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Phoneme encoding during spoken language comprehension is enhanced by linguistic structure and by statistical experience

Poster Session E - Monday, March 31, 2025, 2:30 – 4:30 pm EDT, Back Bay Ballroom/Republic Ballroom

Filiz Tezcan1,2 (tezcanfiliz@gmail.com), Fan Bai1, Noémie te Rietmolen1, Sanne Ten Oever1,2,3, Andrea E. Martin1,2; 1Max Planck Institute for Psycholinguistics, Netherlands, 2Donders Centre for Cognitive Neuroimaging, Radboud University, Netherlands, 3Maastricht University, The Netherlands

The brain uses its knowledge of language (viz., linguistic units and structures, distributional statistics about them) to turn the physical expressions of speech and sign into meaning. However, how these two types of information come together in neural representations of language is an open question that deeply touches on how the information underlying human behavior can be encoded in the brain. Utilizing MEG data from native and non-native speakers listening to Dutch, Chinese, and Turkish speech stimuli, we examined phonemic and acoustic feature encoding during and in the absence of language comprehension. Phoneme features were more robustly encoded in sentences than in word lists, and within words compared to streams of random syllables. Furthermore, for the nonnative speakers, we found statistical experience with an uncomprehended language (i.e. a language speakers were familiar with) to enhance phoneme feature encoding to the same level as in a native language, while acoustic edge tracking was stronger than in the native language, possibly due to lack of suppression by higher-level representations. Our findings suggest that the phase alignment of neural signals with acoustic and phoneme features of speech undergoes dynamic modulation during comprehension based on linguistic structure and statistical experience. This study highlights the interplay between linguistic structure and statistical learning in neural speech processing, with implications for understanding how the brain integrates smaller linguistic units into more abstract structures.

Topic Area: LANGUAGE: Other

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