Brain morphometric similarity and flexibility

Vesna Vuksanovic*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Background: The cerebral cortex is represented through multiple multilayer morphometric similarity networks to study their modular structures. The approach introduces a novel way for studying brain networks' metrics across individuals, and can quantify network properties usually not revealed using conventional network analyses. Methods: A total of 8 combinations or types of morphometric similarity networks were constructed - 4 combinations of the inter-regional cortical features on 2 brain atlases. The networks' modular structures were investigated by identifying those modular interactions that stay consistent across the combinations of inter-regional morphometric features and individuals. Results: The results provide evidence of the community structures as the property of (i) cortical lobar divisions, and also as (ii) the product of different combinations of morphometric features used for the construction of the multilayer representations of the cortex. For the first time, this study has mapped out flexible and inflexible morphometric similarity hubs, and evidence has been provided about variations of the modular network topology across the multilayers with age and IQ. Conclusions: The results contribute to understanding of intra-regional characteristics in cortical interactions, which potentially can be used to map heterogeneous neurodegeneration patterns in diseased brains.

Original languageEnglish
Article numbertgac024
Number of pages13
JournalCerebral Cortex
Issue number3
Early online date16 Jun 2022
Publication statusPublished - 2022

Bibliographical note

Open Access via the OUP Agreement
Funding Information:
The author received financial support for publication by a UK Research & Innovation (UKRI) Medical Research Council (MRC) grant Health Data Research (HDR9006).


  • ageing
  • flexibility
  • general intelligence
  • morphometric similarity network
  • multilayer networks


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