Computational Approaches for Validating Dimensional Constructs of Relevance to Psychopathology (R01 Clinical Trial Optional) | RFA MH 19 242

Opportunity Information: Apply for RFA MH 19 242

This grant opportunity, RFA-MH-19-242, is an NIH/NIMH R01 funding announcement focused on validating the dimensional constructs used to describe psychopathology, especially those laid out in the NIMH Research Domain Criteria (RDoC) matrix or closely comparable frameworks. The basic idea behind the FOA is that while RDoC has been influential and has evolved since it was first released, the field still lacks a broad, data-driven effort that systematically tests whether the constructs in the matrix hold up when examined with modern computational tools and rigorous empirical data. NIMH is looking for research that does not just assume the structure of these domains and constructs is correct, but instead treats that structure as a set of testable hypotheses about how behavior and brain function are organized.

The projects this FOA is trying to stimulate revolve around a few core scientific questions. One major question is whether different behavioral domains truly separate cleanly from each other in real-world data, or whether they blend together more than the matrix implies. Another is how these domains map onto the brain: do they depend on distinct neural circuits, or do they rely on overlapping circuitry with differences in weighting, timing, or context? A third major theme is understanding relationships across the hierarchy of the framework, meaning how broader domains relate to constructs and more fine-grained subconstructs, both statistically (for example, their correlational structure across people and situations) and biologically (for example, whether the same circuit supports multiple constructs, or whether different circuits support what looks like a single construct at the behavioral level). The FOA is essentially pushing applicants to clarify the architecture of these dimensions rather than taking the current labels and boundaries at face value.

A defining feature of the announcement is its emphasis on computational approaches that are tightly integrated with experimental work. NIMH is not simply asking for a computational reanalysis of existing ideas, or a purely experimental study that later adds some modeling as an afterthought. The intention is for computation and experimentation to inform each other directly, such as using modeling to propose testable structure, using experiments or clinical data to challenge that structure, and iterating until the constructs are either supported, refined, reorganized, or possibly replaced. Computational approaches could include methods that discover latent dimensions, evaluate competing models of construct organization, quantify overlap among domains, or link multi-level data (behavior, physiology, neural circuitry) in a way that tests whether the same underlying mechanisms explain patterns seen across traditional diagnoses.

The broader translational motivation is to move beyond symptom-based diagnostic categories and instead identify mechanisms of dysfunction that cut across disorders and may shift over time. By validating which dimensions are real, how they relate, and how they map onto brain circuits, the work supported by this FOA is meant to lay groundwork for improved classification approaches and for identifying treatment targets that are more directly tied to underlying biology and function. In practical terms, the agency is signaling interest in research that can eventually support earlier, more precise, and more effective interventions for serious mental illness by pinpointing which mechanisms are disrupted, for whom, and under what conditions, rather than relying on broad diagnostic labels that may group together multiple distinct underlying problems.

From an administrative standpoint, this is an R01 (clinical trial optional) grant mechanism under the U.S. Department of Health and Human Services, National Institutes of Health, with NIMH as the sponsoring institute. The FOA listed an award ceiling of $1,000,000 and anticipated about five awards. Eligibility is broad and includes many types of U.S. organizations, such as federal recognized tribal governments and tribal organizations, state and local governments, public and private universities, nonprofits (including 501(c)(3) and non-501(c)(3)), for-profit organizations (including small businesses), independent school districts, and other entities as specified in the full announcement. The opportunity was originally posted in late September 2018, with an original closing date of November 20, 2020, indicating it was a time-limited call intended to accelerate progress on this specific validation problem rather than a permanently open program announcement.

• The Department of Health and Human Services, National Institutes of Health in the health sector is offering a public funding opportunity titled "Computational Approaches for Validating Dimensional Constructs of Relevance to Psychopathology (R01 Clinical Trial Optional)" and is now available to receive applicants.
• Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 93.242.
• This funding opportunity was created on Sep 26, 2018.
• Applicants must submit their applications by Nov 20, 2020. (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 $1,000,000.00 in funding.
• The number of recipients for this funding is limited to 5 candidate(s).
• 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 (see text field entitled Additional Information on Eligibility for clarification).

Apply for RFA MH 19 242

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