BRAIN Initiative: Brain Behavior Quantification and Synchronization Data Coordination and Artificial Intelligence Center (U24 Clinical Trial Optional) | RFA MH 23 130

Opportunity Information: Apply for RFA MH 23 130

The National Institutes of Health is soliciting applications under RFA-MH-23-130 to establish a single, centralized Data Coordination and Artificial Intelligence Center (DCAIC) for the BRAIN Initiative's Brain Behavior Quantification and Synchronization (BBQS) Consortium. The award mechanism is a U24 cooperative agreement (clinical trial optional), which usually means NIH expects substantial involvement in steering, coordination, and milestone-driven progress rather than a hands-off grant. The goal is to stand up an organizing and technical hub that can reliably handle the consortium's data flow, harmonize how data are described and shared, and provide modern machine learning and AI support so the broader research community can make use of the consortium's outputs.

The DCAIC is meant to be run by a multi-disciplinary team (with either a single PI or multiple PIs) that can cover five connected functions. First is Data Management, which in practical terms means building and operating the pipelines and infrastructure needed to ingest, curate, quality-check, store, version, and distribute consortium data. Because this is a data coordination center, the expectation is not just passive storage, but active oversight of data integrity, metadata completeness, traceability/provenance, access controls where needed, and the day-to-day operational support required to keep multi-site data submission running smoothly.

Second is Data Standards, focused on making sure the consortium uses consistent formats, metadata conventions, ontologies, and documentation so that datasets can be combined and compared across labs and platforms. This typically includes developing or adopting common data elements, defining validation rules, creating templates and submission checklists, and aligning with broader NIH and BRAIN data-sharing expectations. The emphasis is on interoperability: data should not only be shared, but shared in a way that makes it realistically reusable by other groups without extensive reformatting.

Third is ML/AI Resources. The center is expected to provide machine learning and artificial intelligence enablement for the consortium's data. In a DCAIC context, that often translates into creating shared computational resources, baseline models or benchmarking pipelines, well-documented training datasets, and tools that allow researchers to apply ML/AI methods reproducibly. It can also include guidance on best practices for model evaluation, managing bias and generalization issues, and ensuring that AI workflows are auditable and repeatable across sites.

Fourth is the Data Ecosystem, which is essentially the broader platform and integration layer that connects BBQS data, tools, standards, and users. This can include building portals or interfaces, APIs, search and discovery capabilities, links to relevant repositories, and compatibility with existing neuroscience data infrastructures. The underlying idea is that the DCAIC should not become an isolated silo; it should function as a connective tissue that helps data move from generation to harmonization to analysis to public reuse, while staying aligned with the larger BRAIN Initiative ecosystem.

Fifth is Dissemination, Training, and Coordination. Beyond technical build-out, the center is expected to coordinate consortium-wide practices and communicate them clearly to both consortium members and the wider community. This usually includes running training sessions and workshops, maintaining user-facing documentation, providing help-desk style support, organizing meetings and working groups, and creating educational materials so that external users can actually find, understand, and use the data and tools. Because it is a cooperative agreement supporting a single award, this coordinating role is central: the DCAIC is effectively the operational backbone that keeps standards, timelines, and deliverables aligned across participating projects.

In terms of eligibility, NIH lists a wide range of applicants, including state, county, city, and special district governments; independent school districts; public and state-controlled institutions of higher education; private institutions of higher education; tribal governments (federally recognized); tribal organizations (including those other than federally recognized); public housing authorities/Indian housing authorities; nonprofits with and without 501(c)(3) status; for-profit organizations (other than small businesses) as well as small businesses; and other entities. The FOA also explicitly calls out additional eligible applicant types such as Alaska Native and Native Hawaiian Serving Institutions, Asian American Native American Pacific Islander Serving Institutions (AANAPISIs), Hispanic-serving institutions, Historically Black Colleges and Universities (HBCUs), Tribally Controlled Colleges and Universities (TCCUs), faith-based or community-based organizations, eligible federal agencies, regional organizations, non-domestic (non-U.S.) entities, and U.S. territories or possessions. This broad eligibility signals NIH's openness to teams that combine academic, nonprofit, government, and industry capabilities, particularly if that mix strengthens data infrastructure, standards leadership, and AI/ML implementation.

Administrative details included in the posting are that it is a discretionary funding opportunity, categorized under education/health/income security and social services, and associated with multiple CFDA numbers (93.173, 93.213, 93.242, 93.273, 93.279, 93.286, 93.853, 93.865, 93.866, 93.867), reflecting the cross-institute nature of NIH programs that commonly support BRAIN-related efforts. The opportunity was created on 2023-03-31 with an original closing date of 2023-07-14. The announcement indicates NIH intends to make a single award for this DCAIC, reinforcing that the selected team will serve as the central coordinating entity for the entire BBQS consortium.

• The National Institutes of Health in the education, health, income security and social services sector is offering a public funding opportunity titled "BRAIN Initiative: Brain Behavior Quantification and Synchronization Data Coordination and Artificial Intelligence Center (U24 Clinical Trial Optional)" and is now available to receive applicants.
• Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 93.173, 93.213, 93.242, 93.273, 93.279, 93.286, 93.853, 93.865, 93.866, 93.867.
• This funding opportunity was created on 2023-03-31.
• Applicants must submit their applications by 2023-07-14. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
• Eligible applicants include: State governments, County governments, City or township governments, Special district governments, Independent school districts, Public and State controlled institutions of higher education, Native American tribal governments (Federally recognized), Public housing authorities/Indian housing authorities, Native American tribal organizations (other than Federally recognized tribal governments), Nonprofits having a 501 (c) (3) status with the IRS, other than institutions of higher education, Nonprofits that do not have a 501 (c) (3) status with the IRS, other than institutions of higher education, Private institutions of higher education, For-profit organizations other than small businesses, Small businesses, Others.

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