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Updated: Nov 4, 2025

Brain Imaging Investigation of the Neural Correlates of Observing Virtual Social Interactions
Published on: July 6, 2011
Associations of social network structure with cognition and amygdala volume in multiple sclerosis: An exploratory
Anne Kever1, Korhan Buyukturkoglu1, Seth N Levin2
1Translational Cognitive Neuroscience Laboratory, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA.
Background:
Humans are inherently social, biologically programmed to connect with others. Social connections are known to impact mental and physical health.
Objective:
The aim of this study was to test whether social network structure is linked to cognition, mood, fatigue, and regional brain volumes in persons with multiple sclerosis (MS).
Methods:
A questionnaire quantifying individual-level social network structure (size, density, effective size, and constraint), a comprehensive battery of neuropsychological tests, and magnetic resonance imaging (MRI) was administered to 51 persons with relapsing-remitting MS. Linear regressions assessed associations of network variables to cognition, depression, fatigue, and structural brain volumes.
Results:
Higher network density and constraint, indicating stronger connections among network members, were associated with worse language functions. Conversely, larger network effective size, a measure of non-redundant network members, was associated with better language functions. No relationships of network structure to depression or fatigue were found. Larger network size was related to larger amygdala volume.
Conclusion:
Findings suggest that social network structure is linked to language function and amygdala volume in persons with MS. Patients with close-knit networks showed worse language function than those with open networks. Longitudinal studies with larger samples are warranted to evaluate potential causal links between social network structure and MS-related cognitive impairment.
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