Lauren Salig, Chi‐Lin Yu, Molly Leachman, Nivedhitha Dondati Purushotham, Valeria Ortiz-Villalobos, Zahira Flores-Gaona, Viviana Vélez Negrón, C. Girardini, Hsin-Yuan Fang, Alisa Baron, Lisa M. Bedore, James R. Booth, Elizabeth D. Peña, Teresa Satterfield, Jonathan Brennan, Ioulia Kovelman
Our understanding of the neurobiology of language development is imprecise, particularly for bilingual children in their heritage language, since much research focuses on monolingual children or societal majority languages. In this study, we use a novel computational approach to quantifying linguistic predictions with fNIRS neuroimaging to examine bilingual children's (N = 88, ages 7-12) brain activity as they listen to a naturalistic story in their heritage language of Spanish. The children demonstrated successful neural tracking of word predictability in their heritage language, suggesting they can form rich linguistic representations in Spanish. There were some trends for reading and listening comprehension abilities in English and Spanish to modulate neural tracking of predictability in a Spanish story, but no effects were reliable enough to interpret with confidence. Overall, this first use of a predictability-based computational, naturalistic listening comprehension approach with bilingual children demonstrates the feasibility of this approach and its utility for studying language development.