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Hypergraph modeling of complex interactions: Applications from human musculoskeletal structures to complex system dynamics

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  • Hiroko Yamano
  • Shu Liu
  • Fujio Toriumi

Abstract

The musculoskeletal network is a complex system of different types of nodes and edges interacting with each other. Although there is a wealth of knowledge about the anatomical components of the human body and the connections between them, the interdependence of these components as a system remains largely unexplored. This study aims to understand the structure of musculoskeletal networks by using hypergraphs as a model of the musculoskeletal system with many-to-many connections. We used both pairwise and hypergraph-based embedding methods to learn the connectivity of muscles. Experiments demonstrated the superiority of the proposed hypergraph-based method over pairwise methods in distinguishing the specific roles of the muscles connecting different body parts.

Suggested Citation

  • Hiroko Yamano & Shu Liu & Fujio Toriumi, 2024. "Hypergraph modeling of complex interactions: Applications from human musculoskeletal structures to complex system dynamics," PLOS ONE, Public Library of Science, vol. 19(11), pages 1-16, November.
    • Handle: RePEc:plo:pone00:0310189
    DOI: 10.1371/journal.pone.0310189
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    References listed on IDEAS

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    1. Andrew C Murphy & Sarah F Muldoon & David Baker & Adam Lastowka & Brittany Bennett & Muzhi Yang & Danielle S Bassett, 2018. "Structure, function, and control of the human musculoskeletal network," PLOS Biology, Public Library of Science, vol. 16(1), pages 1-27, January.
    2. Evan M. Gordon & Roselyne J. Chauvin & Andrew N. Van & Aishwarya Rajesh & Ashley Nielsen & Dillan J. Newbold & Charles J. Lynch & Nicole A. Seider & Samuel R. Krimmel & Kristen M. Scheidter & Julia Mo, 2023. "A somato-cognitive action network alternates with effector regions in motor cortex," Nature, Nature, vol. 617(7960), pages 351-359, May.
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