Jiaqi Ding

Song Wang, Zhenyu Lei, Zhen Tan et al.

Functional Magnetic Resonance Image (fMRI) is commonly employed to study human brain activity, since it offers insight into the relationship between functional fluctuations and human behavior. To enhance analysis and comprehension of brain activity, Graph Neural Networks (GNNs) have been widely applied to the analysis of functional connectivities (FC) derived from fMRI data, due to their ability to capture the synergistic interactions among brain regions. However, in the human brain, performing complex tasks typically involves the activation of certain pathways, which could be represented as paths across graphs. As such, conventional GNNs struggle to learn from these pathways due to the long-range dependencies of multiple pathways. To address these challenges, we introduce a novel framework BrainMAP to learn Multiple Activation Pathways in Brain networks. BrainMAP leverages sequential models to identify long-range correlations among sequentialized brain regions and incorporates an aggregation module based on Mixture of Experts (MoE) to learn from multiple pathways. Our comprehensive experiments highlight BrainMAP's superior performance. Furthermore, our framework enables explanatory analyses of crucial brain regions involved in tasks. Our code is provided at https://github.com/LzyFischer/Graph-Mamba.

Tingting Dan, Xinwei Huang, Jiaqi Ding et al.

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.