Casas-Roma, Jordi;
Martinez-Heras, Eloy;
Sole-Ribalta, Albert;
Solana, Elisabeth;
Lopez-Soley, Elisabet;
Vivo, Francesc;
Diaz-Hurtado, Marcos;
... Prados, Ferran; + view all
(2022)
Applying multilayer analysis to morphological, structural, and functional brain networks to identify relevant dysfunction patterns.
Network Neuroscience
, 6
(3)
pp. 916-933.
10.1162/netn_a_00258.
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Abstract
In recent years, research on network analysis applied to MRI data has advanced significantly. However, the majority of the studies are limited to single networks obtained from resting-state fMRI, diffusion MRI, or gray matter probability maps derived from T1 images. Although a limited number of previous studies have combined two of these networks, none have introduced a framework to combine morphological, structural, and functional brain connectivity networks. The aim of this study was to combine the morphological, structural, and functional information, thus defining a new multilayer network perspective. This has proved advantageous when jointly analyzing multiple types of relational data from the same objects simultaneously using graph- mining techniques. The main contribution of this research is the design, development, and validation of a framework that merges these three layers of information into one multilayer network that links and relates the integrity of white matter connections with gray matter probability maps and resting-state fMRI. To validate our framework, several metrics from graph theory are expanded and adapted to our specific domain characteristics. This proof of concept was applied to a cohort of people with multiple sclerosis, and results show that several brain regions with a synchronized connectivity deterioration could be identified.
| Type: | Article |
|---|---|
| Title: | Applying multilayer analysis to morphological, structural, and functional brain networks to identify relevant dysfunction patterns |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1162/netn_a_00258 |
| Publisher version: | https://doi.org/10.1162/netn_a_00258 |
| Language: | English |
| Additional information: | © 2022 Massachusetts Institute of Technology Published under a Creative Commons Attribution 4.0 International (CC BY 4.0) license |
| Keywords: | Science & Technology, Life Sciences & Biomedicine, Neurosciences, Neurosciences & Neurology, Structural connectivity, Functional connectivity, Gray matter networks, Multiple sclerosis, Multilayer, CONNECTIVITY |
| UCL classification: | UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng UCL > Provost and Vice Provost Offices > UCL BEAMS UCL |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10157604 |
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