BRAIN Initiative: Tools to Facilitate High-Throughput Microconnectivity Analysis (R01) | RFA MH 18 505

Opportunity Information: Apply for RFA MH 18 505

The BRAIN Initiative: Tools to Facilitate High-Throughput Microconnectivity Analysis (R01) (RFA-MH-18-505) is a National Institutes of Health (NIH) discretionary grant opportunity designed to accelerate the development and validation of new tools, methods, and community resources for detailed analysis of brain microconnectivity, often referred to as connectomics at the microscale. The central goal is to enable researchers to map and interpret fine-grained neural wiring patterns more routinely and at higher throughput than is currently practical, in both healthy and diseased brain tissue, across model organisms and humans. A major emphasis is on creating techniques that are not only innovative but also broadly usable by the wider neuroscience community rather than being limited to a few specialized labs.

A key motivation behind the program is that current microconnectivity mapping approaches are often expensive, slow, and technically demanding, which limits the number of samples and individuals that can be studied. The announcement highlights that substantially lowering the cost of connectomics could change what is scientifically feasible: it would make it more realistic to map microconnectivity in the same individuals already examined with physiological methods (so that wiring diagrams can be directly linked to function), and it would support larger-scale comparisons of normal versus pathological tissue across many individuals, which is essential for understanding biological variability and disease-related changes. In other words, the opportunity is aimed at moving microconnectivity analysis from boutique, small-N studies toward approaches that can support broader and more statistically informative investigations.

On the technical side, the opportunity explicitly calls for advancements in both electron microscopy (EM) and super-resolution light microscopy. EM remains a cornerstone for ultrastructural connectomics because it can resolve synapses and fine neuronal processes, while super-resolution light microscopy can offer complementary advantages such as molecular labeling, potential scalability, and different tradeoffs in speed and volume. The solicitation is particularly interested in projects that can break through existing technical barriers and substantially improve current capabilities, rather than offering incremental refinements. That could include innovations that increase imaging throughput, improve labeling or sample preparation, enhance reconstruction fidelity, improve cross-modality integration, or enable more reliable and scalable inference of connectivity.

In addition to imaging and experimental workflows, the announcement welcomes work on computational methods and data resources that make high-throughput microconnectivity practical. It specifically notes interest in improved strategies for automated segmentation and analysis of neuronal structures in EM images, which is a major bottleneck in connectomics because converting raw image volumes into usable reconstructions often requires large amounts of computation and/or human proofreading. Proposals may include proof-of-principle demonstrations that show feasibility, as well as the creation of reference datasets intended to enable further technology development by others. This signals that the program values community-enabling outputs such as benchmarks, open resources, or validated pipelines that reduce friction for future users and developers.

The funding mechanism is an R01 research project grant, supporting substantial, multi-year research and development efforts. The opportunity falls under NIH activity areas spanning education, health, income security, and social services, and is 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 NIH institute and program alignments that can intersect with neuroscience technology development. The original posting indicates a creation date of 2017-08-30 and an original closing date of 2018-11-13.

Eligibility is broad and includes a wide range of applicant organizations. Eligible applicants listed include state, county, city or township, and 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; Native American tribal organizations other than federally recognized governments; public housing authorities/Indian housing authorities; nonprofits with and without 501(c)(3) status (excluding institutions of higher education in those categories); for-profit organizations other than small businesses; small businesses; and other entities. The opportunity also explicitly notes additional eligible applicants such as Alaska Native and Native Hawaiian Serving Institutions, Asian American Native American Pacific Islander Serving Institutions (AANAPISISs), 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 non-domestic (non-U.S.) entities (foreign organizations). Overall, the eligibility language signals an intent to attract diverse institutional participation, including organizations that can contribute specialized technical expertise, community-focused infrastructure, or unique research environments.

Taken together, this R01 opportunity is centered on making microconnectivity mapping faster, cheaper, more scalable, and more accessible, with strong encouragement for ambitious technology development in EM and super-resolution microscopy, along with the computational and dataset infrastructure needed to turn high-volume imaging into reliable, interpretable connectivity information that can be used broadly across neuroscience and translational research 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)" 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 2017-08-30.
• Applicants must submit their applications by 2018-11-13. (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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