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Structure-function multilayer network integration and cognition in multiple sclerosis.

Lucas C Breedt1, Giuseppe Pontillo2,3,4,5, Fernando A N Santos1,6

  • 1Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.

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|April 27, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

Cognitive deficits in multiple sclerosis (MS) are linked to brain network changes. This study found weak, atlas-specific associations between multilayer frontoparietal network integration and cognitive performance in MS patients.

Keywords:
Executive functioningFunctional connectivityGraph theoryMultilayer networksStructural connectivity

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Medical Imaging

Background:

  • Multiple sclerosis (MS) frequently causes cognitive deficits beyond focal brain lesions.
  • Whole-brain network alterations are implicated, but research often focuses on single-layer structural or functional networks.
  • Multilayer network integration, particularly in the frontoparietal network, is increasingly recognized for its role in cognition.

Purpose of the Study:

  • To investigate the cognitive relevance of multilayer frontoparietal network integration in individuals with relapsing-remitting MS.
  • To explore the relationship between network centrality and eccentricity measures and cognitive performance.

Main Methods:

  • Utilized diffusion and resting-state functional MRI data from 780 relapsing-remitting MS patients.
  • Assessed nodal multilayer eigenvector centrality and mean eccentricity for single-layer and multilayer networks.
  • Correlated network parameters with Symbol Digit Modalities Test (SDMT) performance.

    • Main Results:

    • Higher multilayer frontoparietal network centrality correlated with poorer SDMT performance (β = -0.117, p = 0.005).
    • Mean eccentricity in both single-layer diffusion and multilayer networks showed associations with SDMT performance (β = -0.123, p < 0.001 and β = 0.085, p = 0.018, respectively).
    • These findings were not consistently replicated across different anatomical parcellations.

    Conclusions:

    • Cognition in MS is associated with multilayer network parameters, but the correlations are weak.
    • The observed associations are atlas-specific, questioning the broad relevance of binary structure-function multilayer network approaches for cognition in MS.