The critical role of interference control in metaphor comprehension evidenced by the drift\u2013diffusion model

Hee-Dong Yoon,Minho Shin,Hyeon-Ae Jeon

doi:10.1038/s41598-021-98351-8

Hee-Dong Yoon, Minho Shin + Show 1 more

Open Access

https://doi.org/10.1038/s41598-021-98351-8

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Abstract

We address the question of, among several executive functions, which one has a strong influence on metaphor comprehension. To this end, participants took part in a metaphor comprehension task where metaphors had varying levels of familiarity (familiar vs. novel metaphors) with different conditions of context (supporting vs. opposing contexts). We scrutinized each participant’s detailed executive functions using seven neuropsychological tests. More interestingly, we modelled their responses in metaphor comprehension using the drift–diffusion model, in an attempt to provide more systematic accounts of the processes underlying metaphor comprehension. Results showed that there were significant negative correlations between response times in metaphor comprehension and scores of the Controlled Oral Word Association Test (COWAT)-Semantic, suggesting that better performances in comprehending metaphors were strongly associated with better interference control. Using the drift–diffusion model, we found that the familiarity, compared to context, had greater leverage in the decision process for metaphor comprehension. Moreover, individuals with better performance in the COWAT-Semantic test demonstrated higher drift rates. In conclusion, with more fine-grained analysis of the decisions involved in metaphor comprehension using the drift–diffusion model, we argue that interference control plays an important role in processing metaphors.

Highlights

We address the question of, among several executive functions, which one has a strong influence on metaphor comprehension
Participants were engaged in a metaphor comprehension task
There were four experimental conditions: a supporting context paired with a familiar metaphor (SC–FM) or a novel metaphor (SC–NM), and an opposing context paired with a familiar metaphor (OC–FM) or a novel metaphor (OC–NM)

Summary

Introduction

This type of speech, known as a metaphor, is constructed by linking one thing to another that has seemingly different concepts but shares relevant features In this example, people comprehend the sentence by comparing the topic (the subject of the metaphor: time) and the vehicle (the word used for a metaphor expression: money) of the metaphor based on the ground (the common and relevant features between the topic and vehicle: valuable). Components of response processing seem to be entangled in individuals’ response speed or accuracy, and we need to disentangle them from each other and account for them in detail To this end, we conducted computational cognitive modeling with the drift–diffusion m odel[9,10,11] to estimate and control for individual differences in metaphor processing with varying levels of familiarity and context. We focused on how performance differences in metaphor comprehension could be demonstrated by different parameters of the diffusion model

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