Date of Award

5-2024

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

College/School

College of Humanities and Social Sciences

Department/Program

Psychology

Thesis Sponsor/Dissertation Chair/Project Chair

Joshua Sandry

Committee Member

Jennifer Pardo

Committee Member

Michael Bixter

Committee Member

James Sumowski

Abstract

Word finding difficulty is a frequently reported subjective cognitive concern among persons with Multiple Sclerosis (pwMS). Word-finding relies on several information retrieval processes, including search and retrieval from the conceptual store, the phonological store, the syllabary, as well as other stores of information. Neuropsychological assessments, including the semantic verbal fluency measure, can be used to measure word retrieval abilities. Despite this, the MS research literature shows that neuropsychological assessment of semantic verbal fluency yields mixed results in detecting word-finding difficulties. While some studies report finding statistically lower semantic fluency scores in pwMS relative to healthy controls (HC), others found no difference. A similar pattern of results was observed concerning two strategies: clustering and switching. While use of semantic clusters was consistently not different from HC, results concerning switching were mixed, with only some studies finding decreased cluster switching. Connectionist linguistic models posit that the semantic store is organized as a network, where closely related concepts are associated. As such, semantic network analysis may provide additional insight into both measuring semantic retrieval difficulties and understanding why word retrieval difficulties occur. Semantic networks generated from this type of analysis provide an estimation of the organization of the conceptual-lexical store. Consistent with study hypotheses, the MS group produced fewer words on the semantic verbal fluency task. The MS group also reported more frequent subjective word finding concerns relative to the HC group. In addition, the MS network was characterized by having longer average shortest path lengths (ASPL; reduced efficiency), lower global clustering coefficient (CCG; reduced interconnectivity), higher modularity (Q), and greater vulnerability to attack (lower percolation integral) compared to HC networks. Supplementary analyses indicated that RRMS networks similarly exhibited higher ASPL, lower CCG, and higher modularity compared to HC networks. Contrary to expectations, cluster switching was not significantly decreased in the MS group compared to the HC group, although results were in the expected direction. In addition, the RRMS network was more robust to attack processes; this finding was opposite of what was hypothesized. This study confirmed prior network findings using samples that were equivalent in age, education, and ethnicity; factors known to impact verbal fluency performance. In addition, it provided novel results concerning semantic network differences in persons with RRMS. Finally, this study is the first to report on the degree of subjective word finding concerns in an MS sample with a long average disease duration. Overall, the results of this study show that semantic retrieval is reduced both in MS and RRMS populations. The pattern of structural network differences may be relevant to guide rehabilitation strategies. Rehabilitation implications are discussed.

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