Structure-function multilayer network integration and cognition in multiple sclerosis

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.