Interaction of Functional Brain Networks Is Associated With <i>k</i> ‐Clique Percolation in the Human Structural Connectome

The human structural connectome has a complex internal community organization, characterized by a high degree of overlap and related to functional and cognitive phenomena. We explored connectivity properties in connectome networks and showed that <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mi>k</mml:mi></mml:mrow> <mml:annotation>$$ k $$</mml:annotation></mml:semantics> </mml:math> -clique percolation of an anomalously high order is characteristic of the human structural connectome. The resulting structural organization maintains a high local density of connectivity distributed throughout the connectome while preserving the overall sparsity of the network. To analyze these findings, we proposed a novel model for the emergence of high-order clique percolation during network formation with a phase transition dynamic under constraints on connection length. Investigating the structural basis of functional brain subnetworks, we identified a direct relationship between their interaction and the formation of clique clusters within their structural connections. Based on these findings, we hypothesize that the percolating clique cluster serves as a distributed bridge between interacting functional subnetworks, showing the complex, complementary nature of their structural connections. We also examined the difference between individual-specific and common structural connections and found that the latter plays a sustaining role in the connectivity of structural communities. At the same time, the superiority of individual connections, in contrast to common ones, creates variability in the interaction of functional brain subnetworks.

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Publication Details

Journal
Human Brain Mapping
Published
2025-10-15
DOI
https://doi.org/10.1002/hbm.70343
Primary Topic
Functional Brain Connectivity Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Interaction of Functional Brain Networks Is Associated With k ‐Clique Percolation in the Human Structural Connectome

Vasilii Tiselko, Olga Valba, Denis Zakharov, Artem Myshkin et al.
Human Brain Mapping
Functional Brain Connectivity Studies
article

Interaction of Functional Brain Networks Is Associated With k ‐Clique Percolation in the Human Structural Connectome

Vasilii Tiselko, Olga Valba, Denis Zakharov, Artem Myshkin, Olesia Dogonasheva
article en

Abstract

The human structural connectome has a complex internal community organization, characterized by a high degree of overlap and related to functional and cognitive phenomena. We explored connectivity properties in connectome networks and showed that <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mi>k</mml:mi></mml:mrow> <mml:annotation>$$ k $$</mml:annotation></mml:semantics> </mml:math> -clique percolation of an anomalously high order is characteristic of the human structural connectome. The resulting structural organization maintains a high local density of connectivity distributed throughout the connectome while preserving the overall sparsity of the network. To analyze these findings, we proposed a novel model for the emergence of high-order clique percolation during network formation with a phase transition dynamic under constraints on connection length. Investigating the structural basis of functional brain subnetworks, we identified a direct relationship between their interaction and the formation of clique clusters within their structural connections. Based on these findings, we hypothesize that the percolating clique cluster serves as a distributed bridge between interacting functional subnetworks, showing the complex, complementary nature of their structural connections. We also examined the difference between individual-specific and common structural connections and found that the latter plays a sustaining role in the connectivity of structural communities. At the same time, the superiority of individual connections, in contrast to common ones, creates variability in the interaction of functional brain subnetworks.

Human Brain MappingVol. 46(15)
National Research University Higher School of Economics (RU), Moscow Institute of Physics and Technology (RU), Inserm (FR), Institut Pasteur (FR), Université Paris Cité (FR), Institut des Sciences Cognitives Marc Jeannerod (FR), Research Center of Neurology (RU)
Agence Nationale de la Recherche, Russian Foundation for Basic Research, National Research University Higher School of Economics
Openalex Percentile: Top 70%
Functional Brain Connectivity Studies
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