Bardella, Giampiero and Bifone, Angelo and Gabrielli, Andrea and Gozzi, Alessandro and Squartini, Tiziano Hierarchical organization of functional connectivity in the mouse brain: a complex network approach. Scientific Reports, 6. p. 32060. ISSN 2045-2322 (2016)
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Abstract
This paper represents a contribution to the study of the brain functional connectivity from the perspective of complex networks theory. More specifically, we apply graph theoretical analyses to provide evidence of the modular structure of the mouse brain and to shed light on its hierarchical organization. We propose a novel percolation analysis and we apply our approach to the analysis of a resting-state functional MRI data set from 41 mice. This approach reveals a robust hierarchical structure of modules persistent across different subjects. Importantly, we test this approach against a statistical benchmark (or null model) which constrains only the distributions of empirical correlations. Our results unambiguously show that the hierarchical character of the mouse brain modular structure is not trivially encoded into this lower-order constraint. Finally, we investigate the modular structure of the mouse brain by computing the Minimal Spanning Forest, a technique that identifies subnetworks characterized by the strongest internal correlations. This approach represents a faster alternative to other community detection methods and provides a means to rank modules on the basis of the strength of their internal edges.
| Item Type: | Article |
|---|---|
| Identification Number: | https://doi.org/10.1038/srep32060 |
| Projects: | EU project FET-Open FOC (grant num. 255987), FET Project SIMPOL (nr. 610704), FET project DOLFINS (grant num. 640772) |
| Uncontrolled Keywords: | Applied physics, Complex networks |
| Subjects: | Q Science > QC Physics |
| Research Area: | Computer Science and Applications |
| Depositing User: | Caterina Tangheroni |
| Date Deposited: | 04 Oct 2016 11:13 |
| Last Modified: | 04 Oct 2016 11:13 |
| URI: | http://eprints.imtlucca.it/id/eprint/3553 |
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