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

Background: Word-finding deficits are common in persons with relapsing-remitting multiple sclerosis (pwRRMS); this may be related to the inefficient organization of semantic information. Objective: To understand whether the semantic organization and semantic retrieval are impacted in pwRRMS. Methods: Semantic fluency data from 64 pwRRMS and 73 controls was utilized to (1) derive standard verbal fluency measures using the Semantic Network and Fluency Utility R package and (2) build semantic networks via the correlation-based network approach in the SemNet R package. Subjective word-finding concerns were assessed in a subgroup of the sample. Group differences were evaluated. Results: PwRRMS endorsed more frequent word-finding concerns. There were no differences between pwRRMS and controls on standard measures of semantic fluency. PwRRMS semantic networks exhibited differences in topology. Specifically, RRMS networks exhibited reduced efficiency, reduced interconnectivity, and reduced flexibility relative to control networks. Conclusion: Word-finding concerns are prevalent in pwRRMS; it is important to screen for and address these concerns in clinical settings. Semantic network analysis appears more sensitive in detecting semantic retrieval deficits in pwRRMS relative to standard semantic fluency metrics. Semantic network disorganization and inflexibility may partially underlie word-finding difficulty in pwRRMS. Strategies aimed at improving network structure may assist in managing these deficits.