A1274
Title: Sex-specific topological structure associated with dementia via latent space estimation
Authors: Selena Wang - Indiana University School of Medicine (United States) [presenting]
Abstract: Sex-specific topological structure associated with typical Alzheimer's disease (AD) dementia is investigated using a novel state-of-the-art latent space estimation technique. A probabilistic approach for latent space estimation extends current multiplex network modeling approaches and captures the higher-order dependence in functional connectomes by preserving transitivity and modularity structures. Sex differences are found in network topology, with females showing more default mode network (DMN)-centered hyperactivity, whereas males show more limbic system (LS)-centered hyperactivity while both show DMN-centered hypoactivity. Centrality plays are found to have an important role in dementia-related dysfunction, with a stronger association between connectivity changes and regional centrality in females than in males. The contribution to current literature is that it provides a more comprehensive picture of dementia-related neurodegeneration linking centrality, network segregation, and DMN-centered changes in functional connectomes and how these components of neurodegeneration differ between the sexes.
