An algebraic topological method for multimodal brain networks comparisons

Abstract : Understanding brain connectivity is one of the most important issues in neuroscience. Nonetheless, connectivity data can reflect either functional relationships of brain activities or anatomical connections between brain areas. Although both representations should be related, this relationship is not straightforward. We have devised a powerful method that allows different operations between networks that share the same set of nodes, by embedding them in a common metric space, enforcing transitivity to the graph topology. Here, we apply this method to construct an aggregated network from a set of functional graphs, each one from a different subject. Once this aggregated functional network is constructed, we use again our method to compare it with the structural connectivity to identify particular brain regions that differ in both modalities (anatomical and functional). Remarkably, these brain regions include functional areas that form part of the classical resting state networks. We conclude that our method -based on the comparison of the aggregated functional network- reveals some emerging features that could not be observed when the comparison is performed with the classical averaged functional network.
Document type :
Journal articles
Complete list of metadatas

Cited literature [25 references]  Display  Hide  Download
Contributor : Mario Chavez <>
Submitted on : Monday, February 1, 2016 - 9:53:17 AM
Last modification on : Tuesday, November 5, 2019 - 3:26:11 PM
Long-term archiving on : Friday, November 11, 2016 - 11:28:15 PM


Publication funded by an institution


Distributed under a Creative Commons Attribution 4.0 International License



Tiago Simas, Mario Chavez, Pablo R. Rodriguez, Albert Diaz-Guilera. An algebraic topological method for multimodal brain networks comparisons. Frontiers in Psychology, Frontiers, 2015, 6, pp.904. ⟨10.3389/fpsyg.2015.00904⟩. ⟨hal-01263828⟩



Record views


Files downloads