Hierarchical neural encoding in multilingual contexts

Activity: Talk/lecture or presentationPresentation

Description

Language comprehension involves understanding a hierarchy of linguistic units, including phonemes, words, phrases, sentences, and paragraphs. Hasson et al. (2015) proposed a hierarchy along the temporal-parietal axis, with increasing temporal receptive windows supporting the processing of phonemes and syllables to higher-level units such as words and phrases. However, limited research has been conducted in cross-language contexts. In the present study, we investigated the neural encoding of three languages (Chinese, English, French) across three linguistic hierarchies (word, sentence, paragraph) by scanning participants with functional magnetic resonance imaging (fMRI) while they listened to a naturalistic story (Li et al., 2022). Voxel-wise modeling with Large Language Model (LLM) embeddings was utilized to analyze the collected data (Huth et al., 2016). Finally, we identified three distinct clusters within the left temporal lobe, spanning from more anterior to more posterior regions. These clusters corresponded to the semantic features at the word, sentence, and paragraph levels, respectively. This distribution pattern was found to be consistent across all three languages. The temporal dynamics of these semantic features revealed a higher degree of similarity in tracking sentence- and paragraph-level information across the three languages. This suggests a commonality in how these higher-level linguistic units are processed and represented in the brain, irrespective of the specific language being processed.
Period9 Dec 2023
Event title18th International Conference on the Processing of East Asian Languages (ICPEAL 2023)
Event typeConference
LocationHong Kong, ChinaShow on map
Degree of RecognitionInternational