Predicting human resting-state functional connectivity from structural connectivity

Détails

ID Serval
serval:BIB_FBC8B589621D
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Predicting human resting-state functional connectivity from structural connectivity
Périodique
Proceedings of the National Academy of Sciences of the United States of America
Auteur⸱e⸱s
Honey C. J., Sporns O., Cammoun L., Gigandet X., Thiran J. P., Meuli R., Hagmann P.
ISSN
1091-6490
Statut éditorial
Publié
Date de publication
2009
Peer-reviewed
Oui
Volume
106
Numéro
6
Pages
2035-2040
Langue
anglais
Résumé
In the cerebral cortex, the activity levels of neuronal populations are continuously fluctuating. When neuronal activity, as measured using functional MRI (fMRI), is temporally coherent across 2 populations, those populations are said to be functionally connected. Functional connectivity has previously been shown to correlate with structural (anatomical) connectivity patterns at an aggregate level. In the present study we investigate, with the aid of computational modeling, whether systems-level properties of functional networks-including their spatial statistics and their persistence across time-can be accounted for by properties of the underlying anatomical network. We measured resting state functional connectivity (using fMRI) and structural connectivity (using diffusion spectrum imaging tractography) in the same individuals at high resolution. Structural connectivity then provided the couplings for a model of macroscopic cortical dynamics. In both model and data, we observed (i) that strong functional connections commonly exist between regions with no direct structural connection, rendering the inference of structural connectivity from functional connectivity impractical; (ii) that indirect connections and interregional distance accounted for some of the variance in functional connectivity that was unexplained by direct structural connectivity; and (iii) that resting-state functional connectivity exhibits variability within and across both scanning sessions and model runs. These empirical and modeling results demonstrate that although resting state functional connectivity is variable and is frequently present between regions without direct structural linkage, its strength, persistence, and spatial statistics are nevertheless constrained by the large-scale anatomical structure of the human cerebral cortex.
Pubmed
Web of science
Open Access
Oui
Création de la notice
06/02/2009 11:28
Dernière modification de la notice
20/08/2019 16:26
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