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Relative Strength Variability Measures for Brain Structural Connectomes and Their Relationship With Cognitive

Hon Wah Yeung1, Colin R Buchanan1, Joanna Moodie1

  • 1Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK.

Human Brain Mapping
|August 6, 2025
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Summary

We introduce novel brain network measures, relative strength variability (RSV) and hierarchical RSV (hRSV), to analyze weighted connectivity. Higher general cognitive function (g) correlated with lower RSV and hRSV, indicating increased network resilience and complexity.

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Area of Science:

  • Neuroscience
  • Network Science
  • Cognitive Science

Background:

  • Understanding the human brain's complex weighted connectivity is crucial for cognitive function.
  • Existing graph measures may not fully capture the nuances of weighted brain networks.
  • Node relative strengths offer a novel perspective on network topology and function.

Purpose of the Study:

  • To introduce and validate two new weighted graph measures: relative strength variability (RSV) and hierarchical RSV (hRSV).
  • To assess the relationship between these novel measures and general cognitive function (g).
  • To compare the predictive power of RSV and hRSV against established network metrics.

Main Methods:

  • Development of RSV and hRSV based on node relative strengths in weighted networks.
  • Application of these measures to structural connectomes from the UK Biobank using six different network weights.
  • Correlation and regression analyses to examine associations with other graph measures and general cognitive function (g).

Main Results:

  • RSV and hRSV showed low correlations with existing graph measures, suggesting they capture unique network information.
  • Higher general cognitive function (g) was significantly associated with lower RSV and hRSV.
  • The novel measures demonstrated stronger and incrementally significant associations with g compared to traditional metrics like clustering coefficient and global efficiency.

Conclusions:

  • RSV and hRSV represent a new class of weighted network measures that provide novel insights into brain connectome organization.
  • These measures are associated with general cognitive ability, with higher cognition linked to greater network resistance to attack and lower statistical complexity.
  • The proposed metrics significantly enhance the prediction of general cognition from weighted structural connectomes.