Understanding Circuits Program

The NIH BRAIN Initiative Understanding Circuits program encompasses a family of "Integrated and Quantitative Approaches to Understanding Circuits" Notice of Funding Opportunities (NOFOs). These funding opportunities range from small or exploratory, targeted brain circuits projects with specific research deliverables (R34, R01) to large, team-research projects with exploratory aims (U01) or with extensive and elaborated goals and a 5 to 10-year horizon of discovery (U19). 

What are exploratory programs? 
Early-stage projects that set the foundation for larger research efforts.

What are full-size programs?
These programs accept applications from either projects enabled by the exploratory programs or from new applications with well-developed approaches.

The Theories, Models and Methods funding opportunity provides support for building computational tools (Theories, Models or Methods) for understanding dynamic circuits that are disseminated for use in the greater research community. 

Funding Opportunities

All funding opportunities in this family of initiatives emphasize the use of cutting-edge methods of activation and recording to understand the behavior of circuits at cellular and sub-second levels of spatial and temporal resolution. In addition, all funding opportunities welcome basic research using human or non-human animal subjects.

This family of initiatives also seeks advances in theory and/or analytics and has a requirement of a data standards and management plan, as well as a data dissemination plan to facilitate use of the results by the research community.

Data Consortium

Data science experts from the NIH BRAIN Initiative Understanding Circuits program will participate in a data science consortium with the goals of:

  1. Identifying common data science tools and resources.
  2. Collaborating on best practices for multi-modal data integration.
  3. Sharing exploratory efforts to pilot optimal workflows for model-driven investigative research.

Collaborative Research in Computational Neuroscience

One of the scientific priority areas identified in the BRAIN 2025 Report, is to produce conceptual foundations for understanding the biological basis of mental processes through the development of new theoretical and data analysis tools. The Collaborative Research in Computational Neuroscience (CRCNS), a joint program of NSF and NIH since 2002, has supported integration of theoretical and experimental neuroscience through collaborative research projects between theorists and experimentalists. Given the overlapping goals between CRCNS and BRAIN, the NIH has brought some CRCNS awards into BRAIN to further the mission of both endeavors.

Related NIH Notice
Collaborative Research in Computational Neuroscience (CRCNS) NSF Innovative Approaches to Science and Engineering Research on Brain Function (NOT-MH-20-110)


For questions and/or to share a draft of your aims:

For questions about “Theories, Models and Methods for Analysis of Complex Data from the Brain”