# Longitudinal Mapping of Human Brain Development in the First Years of Life > **NIH NIH R01** · UNIV OF NORTH CAROLINA CHAPEL HILL · 2022 · $490,211 ## Abstract Longitudinal Mapping of Human Brain Development in the First Years of Life Abstract This proposal requests continued funding support for research at the University of North Carolina at Chapel Hill to develop computational tools for quantifying longitudinal structural changes in the human brain. The previous project period has been extremely successful in advancing robust tools for longitudinal brain analysis of the aging brain. In this renewal, we seek to further advance robust computational tools for comprehensive longitudinal characterization of changes in the early developing brain. This is in line with our long-term goal of creating computational tools for longitudinal charting of brain evolution across the entire human lifespan. The tools to be developed in this project will allow unified and concurrent analysis of longitudinal volumetric data and cortical surfaces, facilitating the mapping of dynamic and spatially heterogeneous structural changes during a critical period of brain development. The tools developed in this project will be tailored to studying the human brain in the first few years of life, which undergoes dynamic development in both structure and function. We will utilize the MRI data made available via the Baby Connectome Project (BCP), involving 500 pediatric subjects scanned from birth to five years of age. The outcome of BCP will inform neuroscientists what normal healthy growth looks like and facilitate discovery of the earliest manifestations of brain disorders. To fully benefit from this unique dataset, dedicated computational tools are needed for accurate processing and analysis of baby MR images, which typically exhibit dynamic heteroge- neous changes across time. However, most computational tools developed to date have been mostly focused on adult subjects and are unreliable when applied to baby MRI. We propose to address this gap with three aims: In Aim 1, we will develop computational tools to allow multifaceted analysis of MRI data, including volumes and white-matter/pial surfaces, to be carried out in common spaces for a more holistic understanding of the early developing brain. Our tools will explicitly consider the rapid changes in MR image appearances that are typical in the first year of life. Unlike conventional methods that are designed for either image volumes or cortical surfaces, resulting in inconsistencies and loss of sensitivity to subtle changes, our tools will allow joint volume-surface analysis in consistent longitudinal spaces. Improving registration accuracy by drawing information from both entities is critical for detecting subtle changes in the developing brain, which is significantly smaller with a thinner cerebral cortex. In Aim 2, we will generate longitudinal, multimodal, and whole-brain parcellation maps for the early developing brain. Subdivision of the brain into coherent regions is an essential step in the macroscopic mapping of spa- tially heterogeneous changes and in the examination of spat... ## Key facts - **NIH application ID:** 10491702 - **Project number:** 5R01EB008374-10 - **Recipient organization:** UNIV OF NORTH CAROLINA CHAPEL HILL - **Principal Investigator:** Pew-Thian Yap - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2022 - **Award amount:** $490,211 - **Award type:** 5 - **Project period:** 2009-09-15 → 2025-06-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10491702 ## Citation > US National Institutes of Health, RePORTER application 10491702, Longitudinal Mapping of Human Brain Development in the First Years of Life (5R01EB008374-10). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10491702. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*