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.

White matter substrates of functional connectivity dynamics in the human brain

Basile, GA
Primo
;
Bertino, S
Secondo
;
Bramanti, A;Ciurleo, R;Anastasi, GP;Milardi, D
Penultimo
;
Cacciola, A
Ultimo
2022-01-01

Abstract

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.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11570/3240751
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