Visualization Process of Perceptual Features in Language Comprehension: A Bidirectional Comparison of Chinese-English and English- Chinese Bilinguals

The mental simulation theory of lexical comprehension holds that word understanding activates perceptual simulation. This process should integrate multiple perceptual features. However, empirical support has been limited to single-feature visualization. Multi-feature visualization remains largely unexplored. Bocanegra et al. (2022) found a dual-feature advantage only under sequential presentation. This supports sequential feature-concatenation processing. Our pilot study detected a dual-feature advantage under simultaneous presentation. Chinese lexical visualization may therefore achieve feature integration more rapidly. Compound words predominate in the Chinese lexicon and encode multiple perceptual features. We hypothesized that Chinese-English (CE) and English-Chinese (EC) bilinguals differ in their visualization processes. Presentation condition (simultaneous/sequential) was the primary independent variable. Ninety-eight EC and 140 CE bilinguals completed Chinese and English visualization tasks. Dual-feature and single-feature advantages were compared across three conditions. None of the four pre-registered hypotheses reached the predetermined significance criterion. Sensitivity analyses showed that increasing stimuli in the English visualization task would yield the recommended statistical power for the expected effect size. An exploratory analysis used language entropy as a continuous measure. EC bilinguals' task performance showed a trend toward correlation with language entropy scores. This finding requires further replication. A supplementary proficiency measure showed no significant L1–L2 difference for EC bilinguals. Their scores approached CE bilinguals' English proficiency. Dual-feature advantages were absent across all three presentation conditions. This reveals the limitations of mental simulation theory in predicting multi-feature visualization. The moderating role of language background remains unconfirmed. Future research should combine valid measurement indices. Language entropy is recommended as an effective index to estimate the moderation.