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Active OTHER RESEARCH-RELATED NIH (US)

Behavioral and neural measures of phonological-to-orthographic transfer in young children

$1.33M USD

Funder EUNICE KENNEDY SHRIVER NATIONAL INSTITUTE OF CHILD HEALTH & HUMAN DEVELOPMENT
Recipient Organization Yale University
Country United States
Start Date Sep 01, 2024
End Date Aug 31, 2026
Duration 729 days
Number of Grantees 1
Roles Principal Investigator
Data Source NIH (US)
Grant ID 10984620
Grant Description

Project summary: A key component in the development of linguistic proficiency is the capacity to learn the statistical regularities present in the ambient language environment, largely by mere exposure. This basic cognitive process enables the discovery of the words and grammatical relations present in speech, and also enables the identification of

these structures in written text. Although groundbreaking strides have been made in linking the independent contributions of auditory and visual statistical learning—the ability to learn from distributional patterns—to literacy, recent meta-analyses reveal that nearly none have analyzed how statistical learning facilitates the cross-

modal transfer between auditory and written linguistic information, a skill that is critical to literacy development. Moreover, while prior research has established connections between statistical learning and language skills in literate children, fewer studies have explored its contribution to language outcomes in speaking, pre-literate

children, and how this connection changes over the course of reading development. Furthermore, measures such as phonological awareness and rapid automatized naming, while reliable correlates of reading, recruit a host of skills, making it difficult to pinpoint the precise mechanisms that support proficient reading.

My goal is to better understand how individual differences in statistical learning impact the cross-modal transfer from auditory materials in spoken language to written text during the initial stages of reading development, and how phonological skills are in turn influenced by learning how to read. My Specific Aims are:

1) to establish implicit neural-entrainment markers of auditory and visual statistical learning in literate children (8-10-year-olds) to measure phonology-to-orthography and orthography-to-phonology transfer, and 2) to determine how the implicit neural-entrainment markers of statistical learning across modalities

predict readiness to read in pre-literate children (4-5-year-olds) and their future reading performance. The use of EEG will allow me to uncover indices of learning and processing that behavioral measures may be insensitive to in young children, affording clearer insights into early literacy development.

In the K99-phase, I will be trained by world-experts in neurocognitive-linguistic development to conduct EEG studies designed to identify neural indices of how statistical learning drives phonology-to-orthography and orthography-to-phonology transfer, my first foray into neuroimaging. In the R00-phase, I will apply the skills and

measures developed during the K99-phase to determine how neural processing predicts individual differences in key reading precursors in pre-literate children and shapes future reading aptitude longitudinally. Combining neuroimaging with the behavioral methodologies of statistical learning and language that I pioneered during my

doctoral and postdoctoral work will kickstart my scientific career and facilitate my transition to an independent, tenure-track position by equipping me with the techniques needed to conduct rigorous, interdisciplinary cognitive neuroscience research with the potential to benefit public health and education.

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Yale University

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