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Using Multimodal Hub Definitions to Assess Network Changes Associated with Alzheimer's Disease

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Using Multimodal Hub Definitions to Assess Network Changes Associated with Alzheimer's Disease
Green, Christian Miller
Alzheimer’s disease (AD) is a neurogenerative disease characterized by dementia, changes in behavior and cognition, and social isolation. Network studies into AD have shown inconclusive results regarding the disease’s effects on global metrics, but highly connected hub nodes are generally agreed to be primarily affected in the disease. One theory proposed to explain this is the activity dependent degeneration hypothesis, which speculates that hub nodes are primarily affected by Aβ and tau buildup due to their high intrinsic metabolic requirements which, over time, results in molecular strain and eventual damage. However, hubs have been described using a variety of different centrality metrics throughout the literature and these centralities likely capture different aspects of a node’s relationship to its network and its metabolic activity. To better understand different centrality metrics’ relationships to hub loss in AD, this study used a multimodal hub paradigm in which several centrality metrics were combined with the expectation that hubs identified by multiple centralities would be more highly active and thus more degraded in AD. Specifically, this study combined degree (Ki) and betweenness centrality (BC) as well as Ki and participation coefficient (PC). The modular consistency of the default mode network (DMN) was also compared across AD and cognitively normal (CN) groups to explore hub relationship with modularity. The results did not support the hypothesis that nodes identified by multiple centralities would be more different across groups, but they did show that high Ki nodes were consistently different while nodes identified only by high BC did not differ between groups. These differences were only observed in full brain analyses, not within the DMN was as expected. However, the scaled inclusivity analysis did show that DMN modular consistency was diminished within AD, replicating previous findings with a novel methodology.
Dagenbach, Dale (committee chair)
Hugenschmidt, Christina (committee member)
2020-05-29T08:36:11Z (accessioned)
2021-05-28T08:30:11Z (available)
2020 (issued)
Neuroscience (discipline)
2021-05-28 (terms)
http://hdl.handle.net/10339/96853 (uri)
en (iso)
Wake Forest University

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