Poster No:
820
Submission Type:
Abstract Submission
Authors:
Ling Liu1, Hua Fan2, YuTing Meng2
Institutions:
1Beijing Language and Culture University, BEIJING, BEIJING, 2Beijing Language and Culture University, Beijing, Beijing
First Author:
Ling Liu
Beijing Language and Culture University
BEIJING, BEIJING
Co-Author(s):
Hua Fan
Beijing Language and Culture University
Beijing, Beijing
YuTing Meng
Beijing Language and Culture University
Beijing, Beijing
Introduction:
Speech perception is fundamental for human communication, especially in tonal languages where semantic information is encoded via consonants, vowels, and lexical tone. However, the exact phonological representation during syllable perception remains elusive.
Methods:
We carried out three parallel experiments using magnetoencephalography (MEG). In the syllables task (n = 27 subjects), participants judged if the overall of preceding (audio1) and following (audio2) syllables were the same. In the tone task (n = 30), they determined tone similarity, and in the consonant task (n = 19), consonant likeness. We focused on brain responses to audio2 and applied multivariate pattern analysis (MVPA) to decode phonemic features from MEG sensor signals of both audio1 and audio2.
Results:
After audio2 onset, we decoded not only its own phonological features but also those of audio1, indicating that audio2 perception triggers audio1 phonological reactivation. In the 200 - 400 ms window post-audio2 onset, the syllables task reactivated consonant, vowel, and tone; the tone task reactivated only tone and vowel; the consonant task reactivated only consonant and vowel.
Conclusions:
Our findings suggest that during tonal language syllable perception, consonant, vowel, and tone phonological attributes are active. Consonant and tone encodings are separate, while consonant-vowel and vowel-tone representations are interconnected. We propose a novel hypothesis that the syllabic representation structure of consonant-vowel-tone is stored distinctly as C - V and V - T forms. This research advances our understanding of phonological representation in tonal language speech perception and offers a new perspective on syllabic representation storage.
Language:
Speech Perception 1
Learning and Memory:
Working Memory
Modeling and Analysis Methods:
EEG/MEG Modeling and Analysis
Multivariate Approaches
Novel Imaging Acquisition Methods:
MEG 2
Keywords:
Cognition
Consciousness
Hearing
Hemispheric Specialization
Language
Machine Learning
MEG
Multivariate
Perception
1|2Indicates the priority used for review
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Please indicate below if your study was a "resting state" or "task-activation” study.
Task-activation
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Healthy subjects
Was this research conducted in the United States?
No
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel?
NOTE: Any human subjects studies without IRB approval will be automatically rejected.
Yes
Were any animal research approved by the relevant IACUC or other animal research panel?
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Not applicable
Please indicate which methods were used in your research:
MEG
Which processing packages did you use for your study?
Other, Please list
-
MNE-python
Provide references using APA citation style.
not applicable
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