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Multimodal multilayer network centrality relates to executive functioning

Authors :
Lucas C. Breedt
Fernando A. N. Santos
Arjan Hillebrand
Liesbeth Reneman
Anne-Fleur van Rootselaar
Menno M. Schoonheim
Cornelis J. Stam
Anouk Ticheler
Betty M. Tijms
Dick J. Veltman
Chris Vriend
Margot J. Wagenmakers
Guido A. van Wingen
Jeroen J. G. Geurts
Anouk Schrantee
Linda Douw
Source :
Network Neuroscience, Vol 7, Iss 1, Pp 299-321 (2023)
Publication Year :
2023
Publisher :
The MIT Press, 2023.

Abstract

AbstractExecutive functioning (EF) is a higher order cognitive process that is thought to depend on a network organization facilitating integration across subnetworks, in the context of which the central role of the fronto-parietal network (FPN) has been described across imaging and neurophysiological modalities. However, the potentially complementary unimodal information on the relevance of the FPN for EF has not yet been integrated. We employ a multilayer framework to allow for integration of different modalities into one ‘network of networks.’ We used diffusion MRI, resting-state functional MRI, MEG, and neuropsychological data obtained from 33 healthy adults to construct modality-specific single-layer networks as well as a single multilayer network per participant. We computed single-layer and multilayer eigenvector centrality of the FPN as a measure of integration in this network and examined their associations with EF. We found that higher multilayer FPN centrality, but not single-layer FPN centrality, was related to better EF. We did not find a statistically significant change in explained variance in EF when using the multilayer approach as compared to the single-layer measures. Overall, our results show the importance of FPN integration for EF and underline the promise of the multilayer framework toward better understanding cognitive functioning.

Details

Language :
English
ISSN :
24721751
Volume :
7
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Network Neuroscience
Publication Type :
Academic Journal
Accession number :
edsdoj.0d755b48842d4ec3967cd3662ed35d53
Document Type :
article
Full Text :
https://doi.org/10.1162/netn_a_00284