PT  - JOURNAL ARTICLE
AU  - Basile, Gianpaolo Antonio
AU  - Bertino, Salvatore
AU  - Nozais, Victor
AU  - Bramanti, Alessia
AU  - Ciurleo, Rosella
AU  - Anastasi, Giuseppe Pio
AU  - Milardi, Demetrio
AU  - Cacciola, Alberto
TI  - Unsupervised clustering of track-weighted dynamic functional connectivity reveals white matter substrates of functional connectivity dynamics
AID  - 10.1101/2021.12.04.471233
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 2021.12.04.471233
4099  - http://biorxiv.org/content/early/2021/12/05/2021.12.04.471233.short
4100  - http://biorxiv.org/content/early/2021/12/05/2021.12.04.471233.full
AB  - The contribution of structural connectivity to functional connectivity dynamics is still far from being fully 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 functional 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 capture biologically meaningful features of brain connectivity organization, as well as predict higher-order cognitive performance.Competing Interest StatementThe authors have declared no competing interest.