A Data-Driven Method to Map the Functional Organisation of Human Brain White Matter
This work addresses the challenge of mapping brain white matter's functional organization for neuroscience and aging research, offering a tool to study cognitive decline, though it is incremental as it builds on existing MRI methods.
The researchers tackled the problem of understanding how white matter pathways facilitate large-scale neural synchronization by developing a data-driven framework integrating diffusion and functional MRI, which revealed age-related declines in functional coupling and identified specific clusters mediating the relationship between age and cognitive performance in human brain studies.
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.