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Tai-Li Chou
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Journal Articles
Publisher: Journals Gateway
Neurobiology of Language (2023) 4 (2): 198–220.
Published: 11 April 2023
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View articletitled, Sources of Heterogeneity in Functional Connectivity During English Word Processing in Bilingual and Monolingual Children
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for article titled, Sources of Heterogeneity in Functional Connectivity During English Word Processing in Bilingual and Monolingual Children
Diversity and variation in language experiences, such as bilingualism, contribute to heterogeneity in children’s neural organization for language and brain development. To uncover sources of such heterogeneity in children’s neural language networks, the present study examined the effects of bilingual proficiency on children’s neural organization for language function. To do so, we took an innovative person-specific analytical approach to investigate young Chinese-English and Spanish-English bilingual learners of structurally distinct languages. Bilingual and English monolingual children ( N = 152, M ( SD ) age = 7.71(1.32)) completed an English word recognition task during functional near-infrared spectroscopy neuroimaging, along with language and literacy tasks in each of their languages. Two key findings emerged. First, bilinguals’ heritage language proficiency (Chinese or Spanish) made a unique contribution to children’s language network density. Second, the findings reveal common and unique patterns in children’s patterns of task-related functional connectivity. Common across all participants were short-distance neural connections within left hemisphere regions associated with semantic processes (within middle temporal and frontal regions). Unique to more proficient language users were additional long-distance connections between frontal, temporal, and bilateral regions within the broader language network. The study informs neurodevelopmental theories of language by revealing the effects of heterogeneity in language proficiency and experiences on the structure and quality of emerging language neural networks in linguistically diverse learners.
Includes: Supplementary data
Journal Articles
Publisher: Journals Gateway
Neurobiology of Language (2021) 2 (2): 280–307.
Published: 09 June 2021
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Abstract
View articletitled, Emerging Native-Similar Neural Representations Underlie Non-Native Speech Category Learning Success
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for article titled, Emerging Native-Similar Neural Representations Underlie Non-Native Speech Category Learning Success
Learning non-native phonetic categories in adulthood is an exceptionally challenging task, characterized by large interindividual differences in learning speed and outcomes. The neurobiological mechanisms underlying the interindividual differences in the learning efficacy are not fully understood. Here we examine the extent to which training-induced neural representations of non-native Mandarin tone categories in English listeners ( n = 53) are increasingly similar to those of the native listeners ( n = 33) who acquired these categories early in infancy. We assess the extent to which the neural similarities in representational structure between non-native learners and native listeners are robust neuromarkers of interindividual differences in learning success. Using intersubject neural representational similarity (IS-NRS) analysis and predictive modeling on two functional magnetic resonance imaging datasets, we examined the neural representational mechanisms underlying speech category learning success. Learners’ neural representations that were significantly similar to the native listeners emerged in brain regions mediating speech perception following training; the extent of the emerging neural similarities with native listeners significantly predicted the learning speed and outcome in learners. The predictive power of IS-NRS outperformed models with other neural representational measures. Furthermore, neural representations underlying successful learning were multidimensional but cost-efficient in nature. The degree of the emergent native-similar neural representations was closely related to the robustness of neural sensitivity to feedback in the frontostriatal network. These findings provide important insights into the experience-dependent representational neuroplasticity underlying successful speech learning in adulthood and could be leveraged in designing individualized feedback-based training paradigms that maximize learning efficacy.
Includes: Supplementary data