The neural dynamics of semantic diversity in spoken word recognition: The role of alpha-beta power

• DOI: 10.31234/osf.io/ks4x2
• Publication Date: 2020-09-18T10:55:44Z
• Authors: Priscila Borges; Vitória Piai
• Keywords: BETA (programming language); Alpha (finance)

Word recognition performance is significantly affected by semantic diversity (SemD), acorpus-based measure that indexes the degree to which contexts associated with a word are similar in meaning. Due prominence of SemD as determinant behaviour, it important understand its neural correlates, but these remain underexplored. To address thisgap, this study examines whether and how information reflected alpha-beta power dynamics during spoken recognition. Given previous evidence linking stronger decreases semantically richer words, high-SemD words were predicted elicit relative low-SemD words. Electroencephalographic data recorded while 13 older adults performed word-picture verification task. Average (10–20 Hz) around 400–600 ms post-word onset served dependentvariable linear mixed models whose fixed effects included other psycholinguistic variables. Results showed was not significant predictor whenposterior sites considered. However, when anterior later time window examined, effect found, higher scores predicting decreases. Additional analyses on event-related potential responses 300–500 post-stimulus no SemD. These findings provide first insights into electrophysiological signature corroborate reports more lexical-semantic needs beretrieved from memory. The null results discussed view few methodologicalaspects, could be explored future studies.