BRAIN Initiative: Tools to Facilitate High-Throughput Microconnectivity Analysis (R01 Clinical Trial Not Allowed) | RFA MH 20 135

Opportunity Information: Apply for RFA MH 20 135

The National Institutes of Health (NIH) BRAIN Initiative funding opportunity titled "BRAIN Initiative: Tools to Facilitate High-Throughput Microconnectivity Analysis (R01 Clinical Trial Not Allowed)" (Funding Opportunity Number RFA-MH-20-135) supports research projects aimed at making brain microconnectivity mapping faster, cheaper, and more practical at scale. The central goal is to develop and validate new tools, methods, and shared resources that enable detailed analysis of microconnectivity, meaning the fine-grained wiring patterns among neurons and their synaptic connections. NIH is looking for technologies that the broader neuroscience community can realistically adopt, not just one-off custom setups, and that can be applied to both healthy and diseased brain tissue across model organisms and humans.

A major motivation behind this opportunity is the current cost and labor intensity of connectomics. Today, producing dense microconnectivity maps often requires expensive instrumentation, slow imaging pipelines, and heavy manual or semi-manual analysis. This announcement emphasizes that major cost reductions would change what is scientifically feasible: researchers could routinely map microconnectivity in the same individual brains that were already studied with physiology (for example, electrophysiology or functional imaging), and they could compare normal versus pathological tissue across many individuals to understand variability rather than relying on a small number of specimens. In other words, NIH is pushing for a shift from boutique, low-throughput connectomics to more routine, higher-throughput microconnectivity analysis that can support statistically meaningful comparisons across conditions, subjects, and disease states.

Technically, the opportunity highlights two imaging and measurement domains as especially important: electron microscopy (EM) and super-resolution light microscopy. EM remains a core workhorse for ultrastructural mapping because it can resolve synapses and fine neuronal processes, but scaling EM connectomics is limited by throughput, sample preparation constraints, imaging speed, and downstream computation. Super-resolution light microscopy approaches are also encouraged because they can provide nanoscale information with different tradeoffs, including potentially higher throughput, compatibility with molecular labeling, and easier integration with other biological measurements. NIH is particularly interested in proposals that break through existing technical barriers and substantially improve current capabilities rather than offering incremental improvements.

The announcement welcomes a range of deliverables as long as they clearly facilitate high-throughput microconnectivity analysis. That includes proof-of-principle demonstrations that show a new method can work in a realistic setting, as well as reference datasets that can accelerate future tool development by providing benchmark material for the community. Another explicitly encouraged area is improved automated segmentation and analysis of neuronal structures in EM images. This reflects a major bottleneck in connectomics: even if imaging becomes faster, reconstructing neurons and identifying synaptic connections from massive image volumes can be time-consuming and computationally demanding. Tools that improve automation, accuracy, scalability, and reproducibility of segmentation and downstream analysis directly support the high-throughput goal.

This is an R01 grant mechanism, meaning it is intended for substantial, investigator-led research projects with clear aims, rigorous validation plans, and deliverables that will be useful beyond the immediate lab. The opportunity is labeled "Clinical Trial Not Allowed," which signals that applicants should not propose clinical trials as part of the project. The work can involve human tissue and disease-relevant research, but it should remain focused on technology and resource development for microconnectivity analysis rather than interventional clinical studies.

Eligibility is broad and includes many types of U.S.-based organizations: state, county, and local 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 and without 501(c)(3) status (excluding higher education institutions in those categories); for-profit organizations other than small businesses; and small businesses. The listing also indicates additional eligible applicants such as Alaska Native and Native Hawaiian Serving Institutions, AANAPISI institutions, 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, U.S. territories or possessions, and foreign (non-U.S.) entities. In practice, applicants should still confirm any specific NIH policy constraints that might apply to foreign components or certain organizational arrangements, but the language provided indicates a wide net for who can apply.

Administrative details from the source information include: Agency Name: National Institutes of Health; Opportunity Category: Discretionary; Funding Instrument Type: Grant; and Funding Activity Category spanning education, health, income security, and social services (consistent with NIH listings that map to CFDA/assistance categories). The CFDA/assistance listing includes multiple numbers (93.173, 93.213, 93.242, 93.273, 93.279, 93.286, 93.853, 93.865, 93.866, 93.867), reflecting the NIH programs and institutes that may be involved. The original closing date shown is 2021-05-27, and the posting creation date is 2019-04-08, which is useful context for timing but also means the solicitation may now be closed unless reissued or replaced by a newer version.

Overall, this opportunity is best understood as a BRAIN Initiative push to make microconnectivity mapping more scalable and accessible by funding transformative advances in imaging (EM and super-resolution light microscopy), sample-to-data pipelines, and automated computational analysis. The strongest-fitting projects are likely those that can demonstrate clear improvements in throughput, cost, and usability; provide validation in relevant tissues and organisms; and produce tools, methods, or datasets that other neuroscience groups can adopt to interrogate microconnectivity in both normal brain circuitry and disease contexts.

• The National Institutes of Health in the education, health, income security and social services sector is offering a public funding opportunity titled "BRAIN Initiative: Tools to Facilitate High-Throughput Microconnectivity Analysis (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 2019-04-08.
• Applicants must submit their applications by 2021-05-27. (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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