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Network structural dependency in the human connectome across the life-span.

Markus D Schirmer1, Ai Wern Chung2, P Ellen Grant2

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The Network Dependency Index (NDI) identifies crucial brain regions, creating consistent subnetworks across lifespan. This new framework reveals age-related changes in human connectome topology more effectively than previous methods.

Keywords:
DiffusionLife-spanNetwork dependency indexRich clubSubnetwork

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Area of Science:

  • Neuroscience
  • Network Science
  • Computational Biology

Background:

  • Human brain connectome exhibits modularity, crucial for understanding development, aging, and disease.
  • Existing network topology measures may lack consistency across age groups.

Purpose of the Study:

  • Introduce the Network Dependency Index (NDI) as a novel weighted network measure.
  • Utilize NDI to define and analyze subnetworks (Tiers) within the human connectome.
  • Investigate age-related topological changes in NDI-defined subnetworks and compare them to rich club-based subnetworks.

Main Methods:

  • Calculated the Network Dependency Index (NDI) for individual brain regions.
  • Applied Gaussian mixture model fitting to stratify the connectome into four subnetworks (Tiers) based on NDI.
  • Analyzed topological properties of NDI-defined subnetworks across different age groups.
  • Compared NDI-derived subnetworks with rich club, feeder, and seeder subnetworks.

Main Results:

  • NDI effectively identifies consistent, central nodes in the human connectome across age groups, outperforming the rich club framework.
  • NDI-based stratification yields stable subnetworks throughout the lifespan.
  • Distinct age-associated topological patterns were observed, with high-NDI subnetworks containing key relay nuclei and cortical regions.

Conclusions:

  • The NDI framework provides a robust method for defining human brain subnetworks.
  • NDI-derived subnetworks demonstrate greater consistency across age than rich club-based approaches.
  • This data-driven approach offers potential for revealing lifespan topological alterations in the connectome.