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From Density to Void: Why Brain Networks Fail to Reveal Complex Higher-Order Structures

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arxiv 2503.14700 v1 pith:2YI24PGN submitted 2025-03-18 q-bio.NC

classification q-bio.NC
keywords higher-orderinteractionsbraincomplexfailhomologynetworksoften
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In brain network analysis using resting-state fMRI, there is growing interest in modeling higher-order interactions beyond simple pairwise connectivity via persistent homology. Despite the promise of these advanced topological tools, robust and consistently observed higher-order interactions over time remain elusive. In this study, we investigate why conventional analyses often fail to reveal complex higher-order structures - such as interactions involving four or more nodes - and explore whether such interactions truly exist in functional brain networks. We utilize a simplicial complex framework often used in persistent homology to address this question.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Biological detail and graph structure in network neuroscience

    q-bio.NC 2025-07 conditional novelty 2.0 of 10

    A review arguing that generalizing network structure does not escape the fundamental problems of intrinsicality, universality, and functional meaningfulness that already affect standard brain network models.

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