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Slide Slam M10

Effects of semantic variables on processes during word planning for production: Evidence from electrophysiological data

Slide Slam Session M, Thursday, October 7, 2021, 6:00 - 8:00 am PDT Log In to set Timezone

Leonie F. Lampe1,2, Audrey Bürki3, Paul F. Sowman1, Solène Hameau1, Lyndsey Nickels1; 1Macquarie University, Sydney, Australia, 2International Doctorate for Experimental Approaches to Language and Brain (IDEALAB), 3University of Potsdam, Germany

Semantic and lexical processing for word production are influenced by word-specific properties of the target word. A subgroup of these word properties are semantic variables, like the number of semantic features. A growing number of studies has investigated influences of semantic variables on behavioural measures of word production. For example, naming performance is facilitated by a higher number of semantic features and inhibited by higher intercorrelational density of a target word (e.g., Rabovsky et al., 2016, Cognition). Studying effects of semantic variables is an important area of research as it informs our understanding of both information representation and processing during word production. However, only one previous study has examined the influence of semantic variables on electrophysiological data collected during word planning for production in picture naming: Rabovsky et al., (2021, JEP:LMC) who analysed just two variables. By analysing electrophysiological data in addition to behavioural data for additional semantic variables, we aimed to further investigate how these variables influence processes during word production and work towards a better understanding of the brain correlates underlying behaviour and the temporal development of processes in word production. 78 participants named 291 colour photographs, while electrophysiological data were recorded. We investigated the electrophysiological correlates of six feature-based semantic variables: number of semantic features, intercorrelational density, number of near semantic neighbours, semantic similarity, typicality, and distinctiveness. The data were analysed using linear mixed effect models, including all six semantic variables, while also controlling for several psycholinguistic variables known to affect word production. We first replicated the analysis approach of Rabovsky et al. (2021), by analysing the mean amplitude of the event-related potential data in a posterior region between 200 and 550ms post picture onset and by investigating the development of the effects of the semantic variables across 10ms time segments between 0 and 550ms in a time-course analysis. Then, we conducted a microstate analysis to study whether, and, if so, how the semantic variables affected the durations of periods of stable electrophysiological patterns. Preliminary results suggest that most of the semantic variables influence brain activity during planning for production. So far, we find a stronger posterior positivity for words with more semantic features. Moreover, number of semantic features, intercorrelational density, semantic similarity, and number of near semantic neighbours affected the number of timeframes associated with two microstates. The results of the final analyses will be presented at the conference. These preliminary findings can be interpreted as reflecting increased activity in the semantic and lexical network involved in word production. This could reflect either enhanced activation of the target word itself or increased activation distributed across a cohort of co-activated semantically related lexical representations caused by the significant semantic variables.

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