Understanding Circuits Program

 The NIH BRAIN Initiative's Understanding Circuits program advances our knowledge of how the nervous system encodes, processes, and transmits information — integrating experimental rigor with computational innovation to achieve a mechanistic understanding of CNS function.

To drive this mission forward, the program supports a family of funding opportunities united by a commitment to Integrated and Quantitative Approaches. Supported projects span the full spectrum: from generating mechanistic insights through tightly coupled experimental-computational frameworks, to developing new theories, models, and methods across a diverse range of experimental systems and species.

Understanding Circuits is also a cornerstone of the BRAIN Initiative's NeuroAI Innovation Domain — championing the bidirectional exchange between experimental and computational neuroscience, and fostering the development of biologically grounded, interpretable models of neural function.

Funding Opportunities

 All funding opportunities in this family share a common foundation: the application of cutting-edge tools for neural activation and recording to resolve circuit function at cellular spatial resolution and sub-second temporal resolution. Basic research using human or non-human animal subjects is welcomed across all opportunities.

Proposals are expected to advance theory and/or analytics, and must include both a data standards and management plan and a data dissemination plan to maximize the utility and accessibility of research outputs for the broader community.

• Integrated BRAIN Circuits Program — Supports research that generates mechanistic insights by bridging across levels of investigation: from cells to circuits to behavior.
• Theories, Models, and Methods — Supports the development and community-wide dissemination of computational tools — theories, models, or methods — for understanding dynamic circuit function.
• Research Opportunities in Humans Program — Offers two distinct funding opportunities: one for exploratory approaches, and one for large-scale research projects, both focused on deepening our understanding of human neurobiology.

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)

Contact

For questions and/or to share a draft of your aims:
[email protected]

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