BRAIN Initiative: Brain-Behavior Quantification and Synchronization Transformative and Integrative Models of Behavior at the Organismal Level (U01 Clinical Trials Not Allowed)
This funding opportunity supports researchers developing advanced tools and methods to measure and analyze complex behaviors in organisms, while integrating environmental data and neural information to enhance our understanding of behavior as a dynamic system.
Description
The BRAIN Initiative: Brain-Behavior Quantification and Synchronization – Transformative and Integrative Models of Behavior at the Organismal Level (U01 Clinical Trials Not Allowed) is a cooperative agreement funding opportunity from the National Institutes of Health (NIH), specifically supported by several participating institutes including the National Institute on Drug Abuse (NIDA), National Eye Institute (NEI), and National Institute on Aging (NIA), among others. This opportunity aims to fund projects that use non-human animal models to develop advanced tools and methods for high-resolution, minimally invasive measurement of behavior in synchrony with environmental and neural data. This initiative supports the overarching goals of the NIH BRAIN Initiative to deepen understanding of brain function and its relationship to behavior in complex, dynamic contexts.
The purpose of this funding opportunity is to advance the development of transformative behavioral models at the organismal level by supporting transdisciplinary teams. Projects should integrate novel sensor technologies, multidimensional behavioral and environmental data, and predictive computational models, including those using AI and machine learning. Proposals must explicitly address three core objectives: interdisciplinary collaboration, development of minimally intrusive sensing technologies for synchronized measurement, and creation of predictive computational models that can integrate neural data. The emphasis is on modeling behavior as a complex dynamic system, not on disease-specific studies.
Funding may be used to support research involving development and validation of new sensing tools, analytic frameworks for multidimensional data, and models of the behavior-environment interface. The research must be conducted in non-human animal models and exclude studies with human participants or data as a significant component. Projects must aim to measure behaviors across various modalities such as ambulation, vocalizations, physiology, and interactions with dynamic environments, with methods that allow naturalistic expression of the animal’s behavioral repertoire.
Eligible applicants include higher education institutions, nonprofits, small businesses, for-profit organizations, government entities (local, state, and tribal), and foreign institutions. Applications must be scientifically distinct if multiple submissions are made by the same organization. Required submissions include a Resource Sharing Plan and Data Management and Sharing Plan in alignment with NIH and BRAIN Initiative guidelines. Milestones for each objective must be clearly stated and projects must be feasible, innovative, and designed with robust quality assurance protocols.
Applications are accepted annually on October 9 in 2024, 2025, and 2026, with the earliest start dates projected for July of the following year. A letter of intent is encouraged 30 days prior to the due date. Applications must be submitted electronically through NIH’s ASSIST, Grants.gov, or an institutional system-to-system platform. All relevant registrations, including SAM, eRA Commons, and Grants.gov, must be completed in advance. Applications will undergo NIH peer review, with selection based on scientific merit, innovation, alignment with program goals, and budget appropriateness.
This funding opportunity does not require cost-sharing and is part of a broader strategy to build a highly integrated understanding of behavior and brain function across diverse research fields. Investigators are expected to actively participate in BRAIN Initiative meetings and collaborative activities, sharing data and resources per program expectations.