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The NINDS, with other NIH Institutes and Centers participating in the BRAIN Initiative, intends to publish "BRAIN Initiative Advanced Postdoctoral Career Transition Award to Promote Diversity (K99/R00)." The program is designed to increase biomedical research workforce diversity and foster a strong cohort of new, highly skilled and well trained, NIH-supported, independent investigators from underrepresented groups working in research areas supported by the BRAIN Initiative, as highlighted in BRAIN 2025: A Scientific Vision. It is designed to facilitate a timely transition of outstanding postdoctoral researchers with a research and/or clinical doctorate degree from mentored, postdoctoral research positions to independent, tenure-track or equivalent faculty positions. This Notice is being provided to allow potential applicants sufficient time to develop meaningful mentoring teams and responsive projects. The FOA is expected to be published in April 2018 with an expected application due date in June 2018. This FOA will utilize the K99/R00 funding activity. Details of the planned FOA are provided below. Research Initiative Details The BRAIN Initiative K99/R00 award is intended for women and members of underrepresented groups who are working in research areas supported by the BRAIN Initiative, who have no more than five years of postdoctoral research experience, and who require at least 12 months of mentored research training and career development (K99 phase) before transitioning to the independent research (R00) phase of the program.

This FOA solicits new theories, computational models, and statistical tools to derive understanding of brain function from complex neuroscience data. Proposed tools could include the creation of new theories, ideas, and conceptual frameworks to organize/unify data and infer general principles of brain function; new computational models to develop testable hypotheses and design/drive experiments; and new mathematical and statistical methods to support or refute a stated hypothesis about brain function, and/or assist in detecting dynamical features and patterns in complex brain data. It is expected that the tools developed under this FOA will be made widely available to the neuroscience research community for their use and modification. Investigative studies should be limited to validity testing of the tools being developed.

This FOA solicits new theories, computational models, and statistical tools to derive understanding of brain function from complex neuroscience data. Proposed tools could include the creation of new theories, ideas, and conceptual frameworks to organize/unify data and infer general principles of brain function; new computational models to develop testable hypotheses and design/drive experiments; and new mathematical and statistical methods to support or refute a stated hypothesis about brain function, and/or assist in detecting dynamical features and patterns in complex brain data. It is expected that the tools developed under this FOA will be made widely available to the neuroscience research community for their use and modification. Investigative studies should be limited to validity testing of the tools being developed.

These awards encourage and support scientists working on the development of novel and creative approaches to understanding brain function. The fund supports efforts to examine how a new technology may be used to monitor, manipulate, analyze, or model brain function at any level, from the molecular to the entire organism. Technology may take any form, from biochemical tools to instruments to software and mathematical approaches. Because the program seeks to advance and enlarge the range of technologies available to the neurosciences, research based primarily on existing techniques will not be considered.

These awards encourage and support scientists working on the development of novel and creative approaches to understanding brain function. The fund supports efforts to examine how a new technology may be used to monitor, manipulate, analyze, or model brain function at any level, from the molecular to the entire organism. Technology may take any form, from biochemical tools to instruments to software and mathematical approaches. Because the program seeks to advance and enlarge the range of technologies available to the neurosciences, research based primarily on existing techniques will not be considered.

Although invention and proof-of-concept testing of new technologies are a key component of the BRAIN Initiative, to achieve their potential these technologies must also be optimized through feedback from end-users in the context of the intended experimental use. This seeks applications for the optimization of existing and emerging technologies and approaches that have potential to address major challenges associated with recording and manipulating neural activity, at or near cellular resolution, at multiple spatial and temporal scales, in any region and throughout the entire depth of the brain. This FOA is intended for the iterative refinement of emergent technologies and approaches that have already demonstrated their transformative potential through initial proof-of-concept testing, and are appropriate for accelerated development of hardware and software while scaling manufacturing techniques towards sustainable, broad dissemination and user-friendly incorporation into regular neuroscience practice. Proposed technologies should be compatible with experiments in behaving animals, and should include advancements that enable or reduce major barriers to hypothesis-driven experiments. Technologies may engage diverse types of signaling beyond neuronal electrical activity for large-scale analysis, and may utilize any modality such as optical, electrical, magnetic, acoustic or genetic recording/manipulation. Applications that seek to integrate multiple approaches are encouraged. Applications are expected to integrate appropriate domains of expertise, including where appropriate biological, chemical and physical sciences, engineering, computational modeling and statistical analysis.

Understanding the dynamic activity of neural 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 largescale recording and manipulation of neural activity to enable transformative understanding of dynamic signaling in the nervous system. In particular, we seek exceptionally creative approaches to address major challenges associated with recording and manipulating neural 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, and should include advancements that enable or reduce major barriers to hypothesis-driven experiments. Technologies may engage diverse types of signaling beyond neuronal electrical activity for large-scale analysis, and may utilize any modality such as optical, electrical, magnetic, acoustic or genetic recording/manipulation. Applications that seek to integrate multiple approaches are encouraged. Where appropriate, applications are expected to integrate appropriate domains of expertise, including biological, chemical and physical sciences, engineering, computational modeling and statistical analysis.

The purpose of this Funding Opportunity Announcement (FOA) is to support the development of advanced computational, bioinformatic and statistical tools to determine the functional relevance of genetic variants associated with mental disorders of complex etiologies identified through genome-wide association or sequencing studies. The overarching goal of this initiative is to support the development of innovative computational methods that facilitate the elucidation of the functionality of genetic variants associated with mental illness, taking into account the added complexities and nuances of brain diseases, and to ultimately inform novel treatment development based on human biology.