White matter substrates of functional connectivity dynamics in the human brain

The contribution of structural connectivity to functional connectivity dynamics is still far from being elucidated. Herein, we applied track-weighted dynamic functional connectivity (tw-dFC), a model integrating structural, functional, and dynamic connectivity, on high quality diffusion weighted imaging and resting-state fMRI data from two independent repositories. The tw-dFC maps were analyzed using independent component analysis, aiming at identifying spatially independent white matter components which support dynamic changes in func-tional connectivity. Each component consisted of a spatial map of white matter bundles that show consistent fluctuations in functional connectivity at their endpoints, and a time course representative of such functional activity. These components show high intra-subject, inter-subject, and inter-cohort reproducibility. We provided also converging evidence that functional information about white matter activity derived by this method can cap-ture biologically meaningful features of brain connectivity organization, as well as predict higher-order cognitive performance.

Automated summary

This study used the track-weighted dynamic functional connectivity model to investigate the contribution of structural connectivity to functional connectivity dynamics. The results showed that this model can provide functional information about white matter activity, capturing meaningful features of brain connectivity organization and predicting higher-order cognitive performance.