Opportunity Information: Apply for RFA MH 21 130
The funding opportunity "BRAIN Initiative: Secondary Analysis and Archiving of BRAIN Initiative Data (R01 Clinical Trial Not Allowed)" (Funding Opportunity Number: RFA-MH-21-130) is a National Institutes of Health (NIH) discretionary grant that supports research using existing neuroscience data to advance the goals of the BRAIN Initiative, especially the goal of understanding brain circuits. This announcement is a reissue of an earlier solicitation (RFA-MH-20-120) and is focused on getting more value out of data that have already been collected, either by enabling new discoveries through secondary analysis and data mining or by improving the accessibility and long-term utility of valuable BRAIN-relevant datasets through archiving.
At its core, the program is designed for projects that do not need to generate new primary data to be impactful. Instead, it encourages applicants to use existing datasets to ask questions that could not realistically be answered within the limits of a single study, a single laboratory, or a single experimental technology. That includes proposing and testing new hypotheses that were outside the original aims of the data-generating studies, as well as revisiting existing datasets with newer analytical tools, computational approaches, or integrative methods that were not available or not applied at the time the data were first produced. In practical terms, the most competitive ideas are likely to be those that clearly show how the proposed analyses will reveal new insights about neural circuits or circuit function, rather than simply reproducing or lightly extending prior work.
The opportunity also explicitly invites applications focused on data preparation and submission to BRAIN Initiative data archives. That means a project can be built around curating, organizing, harmonizing, annotating, formatting, and documenting high-value datasets so they can be deposited into an appropriate BRAIN archive and be reusable by the broader community. This emphasis reflects a broader BRAIN and NIH priority: making sure that expensive, complex, and unique neuroscience datasets do not remain difficult to find or difficult to reuse due to inconsistent metadata, incomplete documentation, or nonstandard formats. A strong archiving-focused application would typically explain why the data are particularly valuable for circuit-level understanding, what steps are needed to make the data interoperable and usable, and how the final archived product will meet archive requirements and serve future secondary analyses by others.
Methodologically, the FOA is open to a wide range of approaches as long as they are applied to existing data and are aimed at new scientific aims. It highlights innovative analyses, data mining, and novel combinations or integrations of datasets. This could include, for example, combining datasets across modalities (such as electrophysiology with imaging, or behavioral measurements with neural recordings), across cohorts or labs, or across experimental contexts to look for circuit principles that generalize. It can also include applying modern computational techniques, improved statistical frameworks, or newer signal processing and machine learning tools to extract information that was previously hidden, too noisy, or too complex to interpret. The unifying theme is that the proposed work should produce new knowledge or new community resources from data that already exist.
This is an R01 funding mechanism, and the FOA states "Clinical Trial Not Allowed," meaning the proposed project cannot include a clinical trial as defined by NIH. The program is therefore aimed at secondary research and data resource activities rather than prospective interventional studies. The award ceiling listed for this opportunity is $300,000, and it is administered by NIH under 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 involvement of multiple NIH components and mission areas relevant to neuroscience and mental health.
Eligibility is broad and includes many types of organizations. Eligible applicants include state, county, and city or township governments; special district governments; independent school districts; public and state-controlled institutions of higher education; private institutions of higher education; federally recognized Native American tribal governments; other Native American tribal organizations; public housing authorities/Indian housing authorities; nonprofits with or without 501(c)(3) status (other than higher education institutions); for-profit organizations (other than small businesses); and small businesses. The FOA also calls out additional eligible applicant categories such as Alaska Native and Native Hawaiian Serving Institutions, AANAPISIs, Hispanic-serving Institutions, Historically Black Colleges and Universities, Tribally Controlled Colleges and Universities, faith-based or community-based organizations, eligible federal agencies, regional organizations, U.S. territories or possessions, tribal governments that are not federally recognized, and non-U.S. entities (foreign organizations). This wide eligibility signals an intention to draw from diverse research and data-science communities, including organizations that may contribute specialized analytic expertise, unique datasets, or strong data stewardship capabilities.
Key administrative details from the source include an original closing date of 2021-10-07 and a creation date of 2021-03-10. While those dates indicate this specific posting was tied to a particular application cycle, the program description is still useful for understanding NIH priorities around BRAIN data reuse and archiving. Overall, the opportunity is best understood as support for high-impact work that either (1) extracts new circuit-level insights from existing BRAIN-relevant data through sophisticated secondary analysis, or (2) turns important but underutilized datasets into well-documented, archived resources that can fuel many future discoveries.Apply for RFA MH 21 130
- The National Institutes of Health in the education, health, income security and social services sector is offering a public funding opportunity titled "BRAIN Initiative: Secondary Analysis and Archiving of BRAIN Initiative Data (R01 Clinical Trial Not Allowed)" 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 2021-03-10.
- Applicants must submit their applications by 2021-10-07. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
- Each selected applicant is eligible to receive up to $300,000.00 in funding.
- 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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Frequently Asked Questions (FAQs)
What is the name of this funding opportunity?
The opportunity is titled "BRAIN Initiative: Secondary Analysis and Archiving of BRAIN Initiative Data (R01 Clinical Trial Not Allowed)."
What is the Funding Opportunity Number (FOA number)?
The Funding Opportunity Number is RFA-MH-21-130.
