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Semantic networks in relapsing-remitting multiple sclerosis exhibit reduced efficiency, interconnectivity, and

Sophia Lall, Jennifer Pardo, Joshua Sandry1

  • 1Department of Psychology, Montclair State University, Montclair, NJ, USA.

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|December 9, 2025
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Summary

Persons with relapsing-remitting multiple sclerosis (pwRRMS) experience word-finding difficulties. Semantic network analysis reveals disorganized semantic retrieval in pwRRMS, unlike standard fluency tests.

Keywords:
Relapsing-remitting multiple sclerosisnetwork analysissemantic retrievalspeechverbal fluencyword-finding

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Area of Science:

  • Neurology
  • Cognitive Science
  • Linguistics

Background:

  • Word-finding deficits are prevalent in persons with relapsing-remitting multiple sclerosis (pwRRMS).
  • These deficits may stem from inefficient semantic information organization.
  • Understanding these cognitive challenges is crucial for managing the condition.

Purpose of the Study:

  • To investigate semantic organization and retrieval in pwRRMS.
  • To compare semantic network topology between pwRRMS and healthy controls.
  • To assess the relationship between subjective word-finding concerns and objective measures.

Main Methods:

  • Utilized semantic fluency data from 64 pwRRMS and 73 controls.
  • Derived standard verbal fluency measures using the Semantic Network and Fluency Utility R package.
  • Constructed semantic networks using a correlation-based network approach in the SemNet R package.

Main Results:

  • PwRRMS reported more frequent word-finding concerns than controls.
  • No significant differences were found in standard semantic fluency measures.
  • PwRRMS exhibited altered semantic network topology, including reduced efficiency, interconnectivity, and flexibility.

Conclusions:

  • Word-finding difficulties are common and should be screened for in pwRRMS.
  • Semantic network analysis is more sensitive than standard metrics for detecting semantic retrieval deficits in pwRRMS.
  • Semantic network disorganization may underlie word-finding issues; interventions targeting network structure could be beneficial.