# Neuroimaging Core

> **NIH NIH U19** · BOSTON UNIVERSITY MEDICAL CAMPUS · 2024 · $3,062,001

## Abstract

NEUROIMAGING CORE SUMMARY
Much has yet to be understood about the brains of "superagers" and what and how resilience
factors impact the typical brain-aging trajectory, and identify which aspects of brain reserve are
most associated with preserved cognition functioning in centenarian cognitive superagers. The
Neuroimaging Core oversees the acquisition, storage, and analysis of imaging data at three
participating imaging centers: MGH (Boston), Columbia University (NYC), and UCLA (Los
Angeles). These sites have identical scanners, the Siemens Prisma 3T MRI, that are also
the most advanced pulse sequencers available. The Core will optimize acquisition and analysis
approaches to ensure that the data across centers are highly standardized and achieve equivalent
contrast to noise ratios (CNRs) to ensure that data integration is successful. The Core's broad
goal is to answer specific questions about resilience by identifying a set of high-resolution
pulse sequences that examine brain structure and function, in a time interval tolerable for
centenarians, using state of the art data analysis techniques. The NIC's general hypothesis
is that preserved structural and functional connectivity are essential to long-term preserved
cognition. This hypothesis will be tested by generating optimal MRI data combined with analysis
tools designed to examine network dynamics and longitudinal trajectories, focusing on brain
networks and regions most critical to cognition and memory. The three specific aims are: Aim
1:Test and employ across three sites, state of the art pulse sequences on the Prisma platform
that are essential for understanding the resilient brain structure including Multi-echo/Multiband,
navigator high-resolution T1/T2, resting-state functional connectivity MR, Diffuser Tensor
Imaging, Pseudo-Continuous Arterial Spin Labeling, and Quantitative Susceptibility Mapping.
Aim 2:Perform ongoing with-and between-site QA, pre-processing for image standardization
and bias corrections, and centralize data across sites into an imaging data repository. Aim 3:
Conduct image analysis that combines data across sites/within modality; create output metrics
for each data-type, and in conjunction with the projects, assist in integrating imaging
measures into project hypotheses. The imaging centers are joined and further integrated by a
state-of-the-art data analysis center at the University of Utah. Experts in imaging statistics
interface with the other RADCO cores and projects to integrate data types for hypothesis testing.

## Key facts

- **NIH application ID:** 10907589
- **Project number:** 5U19AG073172-04
- **Recipient organization:** BOSTON UNIVERSITY MEDICAL CAMPUS
- **Principal Investigator:** SUSAN Y BOOKHEIMER
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $3,062,001
- **Award type:** 5
- **Project period:** 2021-09-30 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10907589

## Citation

> US National Institutes of Health, RePORTER application 10907589, Neuroimaging Core (5U19AG073172-04). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10907589. Licensed CC0.

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