Who is the funding agency?
This is a National Institutes of Health (NIH) discretionary grant opportunity.
What is the main purpose of this FOA?
The FOA supports projects that increase the value of existing neuroscience data relevant to the BRAIN Initiative. It emphasizes (1) secondary analysis/data mining to enable new discoveries and (2) archiving activities that improve accessibility and long-term utility of high-value datasets.
How does this FOA relate to the BRAIN Initiative?
The FOA is intended to advance BRAIN Initiative goals, with particular emphasis on understanding brain circuits and circuit function using existing datasets.
Is this FOA new, or is it a reissue?
It is a reissue of an earlier solicitation, RFA-MH-20-120.
What kinds of projects are a good fit for this program?
Projects that do not need to generate new primary data to be impactful. Competitive projects typically propose secondary analyses that lead to new circuit-level insights, or archiving-focused work that turns valuable datasets into reusable community resources.
Does the FOA allow collection of new primary data?
The program is designed around existing data and is focused on getting more value from data that have already been collected. The emphasis is on secondary analysis and/or data preparation for archiving rather than generating new primary datasets.
What is meant by "secondary analysis" in this FOA?
Secondary analysis refers to using existing datasets to answer new questions. This can include proposing and testing hypotheses that were outside the original study aims, or reanalyzing data using newer analytical tools, computational approaches, or integrative methods that were not available or not applied when the data were first produced.
What types of scientific questions are especially encouraged?
Questions that cannot realistically be answered within the limits of a single study, a single laboratory, or a single experimental technology, and that clearly aim to reveal new insights about neural circuits or circuit function.
What does the FOA say about reproducing prior work?
The FOA emphasizes that the most competitive projects are likely to go beyond simply reproducing or lightly extending prior work, and instead should demonstrate how the analyses will produce genuinely new insights about circuits or circuit function.
What kinds of methods or approaches are allowed?
A wide range of approaches are allowed as long as they are applied to existing data and serve new scientific aims. The FOA highlights innovative analyses, data mining, and novel combinations or integrations of datasets.
Can applicants integrate multiple datasets or modalities?
Yes. The FOA explicitly highlights novel combinations or integrations of datasets, including combining data across modalities (for example, electrophysiology with imaging, or behavioral measures with neural recordings), across cohorts or labs, or across experimental contexts.
Can modern computational or machine learning tools be used?
Yes. The FOA highlights applying modern computational techniques, improved statistical frameworks, and newer signal processing or machine learning tools to extract information that was previously hidden, too noisy, or too complex to interpret.
What is the archiving component of this FOA?
The FOA invites applications focused on preparing and submitting BRAIN-relevant datasets to BRAIN Initiative data archives. This can include curating, organizing, harmonizing, annotating, formatting, and documenting datasets so they can be deposited and reused by the broader community.
Why does the FOA emphasize archiving and data preparation?
It reflects NIH and BRAIN priorities to ensure that expensive, complex, and unique neuroscience datasets remain findable and reusable, rather than being difficult to reuse due to inconsistent metadata, incomplete documentation, or nonstandard formats.
What would a strong archiving-focused application typically address?
Based on the FOA description, a strong archiving-focused project would typically explain why the dataset is valuable for circuit-level understanding, what steps are needed to make it interoperable and usable, and how the final archived product will meet archive requirements and support future secondary analyses by others.
What is the funding mechanism?
The FOA uses the R01 mechanism.
Are clinical trials allowed under this FOA?
No. The FOA states "Clinical Trial Not Allowed," meaning the proposed project cannot include a clinical trial as defined by NIH.
What is the award ceiling for this opportunity?
The award ceiling listed is $300,000.
Which CFDA numbers are associated with this opportunity?
The FOA is administered under multiple CFDA numbers: 93.173, 93.213, 93.242, 93.273, 93.279, 93.286, 93.853, 93.865, 93.866, and 93.867.
Who is eligible to apply?
Eligibility is broad. Eligible applicants include: state, county, and city or township governments; special district governments; independent school districts; public and state-controlled institutions of higher education; private institutions of higher education; federally recognized Native American tribal governments; other Native American tribal organizations; public housing authorities/Indian housing authorities; nonprofits with or without 501(c)(3) status (other than higher education institutions); for-profit organizations (other than small businesses); and small businesses.
Are additional organization types explicitly listed as eligible?
Yes. The FOA also calls out Alaska Native and Native Hawaiian Serving Institutions, AANAPISIs, Hispanic-serving Institutions, Historically Black Colleges and Universities, Tribally Controlled Colleges and Universities, faith-based or community-based organizations, eligible federal agencies, regional organizations, U.S. territories or possessions, tribal governments that are not federally recognized, and non-U.S. entities (foreign organizations).
Does the FOA allow non-U.S. (foreign) organizations to apply?
Yes. Non-U.S. entities (foreign organizations) are explicitly listed among eligible applicant types.
What are the key dates listed for this FOA?
The source lists a creation date of 2021-03-10 and an original closing date of 2021-10-07.
What is the overall takeaway for potential applicants?
This opportunity supports high-impact work that either (1) produces new circuit-level knowledge through sophisticated secondary analysis of existing BRAIN-relevant data, or (2) creates well-documented, archived datasets that become durable community resources for many future discoveries.
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