Notices of Funding Opportunities

This Funding Opportunity Announcement (FOA) encourages research grant applications directed toward developing next-generation human cell-derived assays that replicate complex nervous system architectures and physiology with improved fidelity over current capabilities. This includes technologies that do not rely on the use of human fetal tissue, as described in NOT-19-042. Supported projects will be expected to enable future studies of complex nervous system development, function and aging in healthy and disease states.

The BRAIN Initiative® and the neuroscience field as a whole is generating massive and diverse research data across different modalities, spatiotemporal scales and species in efforts to advance our understanding of the brain. The data types are being produced through development and application of innovative technologies in high-throughput -omics profiling, optical microscopy, electron microscopy, electrophysiological recording, macroscale neuroimaging, neuromodulation, and others. The BRAIN Initiative® has made significant investments in the development of an infrastructure to make data available to the research community in a useful way. This infrastructure includes data archives, data standards, and software for data integration, analysis and machine learning. This Funding Opportunity Announcement (FOA) encourages secondary analysis of the large amounts of existing data related to The BRAIN Initiative®. The data do not need to be held in one of the funded BRAIN Initiative data archives, but the data must be held in a data archive that is readily accessible to the research community. Support will be provided for innovative analysis of relevant existing datasets using conventional or novel analytic methods, data science techniques, and machine learning approaches. Support may also be requested to prepare and submit existing data into any of The BRAIN Initiative® data archives. Investigators should not underestimate the time and effort that may be necessary to curate or harmonize data. Analyzed data, models and analytical tools generated under this FOA are expected to be deposited into an appropriate data archive. Since The BRAIN Initiative® data archives are mostly making the data available to the research community through cloud-based storage, depositing the analyzed data, models and tools are expected to enhance opportunities to create a data sandbox where investigators can easily compare the results of their analysis with those from other research groups.

The purpose of this Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative is to encourage applications that will develop and validate tools and resources to facilitate the detailed analysis of brain microconnectivity. Novel and augmented techniques are sought that will ultimately be broadly accessible to the neuroscience community for the interrogation of microconnectivity in healthy and diseased brains of model organisms and humans. Development of technologies that will significantly drive down the cost of connectomics would enable routine mapping of the microconnectivity on the same individuals that have been analyzed physiologically, or to compare normal and pathological tissues in substantial numbers of multiple individuals to assess variability. Advancements in both electron microscopy (EM) and super resolution light microscopic approaches are sought. Applications that propose to develop approaches that break through existing technical barriers to substantially improve current capabilities are highly encouraged. Proof-of-principle demonstrations and/or reference datasets enabling future development are welcome, as are improved approaches for automated segmentation and analysis strategies of neuronal structures in EM images.no

This funding opportunity announcement (FOA) supports efforts to disseminate resources and to integrate them into neuroscience research practice. Projects should be highly relevant to specific goals of the BRAIN Initiative, goals that are described in the planning document "BRAIN 2025: A Scientific Vision." They should engage in one or more of the following activities: distribution of tools and reagents; user training on the usage of new technologies or techniques; providing access to existing technology platforms and specialized facilities; minor improvements to increase the scale/efficiency of resource production and delivery; minor adaptations to meet the needs of a user community. Applications strictly focused on technology or software development, rather than dissemination of an existing resource, are not responsive to this FOA. Refinements to microscopes or tools necessary to customize them to the experimental needs of the end users is allowed. Projects should address compelling needs of neuroscience researchers working toward the goals of the BRAIN 2025 report that are otherwise unavailable or impractical in their current form.

This Funding Opportunity Announcement (FOA) intends to support a group of Specialized Collaboratories that will adopt scalable technology platforms and streamlined workflows to accelerate progress towards establishing comprehensive molecular and anatomical reference cell atlases of human brain and/or non-human primate brains. A central goal of this FOA is to build a brain cell census resource that can be widely used throughout the research community.

This funding opportunity announcement (FOA), in support of the NIH Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative, is one of several FOAs aimed at supporting transformative discoveries that will lead to breakthroughs in understanding human brain function. Guided by the long-term scientific plan, BRAIN 2025: A Scientific Vision, this FOA specifically seeks to support efforts addressing core ethical issues associated with research focused on the human brain and resulting from emerging technologies and advancements supported by The BRAIN Initiative®. The hope is that efforts supported under this FOA might be both complementary and integrative with the transformative, breakthrough neuroscience discoveries supported through The BRAIN Initiative®.

