Exploring how language experience influences language development using AI models and brain imaging
Official title: Understanding how experience shapes language development through comparisons of large language models and neural representations
Funded at Massachusetts Institute of Technology · NIH-11165183 · Data updated 2026-11-12
This study is looking at how the amount of language kids and teens hear affects how their brains develop language skills, using brain scans to see how different age groups respond to language.
Quick facts
| Grant type | Fellowship grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Massachusetts Institute of Technology NIH-funded |
| Lab location | 1 site (Cambridge, United States) |
| Project start | April 1, 2025 |
| Project end | March 31, 2028 |
| Funding year | 2025 |
| Award (this year) | $75,520 |
| NIH project number | 1F32HD117580-01A1 |
| Project ID | NIH-11165183 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for participation are children and adolescents aged 6 to 16 who are in the process of acquiring language skills.
✕Less likely to help
Patients who are not within the specified age range or who do not have language acquisition challenges may not benefit from this research.
What this research studies
This research investigates how language experience affects language development in children and adolescents by comparing brain activity with large language models (LLMs). Using advanced brain imaging techniques, the study will measure how different age groups respond to language and how these responses relate to the amount of language data they have been exposed to. By analyzing brain patterns and LLM outputs, the research aims to uncover the developmental changes in language representation in the brain. Participants will include children and adolescents from various age groups, providing insights into the critical role of language experience in shaping language skills.
Why it matters
Potential benefit: If successful, this research could enhance our understanding of language development, potentially leading to improved educational strategies and interventions for children with language acquisition challenges.
How similar studies have gone: Other research has shown promising results in using AI models to understand cognitive processes, suggesting that this approach could yield valuable insights into language development.
Where this research is happening
-
Massachusetts Institute of Technology
Cambridge, United States Active
Researchers
- Principal investigator: Olson, Halie Ann — Massachusetts Institute of Technology
- Study coordinator: Olson, Halie Ann
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.