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

> **NIH NIH K99** · YALE UNIVERSITY · 2024 · $132,867

## Abstract

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 ...

## Key facts

- **NIH application ID:** 10984620
- **Project number:** 1K99HD113838-01A1
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** Erin Isbilen
- **Activity code:** K99 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $132,867
- **Award type:** 1
- **Project period:** 2024-09-01 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10984620

## Citation

> US National Institutes of Health, RePORTER application 10984620, Behavioral and neural measures of phonological-to-orthographic transfer in young children (1K99HD113838-01A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10984620. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*