This Funding Opportunity Announcement (FOA) intends to accelerate the integration and use of scalable technologies and tools to enhance brain cell census research, including the development of technology platforms and/or resources that will enable a swift and comprehensive survey of brain cell types and circuits. Applications are expected to address limitations and gaps of existing technologies/tools as a benchmark against which the improvements or competitive advantages of the proposed ones will be measured. The improvements include throughput, sensitivity, selectivity, scalability, spatiotemporal resolution and reproducibility in cell census analyses. The projects funded under this FOA will align with the overarching goals of The BRAIN Initiative® Cell Census Network (BICCN) and are expected to enable the generation of a substantial amount of cell census data using the proposed technologies or via collaboration with the BICCN.

This FOA will support integrated, interdisciplinary research teams from prior BRAIN technology and/or integrated approaches teams, and/or new projects from the research community that focus on examining circuit functions related to behavior, using advanced and innovative technologies. The goal will be to support programs with a team science approach that can realize meaningful outcomes within 5-plus years. Awards will be made for 5 years, with a possibility of one competing renewal. Applications should will incorporate overarching principles of circuit function in the context of specific neural systems underlying sensation, perception, emotion, motivation, cognition, decision-making, motor control, communication, or homeostasis. Applications should incorporate theory-/model-driven experimental design and should offer predictive models as deliverables. Applications should seek to understand circuits of the central nervous system by systematically controlling stimuli and/or behavior while actively recording and/or manipulating relevant dynamic patterns of neural activity and by measuring the resulting behaviors and/or perceptions. Applications are expected to employ approaches guided by specified theoretical constructs, and are encouraged to employ quantitative, mechanistic models where appropriate. Applications will be required to manage their data and analysis methods in a prototype framework that will be developed and used in the proposed U19 project and exchanged with other BRAIN U19 awardees for further refinement and development. Model systems, including the possibility of multiple species ranging from invertebrates to humans, can be employed and should be appropriately justified. Programs should employ multi-component teams of research expertise including neurobiologists, statisticians, physicists, mathematicians, engineers, computer scientists, and data scientists, as appropriate - that seek to cross boundaries of interdisciplinar

This FOA will support integrated, interdisciplinary research teams from prior BRAIN technology and/or integrated approaches teams, and/or new projects from the research community that focus on examining circuit functions related to behavior, using advanced and innovative technologies. The goal will be to support programs with a team science approach that can realize meaningful outcomes within 5-plus years. Awards will be made for 5 years, with a possibility of one competing renewal. Applications should address overarching principles of circuit function in the context of specific neural systems underlying sensation, perception, emotion, motivation, cognition, decision-making, motor control, communication, or homeostasis. Applications should incorporate theory-/model-driven experimental design and should offer predictive models as deliverables. Applications should seek to understand circuits of the central nervous system by systematically controlling stimuli and/or behavior while actively recording and/or manipulating relevant dynamic patterns of neural activity and by measuring the resulting behaviors and/or perceptions. Applications are expected to employ approaches guided by specified theoretical constructs, and are encouraged to employ quantitative, mechanistic models where appropriate. Applications will be required to manage their data and analysis methods in a prototype framework that will be developed and used in the proposed U19 project and exchanged with other U19 awardees for further refinement and development. Model systems, including the possibility of multiple species ranging from invertebrates to humans, can be employed and should be appropriately justified. Budgets should be commensurate with multi-component teams of research expertise including neurobiologists, statisticians, physicists, mathematicians, engineers, computer scientists, and data scientists, as appropriate - that seek to cross boundaries of interdisciplinary collaboration.

Invasive surgical procedures provide the unique ability to record and stimulate neurons within precisely localized brain structures in humans. Human studies using invasive technology are often constrained by a limited number of patients and resources available to implement complex experimental protocols and are rarely aggregated in a manner that addresses research questions with appropriate statistical power. Therefore, this RFA seeks applications to assemble diverse, integrated, multi-disciplinary teams that cross boundaries of interdisciplinary collaboration to overcome these fundamental barriers and to investigate high-impact questions in human neuroscience. Projects should maximize opportunities to conduct innovative in vivo neuroscience research made available by direct access to brain recording and stimulating from invasive surgical procedures. Projects should employ approaches guided by specified theoretical constructs and quantitative, mechanistic models where appropriate. Awardees will join a consortium work group, coordinated by the NIH, to identify consensus standards of practice, including neuroethical considerations, to collect and provide data for ancillary studies, and to aggregate and standardize data for dissemination among the wider scientific community.