Summary metrics of memory subnetwork functional connectivity alterations in multiple sclerosis

Area of Science:

• Neuroscience
• Cognitive Neuroscience
• Medical Imaging

Background:

• Memory dysfunction is a significant challenge in multiple sclerosis (MS), with unclear underlying mechanisms.
• Resting-state functional connectivity (RSFC) of large-scale brain networks is a sensitive indicator of memory impairment.

Purpose of the Study:

• To develop and validate novel summary metrics for assessing memory network RSFC in MS.
• To investigate the relationship between these RSFC metrics, cognitive function, and lesion load in MS.

Main Methods:

• Collected cognitive data and 3T MRI scans from 235 MS patients and 35 healthy controls (HCs).
• Calculated anteriority index (AntI) for within-network RSFC and integration index (IntI) for between-network RSFC within memory subnetworks.
• Assessed group differences in index scores, associations with cognitive performance (memory and non-memory), and relationships with T2 lesion volume (T2LV).

Main Results:

• MS patients showed marginally elevated AntI compared to HCs, with no significant group difference in IntI.
• Higher AntI and IntI scores were significantly associated with better memory performance in MS patients.
• Increased T2LV was correlated with higher AntI and IntI, and these indices partially mediated the negative impact of T2LV on memory.

Conclusions:

• Novel within-subject RSFC metrics (AntI and IntI) offer a reliable way to study memory network alterations in MS.
• These metrics advance the development of mechanistic models for understanding and potentially treating memory dysfunction in MS.
• The findings highlight the complex interplay between brain connectivity, lesion burden, and cognitive function in multiple sclerosis.