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Published on: June 3, 2013
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A multimodal neuroimaging dataset for investigating speech perceptual normalization.
Shun Liu1,2,3, Suiping Wang4
1Philosophy and Social Science Laboratory of Reading and Development in Children and Adolescents, South China Normal University, Guangzhou, Guangdong, China. liushun33@gmail.com.
Scientific Data
|December 3, 2025
Summary
Speech perception involves complex interactions between sounds and meaning. This study provides a unique neuroimaging dataset to explore how the brain processes segmental and suprasegmental speech features together.
Area of Science:
- Neuroscience
- Speech Perception
- Linguistics
Background:
- Speech perception faces challenges due to the lack of one-to-one mapping between acoustic signals and linguistic interpretations.
- Intrinsic normalization, where acoustic cues influence each other's categorization, is a key mechanism for resolving this ambiguity.
- Temporal overlap between segmental (consonant, vowel) and suprasegmental (tone) features creates complex interactions in speech processing.
Purpose of the Study:
- To address the underexplored neural basis of segmental-suprasegmental interactions in speech perception.
- To present a novel, integrated multimodal neuroimaging dataset specifically designed for studying speech normalization.
- To enable research into the neural representations and connectivity underlying the integration of different speech features.
Main Methods:
- Acquisition of multimodal neuroimaging data: structural MRI (sMRI), resting-state fMRI (rs-fMRI), task-based fMRI, and diffusion MRI (dMRI).
- Collection of behavioral data from 28 participants (14 females, mean age 20.79 ± 1.52 years).
- Participants completed two-alternative forced-choice categorization tasks involving consonant-tone and vowel-tone continua.
Main Results:
- The dataset captures neural and behavioral responses during the processing of interacting segmental and suprasegmental speech features.
- It allows for the examination of functional connectivity and white matter pathways involved in speech normalization.
- Provides a resource for investigating how the brain integrates acoustic information across different linguistic levels.
Conclusions:
- This multimodal dataset offers a unique resource for investigating the neural mechanisms of speech normalization.
- It facilitates exploration of how the brain integrates segmental and suprasegmental information during perception.
- Enables deeper understanding of the neural correlates of resolving acoustic-linguistic mapping ambiguities.
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