Resting-state functional connectivity in multiple sclerosis: an examination of group differences and individual...

Area of Science:

• Neuroscience
• Neurology
• Medical Imaging

Background:

• Multiple sclerosis (MS) is a central nervous system disease causing physical and cognitive impairments.
• Relapsing-remitting MS (RRMS) is the most common form, characterized by distinct neurological episodes.
• Understanding network integrity in RRMS is crucial for assessing disease impact and progression.

Purpose of the Study:

• To investigate the association between resting-state network integrity and cognitive function in RRMS patients.
• To correlate network integrity with measures of disease severity in RRMS.
• To compare network integrity between RRMS individuals and healthy controls.

Main Methods:

• Resting-state functional magnetic resonance imaging (fMRI) was used to collect neuroimaging data.
• Independent component analysis (ICA) and dual regression were applied to analyze network integrity.
• Neuropsychological assessments measured cognition and disease severity.

Main Results:

• Individuals with RRMS showed reduced connectivity in motor and visual networks compared to controls.
• No significant differences in frontoparietal, executive control, or default-mode networks were found.
• Higher disease severity was linked to decreased motor and executive control network connectivity.
• Increased disease burden correlated with altered inter-network connectivity between visual and visuomotor areas.

Conclusions:

• Resting-state network integrity is altered in RRMS, particularly in motor and visual systems.
• Network connectivity changes correlate with disease severity and cognitive function.
• These findings highlight the potential of resting-state oscillations as biomarkers for MS progression and therapeutic targets.