TbCAPs: A toolbox for co-activation pattern analysis.

Détails

ID Serval
serval:BIB_20BFE026D10C
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
TbCAPs: A toolbox for co-activation pattern analysis.
Périodique
NeuroImage
Auteur⸱e⸱s
Bolton TAW, Tuleasca C., Wotruba D., Rey G., Dhanis H., Gauthier B., Delavari F., Morgenroth E., Gaviria J., Blondiaux E., Smigielski L., Van De Ville D.
ISSN
1095-9572 (Electronic)
ISSN-L
1053-8119
Statut éditorial
Publié
Date de publication
01/05/2020
Peer-reviewed
Oui
Volume
211
Pages
116621
Langue
anglais
Notes
Publication types: Journal Article
Publication Status: ppublish
Résumé
Functional magnetic resonance imaging provides rich spatio-temporal data of human brain activity during task and rest. Many recent efforts have focussed on characterising dynamics of brain activity. One notable instance is co-activation pattern (CAP) analysis, a frame-wise analytical approach that disentangles the different functional brain networks interacting with a user-defined seed region. While promising applications in various clinical settings have been demonstrated, there is not yet any centralised, publicly accessible resource to facilitate the deployment of the technique. Here, we release a working version of TbCAPs, a new toolbox for CAP analysis, which includes all steps of the analytical pipeline, introduces new methodological developments that build on already existing concepts, and enables a facilitated inspection of CAPs and resulting metrics of brain dynamics. The toolbox is available on a public academic repository at https://c4science.ch/source/CAP_Toolbox.git. In addition, to illustrate the feasibility and usefulness of our pipeline, we describe an application to the study of human cognition. CAPs are constructed from resting-state fMRI using as seed the right dorsolateral prefrontal cortex, and, in a separate sample, we successfully predict a behavioural measure of continuous attentional performance from the metrics of CAP dynamics (R ​= ​0.59).
Mots-clé
Attention, Co-activation pattern analysis, Continuous performance, Dynamic functional connectivity, Frame-wise analysis, Open source software, Task-positive network
Pubmed
Web of science
Open Access
Oui
Financement(s)
Université de Lausanne / Jeune Chercheur en Recherche Clinique
Création de la notice
17/02/2020 17:46
Dernière modification de la notice
22/06/2020 6:21
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