用脑图谱数据揭示白质通路如何支持大脑远距离协同活动。
A Data-Driven Method to Map the Functional Organisation of Human Brain White Matter
- 结合扩散与功能磁共振，通过轨迹动态功能连接建模白质通路的动态耦合。
- 发现老年人白质通路功能耦合强度和时间变异性普遍下降。
- 特定通路（如控制、默认模式系统）中介了年龄与认知能力的关系。
大脑白质由轴突束组成，支持长程神经通信。尽管扩散MRI（dMRI）可通过纤维追踪实现对这些通路的精细映射，但白质通路如何直接促进大规模神经同步仍不明确。我们开发了一种数据驱动框架，整合dMRI与功能MRI（fMRI），以建模白质轨迹所支持的动态耦合。具体地，采用轨迹动态功能连接（Track-DFC）刻画由单条白质轨迹连接的远端灰质之间的功能耦合。基于独立成分分析并结合k-medoids聚类，从人类连接组计划（HCP）年轻成人队列中提取出功能一致的白质轨迹簇。应用于HCP老龄化队列时，这些簇表现出广泛的年龄相关性下降，包括功能耦合强度和时间变异性降低。重要的是，涵盖控制、默认模式、注意和视觉系统间连接的特定簇显著中介了年龄与认知表现之间的关系。这些发现描绘了白质轨迹的功能组织结构，并为研究脑衰老与认知衰退提供了有力工具。
原文摘要 · Abstract (English)
The white matter of the brain is organised into axonal bundles that support long-range neural communication. Although diffusion MRI (dMRI) enables detailed mapping of these pathways through tractography, how white matter pathways directly facilitate large-scale neural synchronisation remains poorly understood. We developed a data-driven framework that integrates dMRI and functional MRI (fMRI) to model the dynamic coupling supported by white matter tracks. Specifically, we employed track dynamic functional connectivity (Track-DFC) to characterise functional coupling of remote grey matter connected by individual white matter tracks. Using independent component analysis followed by k-medoids clustering, we derived functionally-coherent clusters of white matter tracks from the Human Connectome Project young adult cohort. When applied to the HCP ageing cohort, these clusters exhibited widespread age-related declines in both functional coupling strength and temporal variability. Importantly, specific clusters encompassing pathways linking control, default mode, attention, and visual systems significantly mediated the relationship between age and cognitive performance. Together, these findings depict the functional organisation of white matter tracks and provide a powerful tool to study brain ageing and cognitive decline.
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