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Topological Modules of Human Brain Networks Are Anatomically Embedded: Evidence from Modularity Analysis at Multiple Scales

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Computational Aspects and Applications in Large-Scale Networks (NET 2016)

Abstract

Human brain networks show modular organization: cortical regions tend to form densely connected modules with only weak inter-modular connections. However, little is known on whether modular structure of brain networks is reliable in terms of test–retest reproducibility and, most importantly, to what extent these topological modules are anatomically embedded. To address these questions, we use MRI data of the same individuals scanned with an interval of several weeks, reconstruct structural brain networks at multiple scales, and partition them into communities and evaluate similarity of partitions (i) stemming from the test–retest data of the same versus different individuals and (ii) implied by network topology versus anatomy-based grouping of neighboring regions. First, our results demonstrate that modular structure of brain networks is well reproducible in test–retest settings. Second, the results provide evidence of the theoretically well-motivated hypothesis that brain regions neighboring in anatomical space also tend to belong to the same topological modules.

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Acknowledgements

The publication was prepared within the framework of the Academic Fund Program at the National Research University Higher School of Economics (HSE) in 2017 (grant 16-05-0050) and by the Russian Academic Excellence Project “5-100”.

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Correspondence to Anvar Kurmukov .

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Kurmukov, A. et al. (2018). Topological Modules of Human Brain Networks Are Anatomically Embedded: Evidence from Modularity Analysis at Multiple Scales. In: Kalyagin, V., Pardalos, P., Prokopyev, O., Utkina, I. (eds) Computational Aspects and Applications in Large-Scale Networks. NET 2016. Springer Proceedings in Mathematics & Statistics, vol 247. Springer, Cham. https://doi.org/10.1007/978-3-319-96247-4_22

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