally high ability to integrate information propagating through different frequency bands. We also generalized the concept of core-periphery structure to multilayer networks to be able to apply it to a multimodal brain connectivity model that combines structural and functional networks in a single multiplex topology. Hence, we could identify, from a systemic point of view, the most important regions at the scale of the entire brain and study their alteration in patients with Alzheimer’s disease. Therefore, this thesis expose how multilayer networks applied to brain connectivity can help in understanding neurodegenerative diseases such as Alzheimer’s disease.
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Jérémy Guillon. Multilayer Approach to Brain Connectivity in Alzheimer’s Disease. Computer science. Sorbonne Université, 2018. English. ⟨NNT : 2018SORUS305⟩. ⟨tel-02864838⟩

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