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Updated: Sep 21, 2025

Comprehensive Autopsy Program for Individuals with Multiple Sclerosis
Published on: July 19, 2019
Summary metrics of memory subnetwork functional connectivity alterations in multiple sclerosis
Victoria M Leavitt1, Jordan D Dworkin2, Korhan Buyukturkoglu3
1Translational Cognitive Neuroscience Laboratory, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA/Multiple Sclerosis Center, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA.
Background:
Memory dysfunction is common in multiple sclerosis (MS); mechanistic understanding of its causes is lacking. Large-scale network resting-state functional connectivity (RSFC) is sensitive to memory dysfunction.
Objective:
We derived and tested summary metrics of memory network RSFC.
Methods:
Cognitive data and 3T magnetic resonance imaging (MRI) scans were collected from 235 MS patients and 35 healthy controls (HCs). Index scores were calculated as RSFC within (anteriority index, AntI) and between (integration index, IntI) dorsomedial anterior temporal and medial temporal memory subnetworks. Group differences in index expression were evaluated. Associations between index scores and memory/non-memory cognition were evaluated; relationships between T2 lesion volume (T2LV) and index scores were assessed.
Results:
Index scores were related to memory and T2LV in MS patients, who showed marginally elevated AntI relative to HC (p = 0.06); no group differences were found for IntI. Better memory was associated with higher AntI (β = 0.15, p = 0.018) and IntI (β = 0.16, p = 0.014). No associations were found for non-memory cognition. Higher T2LV was associated with higher AntI and IntI; exploratory mediation analysis revealed significant inconsistent mediation, that is, higher index scores partially suppressed the negative association between T2LV and memory.
Conclusion:
Summary, within-subject metrics permit replication and circumvent challenges of traditional (incommensurate) RSFC variables to advance development of mechanistic models of memory dysfunction in MS.
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