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Understanding Mechanistic Role of Structural and Functional Connectivity in Tau Propagation Through Multi-Layer Modeling

arXiv 2510.20148 ↗First posted 23 Oct 2025cs.LG math.DS physics.med-phcited by 0

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Abstract (arXiv)

Emerging neuroimaging evidence shows that pathological tau proteins build up along specific brain networks, suggesting that large-scale network architecture plays a key role in the progression of Alzheimer's disease (AD). However, how structural connectivity (SC) and functional connectivity (FC) interact to influence tau propagation remains unclear. Leveraging an unprecedented volume of longitudinal neuroimaging data, we examine SC-FC interactions through a multi-layer graph diffusion model. Beyond showing that connectome architecture constrains tau spread, our model reveals a regionally asymmetric contribution of SC and FC. Specifically, FC predominantly drives tau spread in subcortical areas, the insula, frontal and temporal cortices, whereas SC plays a larger role in occipital, parietal, and limbic regions. The relative dominance of SC versus FC shifts over the course of disease, with FC generally prevailing in early AD and SC becoming primary in later stages. Spatial patterns of SC- and FC-dominant regions strongly align with the regional expression of AD-associated genes involved in inflammation, apoptosis, and lysosomal function, including CHUK (IKK-alpha), TMEM106B, MCL1, NOTCH1, and TH. In parallel, other non-modifiable risk factors (e.g., APOE genotype, sex) and biological mechanisms (e.g., amyloid deposition) selectively reshape tau propagation by shifting dominant routes between anatomical and functional pathways in a region-specific manner. Findings are validated in an independent AD cohort.

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References · 5

  1. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,282
  2. 2020Simple and Deep Graph Convolutional Networkscited by 857
  3. 2021How Attentive are Graph Attention Networks?cited by 818
  4. 2020Liquid Time-constant Networkscited by 160
  5. 2013Highly comparative time-series analysis: The empirical structure of time series and their methodscited by 30

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