Distance-dependent consensus thresholds for generating group-representative structural brain networks.

Détails

ID Serval
serval:BIB_164C89348588
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Distance-dependent consensus thresholds for generating group-representative structural brain networks.
Périodique
Network neuroscience
Auteur(s)
Betzel R.F., Griffa A., Hagmann P., Mišić B.
ISSN
2472-1751 (Electronic)
ISSN-L
2472-1751
Statut éditorial
Publié
Date de publication
2019
Peer-reviewed
Oui
Volume
3
Numéro
2
Pages
475-496
Langue
anglais
Notes
Publication types: Journal Article
Publication Status: epublish
Résumé
Large-scale structural brain networks encode white matter connectivity patterns among distributed brain areas. These connection patterns are believed to support cognitive processes and, when compromised, can lead to neurocognitive deficits and maladaptive behavior. A powerful approach for studying the organizing principles of brain networks is to construct group-representative networks from multisubject cohorts. Doing so amplifies signal to noise ratios and provides a clearer picture of brain network organization. Here, we show that current approaches for generating sparse group-representative networks overestimate the proportion of short-range connections present in a network and, as a result, fail to match subject-level networks along a wide range of network statistics. We present an alternative approach that preserves the connection-length distribution of individual subjects. We have used this method in previous papers to generate group-representative networks, though to date its performance has not been appropriately benchmarked and compared against other methods. As a result of this simple modification, the networks generated using this approach successfully recapitulate subject-level properties, outperforming similar approaches by better preserving features that promote integrative brain function rather than segregative. The method developed here holds promise for future studies investigating basic organizational principles and features of large-scale structural brain networks.
Mots-clé
Complex networks, Connectome, Consensus, Group-representative, Wiring cost
Pubmed
Open Access
Oui
Création de la notice
28/04/2019 15:49
Dernière modification de la notice
20/08/2019 13:45
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