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The Effects of Endogenous Semantic Variables during Productive Lexical Retrieval: A Behavioral-Neural Dual Swinging Model (DSM)

Poster Session B, Friday, October 25, 10:00 - 11:30 am, Great Hall 3 and 4

Keyi Kang1, Sifan Zhang1, Haoyun Zhang1; 1University of Macau

Conceptual preparation is the first step in language production. Endogenous semantic variables, reflecting inherent semantic properties of concepts, could influence productive lexical retrieval (Lampe et al., 2022, 2023). Among many variables, semantic richness, which refers to the number of semantic features associated with concepts, may enhance the accumulated activation spreading to the concept leading to conceptual facilitation. Semantic density, indicating the degree of intercorrelation among concepts, may activate more semantically related alternatives causing lexical interference (McRae et al., 2005; Abdel Rahman & Melinger, 2019; Rabovsky et al., 2021). The effects of conceptual facilitation and lexical interference, especially their interaction, are critical for understanding the effects of semantic variables on lexical retrieval. Yet, empirical understandings and underlying mechanisms of such process remain limited. Here, we propose a Behavioral-Neural Dual Swinging Model (DSM) revealing the swinging between conceptual facilitation and lexical interference, as well as extending the swinging to neural resource allocation. Specifically, processing concepts with more semantic features (i.e., higher semantic richness) requires more intensive semantic engagement and greater utilization of semantic-related neural resources. The cumulative activation of semantic features may elicit greater behavioral conceptual facilitation when retrieving target concepts. When the conceptual facilitation outweighs the lexical interference, there will be a facilitation-dominant effect associated with better behavioral performance and less engagement of domain-general regions. On the other hand, processing concepts with higher semantic density may induce interference from more co-activated competitors, demanding greater inhibitory control and the involvement of domain-general neural resources during lexical selection. When lexical interference outweighs the conceptual facilitation, there will be an inhibition-dominant effect associated with worse behavioral performance and greater engagement of domain-general regions. To further test the model, we examined the interactive effect of semantic richness and semantic density on productive word retrieval both behaviorally and neutrally, using a picture naming paradigm. Parametric modulation analyses were conducted to reveal the BOLD changes sensitive to the natural non-dichotomous distribution of semantic variables. Results showed that retrieving concepts with higher semantic richness was significantly associated with lower error rate and faster retrieval speed (ps < 0.001), along with greater involvement of semantic-related regions and less involvement of domain-general regions. Though there was no significant effect of semantic density behaviorally, processing concepts with higher semantic density engaged more cognitive control neural resources, indicating an overall interference effect. There was also a significant interaction between semantic richness and density on reaction time (p < 0.01). Further Johnson-Neyman analyses showed that the semantic density effect varied from significant inhibition to no effect to significant facilitation as semantic richness increased. Correspondingly, the facilitation from semantic richness could offset the interference of semantic density, leading to decreased involvement of domain-general regions. These results nicely support the DSM by showing that productive retrieval is driven by the swinging between semantic richness-induced conceptual facilitation primarily managed in semantic-related regions and semantic density-induced lexical interference managed in domain-general regions. Moreover, the conceptual facilitation accumulated from semantic richness plays a decisive role, mitigating interference from competitors and the neural demands in domain-general regions.

Topic Areas: Language Production, Meaning: Lexical Semantics

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