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Title: Coupled pathology appearance and propagation models of neurodegeneration. Session: Oral Session Speaker: Tiantian He Abstract: Two main approaches driven by brain connectivity are used to investigate the evolving pattern of neurodegenerative pathology over human brains: i) appearance of pathology and ii) network propagation. The former states that pathology appears spontaneously in brain regions, and the pattern is relevant to various network metrics [10]. The latter uses the network as a substrate for disease spreading from specific epicenter(s) via, for example, network diffusion models (NDM) [5,9]. However, the complexity and heterogeneity of neurodegenerative conditions suggests that multiple processes may contribute and vary among individuals. Garbarino et al. [1] showed that a linear combination of patterns derived from various network-based appearance and propagation models described atrophy patterns better than any individual model. However, that work does not consider interaction of such processes. In this work, we combine pathology appearance and propagation more deeply via models that simultaneously propagate pathology over the network gradually as it appears according to network metrics. We develop four coupled models, which improve the data fitting.