# ABCD-USA Consortium: Data Analysis, Informatics and Resource Center

> **NIH NIH U24** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2021 · $291,722

## Abstract

The recent emergence of publicly shared large-scale functional neuroimaging datasets (e.g.,
ABCD, HCP, ADNI, UK Biobank) offers many opportunities for robust and generalizable
research into population-level variability and disease biomarkers. However, comparing and
combining neuroimaging data across disparate projects is non-trivial due to systematic biases
that are introduced as a result of differences in acquisition hardware and/or protocols.
Therefore, there is an urgent need for advanced data harmonization methods that correct for
these biases and enable direct comparisons within and across large-scale neuroimaging
datasets. But to validate harmonization methods it is critical to have within-subject data
collected under these differing protocols, which currently does not exist.
To begin to address this problem, in this Administrative Supplement to the ABCD-USA
Consortium: Data Analysis, Informatics and Resource Center we propose to increase the
scientific utility and usability of five large-scale neuroimaging datasets (ABCD, HCP-Lifespan,
ADNI, UK Biobank, and Baby Connectome Project) by generating a within-subject, cross-project
neuroimaging harmonization dataset. This will enable: a) using one dataset as a replication data
set for analyses conducted on other datasets; and b) aggregating data across projects in order
to generate even larger sample sizes for sophisticated modeling and data-driven analyses,
including the ability to have out of sample generalization analyses. In addition, many other
investigators are generating datasets using one or more of these imaging protocols, and will
wish to harmonize both with the protocol from which they based their MR acquisitions, and with
other datasets. We will generate the data to develop and validate critically needed
harmonization methods, and make the data publicly available.

## Key facts

- **NIH application ID:** 10167380
- **Project number:** 3U24DA041123-07S1
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** ANDERS M DALE
- **Activity code:** U24 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $291,722
- **Award type:** 3
- **Project period:** 2015-09-30 → 2027-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10167380

## Citation

> US National Institutes of Health, RePORTER application 10167380, ABCD-USA Consortium: Data Analysis, Informatics and Resource Center (3U24DA041123-07S1). Retrieved via AI Analytics 2026-06-03 from https://api.ai-analytics.org/grant/nih/10167380. Licensed CC0.

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