# Continuous longitudinal atlas construction for the study of brain development

> **NIH NIH R01** · MASSACHUSETTS GENERAL HOSPITAL · 2022 · $512,489

## Abstract

Abstract:
There is rapid development of the cerebral cortex that takes place during the perinatal period. In
order to characterize this complex process spatio-temporal atlases are needed. At present,
however, there is limited availability of cortical surface atlases for the infant brain. The
development of robust tools applicable to this population has been significantly lagging compared
to those introduced for adults given the difficulty of obtaining data from non-compliant neonates
and toddlers and the rapid change in contrast and geometry displayed during development in
infants. With the advent of large longitudinal brain imaging studies, such as the UNC/UMN Baby
Connectome Project (BCP) and HEALthy Brain and Child Development (HBCD) Study, novel
algorithmic solutions are needed to efficiently process these data sets. During the proposed
project, we intend to develop a FreeSurfer-compatible pipeline that will establish a consistent and
unbiased representation of the perinatal cortex over time and a set of tools that, when used with
standard clinical MRI acquisitions, will enable the computation of accurate and robust spherical
representations of the developing brain along with detailed macrostructural annotations. Such
surfaces then will be used to characterize healthy brain development over the first ten years of
life. For our clinical application, we will focus on the effects of early life adversity on brain
development as well as on disentangling contradictory findings about brain abnormalities in very
preterm infants, such as gyrification complexity in their anterior and posterior temporal lobes. This
work will be performed at the MGH/Harvard/MIT Martinos Center for Biomedical Imaging relying
on datasets collected by local collaborators, NIH-funded publicly available large scale data sets
as well as a clinical cohort assembled by colleagues at the Washington University. Such an effort
will allow us to take advantage of cutting-edge neonatal imaging and computational algorithm
development expertise in an attempt to deliver computational tools robust and accurate enough
for future clinical studies

## Key facts

- **NIH application ID:** 10499546
- **Project number:** 1R01HD109436-01
- **Recipient organization:** MASSACHUSETTS GENERAL HOSPITAL
- **Principal Investigator:** Lilla Zollei
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $512,489
- **Award type:** 1
- **Project period:** 2022-08-12 → 2027-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10499546

## Citation

> US National Institutes of Health, RePORTER application 10499546, Continuous longitudinal atlas construction for the study of brain development (1R01HD109436-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10499546. Licensed CC0.

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