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Functional brain network organization measured with magnetoencephalography predicts cognitive decline in multiple
Ilse M Nauta1, Shanna D Kulik2, Lucas C Breedt2
1Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands.
Multiple Sclerosis (Houndmills, Basingstoke, England)
|December 9, 2020
Summary
Functional brain network integration measured with magnetoencephalography (MEG) predicts cognitive decline in multiple sclerosis (MS) patients. This finding is independent of structural brain damage, offering a new way to track disease progression.
Area of Science:
- Neuroscience
- Medical Imaging
- Neurology
Background:
- Cognitive decline in multiple sclerosis (MS) is challenging to predict.
- Structural brain damage alone does not fully account for the variability in MS patient outcomes.
Purpose of the Study:
- To determine if functional brain network organization, assessed via magnetoencephalography (MEG), can predict cognitive decline in MS patients over five years.
- To evaluate the predictive value of functional brain networks beyond existing measures of structural pathology.
Main Methods:
- Analysis of resting-state MEG recordings, structural MRI, and neuropsychological assessments from 146 MS patients.
- Utilized minimum spanning tree network properties to quantify functional brain network integration and overload.
- Correlated network properties with baseline and longitudinal cognitive performance, adjusting for structural damage.
Main Results:
- A more integrated beta band network (smaller diameter) and a less integrated delta band network (lower leaf fraction) at baseline predicted subsequent cognitive decline.
- These functional network changes predicted cognitive decline independently of structural brain damage.
- Cross-sectional analysis revealed that less integrated networks correlated with poorer cognitive function across different frequency bands.
Conclusions:
- Functional brain network integration is an independent predictor of cognitive decline in MS, complementing structural damage assessments.
- MEG-derived functional network measures show significant potential for predicting disease progression in MS patients.
- This study highlights the importance of assessing brain network dynamics for understanding and predicting cognitive impairment in MS.
