Multilevel irreversibility reveals higher-order organization of nonequilibrium interactions in human brain dynamics DOI Creative Commons
Ramón Nartallo-Kaluarachchi, Leonardo Bonetti, Gemma Fernández-Rubio

et al.

Proceedings of the National Academy of Sciences, Journal Year: 2025, Volume and Issue: 122(10)

Published: March 7, 2025

Information processing in the human brain can be modeled as a complex dynamical system operating out of equilibrium with multiple regions interacting nonlinearly. Yet, despite extensive study global level nonequilibrium brain, quantifying irreversibility interactions among at levels remains an unresolved challenge. Here, we present Directed Multiplex Visibility Graph Irreversibility framework, method for analyzing neural recordings using network analysis time-series. Our approach constructs directed multilayer graphs from multivariate time-series where information about decoded marginal degree distributions across layers, which each represents variable. This framework is able to quantify every interaction system. Applying magnetoencephalography during long-term memory recognition task, between and identify combinations showed higher their interactions. For individual regions, find cognitive versus sensorial while pairs, strong relationships are uncovered pairs same hemisphere. triplets quadruplets, most cognitive-sensorial alongside medial regions. Combining these results, show that multilevel offers unique insights into higher-order, hierarchical organization dynamics perspective dynamics.

Language: Английский

Multilevel irreversibility reveals higher-order organization of nonequilibrium interactions in human brain dynamics DOI Creative Commons
Ramón Nartallo-Kaluarachchi, Leonardo Bonetti, Gemma Fernández-Rubio

et al.

Proceedings of the National Academy of Sciences, Journal Year: 2025, Volume and Issue: 122(10)

Published: March 7, 2025

Information processing in the human brain can be modeled as a complex dynamical system operating out of equilibrium with multiple regions interacting nonlinearly. Yet, despite extensive study global level nonequilibrium brain, quantifying irreversibility interactions among at levels remains an unresolved challenge. Here, we present Directed Multiplex Visibility Graph Irreversibility framework, method for analyzing neural recordings using network analysis time-series. Our approach constructs directed multilayer graphs from multivariate time-series where information about decoded marginal degree distributions across layers, which each represents variable. This framework is able to quantify every interaction system. Applying magnetoencephalography during long-term memory recognition task, between and identify combinations showed higher their interactions. For individual regions, find cognitive versus sensorial while pairs, strong relationships are uncovered pairs same hemisphere. triplets quadruplets, most cognitive-sensorial alongside medial regions. Combining these results, show that multilevel offers unique insights into higher-order, hierarchical organization dynamics perspective dynamics.

Language: Английский

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