BRAIN Initiative: New Technologies and Novel Approaches for Recording and Modulation in the Nervous System (R01 Clinical Trial Not Allowed)
January 20, 2026
State governments, County governments, City or township governments, Special district governments, Independent school districts, Public & State controlled institutions of higher education, Native American tribal governments (Federally recognized), Public housing authorities, Native American tribal organizations, Nonprofits (with 501(c)(3) status), Nonprofits (without 501(c)(3) status)
Reissue of RFA-NS-18-020: Understanding the dynamic activity of brain circuits is central to the NIH BRAIN Initiative. This FOA seeks applications for proof-of-concept testing and development of new technologies and novel approaches for recording and modulation (including various modalities for stimulation/activation, inhibition and manipulation) of cells (i.e., neuronal and non-neuronal) and networks to enable transformative understanding of dynamic signaling in the central nervous system (CNS). This FOA seeks exceptionally creative approaches to address major challenges associated with recording and modulating CNS activity, at or near cellular resolution, at multiple spatial and/or temporal scales, in any region and throughout the entire depth of the brain. It is expected that the proposed research may be high-risk, but if successful, could profoundly change the course of neuroscience research. Proposed technologies should be compatible with experiments in behaving animals, validated under in vivo experimental conditions, and capable of reducing major barriers to conducting neurobiological experiments and making new discoveries about the CNS. Technologies may engage diverse types of signaling beyond neuronal electrical activity such as optical, magnetic, acoustic and/or genetic recording/manipulation. Applications that seek to integrate multiple approaches are encouraged. If suitable, applications are expected to integrate appropriate domains of expertise, including biological, chemical and physical sciences, engineering, computational modeling and statistical analysis.