Group items tagged

The primary objective of this FOA is to stimulate innovative Convergent Neuroscience (CN) approaches to establish causal and/or probabilistic linkages across contiguous levels of analysis (e.g., gene, molecule, cell, circuit, system, behavior) in an explanatory model of psychopathology. In particular, applicants should focus on how specific constituent biological processes at one level of analysis contribute to quantifiable properties at other levels, either directly or as emergent phenomena.  Although not required, it is preferable that applications link at least three levels of analysis and include an emphasis on genetics. The projects under this FOA will develop novel methods, theories, and approaches through a CN team framework, bringing together highly synergistic inter/transdisciplinary teams from neuroscience and "orthogonal" fields (e.g., data/computational science, physics, engineering, mathematics, and environmental sciences). Successful teams will combine, expand upon, or develop conceptual frameworks and theoretical approaches, and build explanatory computational models that connect contiguous levels of analysis. Such frameworks, theories, and computational explanatory models should be validated through experimental approaches to elucidate biological underpinnings of complex behavioral (including cognitive and affective) outcomes in psychopathology. Additionally, a goal of this program is to advance research in CN by creating a shared community framework of resources which may be used by the broader research community to further research, as such, successful team will have robust plan for sharing data and other resources.

The intent of the FY19 FITBIR Analysis Award is to leverage this data to identify actionable insights for the diagnosis, management, and treatment of TBI. The proposed research must be relevant to active duty Service members, Veterans, military beneficiaries, and/or the American public. The anticipated total costs budgeted for the entire period of performance for an FY19 JPC-6/CCCRP PH/TBI FITBIR Analysis Award will not exceed $750,000. Refer to Section II.D.5, Funding Restrictions, for detailed funding information. The JPC-6/CCCRP expects to allot approximately $3M of the FY19 PH/TBIRP appropriation to fund approximately 4 FITBIR Analysis Award applications. Funding of applications received is contingent upon the availability of Federal funds for this program as well as the number of applications received, the quality and merit of the applications as evaluated by scientific and programmatic review, and the requirements of the Government. Funds to be obligated on any award resulting from this funding opportunity will be available for use for a limited time period based on the fiscal year of the funds. It is anticipated that awards made from this FY19 FITBIR Analysis Award funding opportunity will be funded with FY19 funds, which will expire for use on September 30, 2025

The BRAIN Initiative and the neuroscience field as a whole are 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.

The purpose of this FOA is to provide resources for integrated development of experimental, analytic and theoretical capabilities for large-scale analysis of neural systems and circuits. We seek applications for exploratory studies that use new and emerging methods for large scale recording and manipulation of neural circuits across multiple brain regions. Applications should propose to elucidate the contributions of dynamic circuit activity to a specific behavioral or neural system. Studies should incorporate rich information on cell-types, on circuit functionality and connectivity, and should be performed in conjunction with sophisticated analysis of ethologically relevant behaviors. Applications should propose teams of investigators that seek to cross boundaries of interdisciplinary collaboration by bridging fields and linking theory and data analysis to experimental design. Exploratory studies supported by this FOA are intended to develop experimental capabilities and theoretical frameworks in preparation for a future competition for large scale awards.

The purpose of this FOA is to promote the integration of experimental, analytic, and theoretical capabilities for large-scale analysis of neural systems and circuits. This FOA seeks applications for exploratory research studies that use new and emerging methods for large scale recording and manipulation of neural circuits across multiple brain regions. Applications should propose to elucidate the contributions of dynamic circuit activity to a specific behavioral or neural system. 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. Studies should incorporate rich information on cell-types, on circuit functionality and connectivity, and should be performed in conjunction with sophisticated analysis of complex, ethologically relevant behaviors. Applications should propose teams of investigators that seek to cross boundaries of interdisciplinary collaboration by bridging fields and linking theory and data analysis to experimental design. Exploratory studies supported by this FOA are intended to develop experimental capabilities and quantitative, theoretical frameworks in preparation for a future competition for larger-scale, multi-component, Team-Research BRAIN Circuit Programs (U19).

The purpose of this FOA is to promote the integration of experimental, analytic, and theoretical capabilities for large-scale analysis of neural systems and circuits. This FOA seeks applications for exploratory research studies that use new and emerging methods for large scale recording and manipulation of neural circuits across multiple brain regions. Applications should propose to elucidate the contributions of dynamic circuit activity to a specific behavioral or neural system. 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. Studies should incorporate rich information on cell-types, on circuit functionality and connectivity, and should be performed in conjunction with sophisticated analysis of complex, ethologically relevant behaviors. Applications should propose teams of investigators that seek to cross boundaries of interdisciplinary collaboration by bridging fields and linking theory and data analysis to experimental design. Exploratory studies supported by this FOA are intended to develop experimental capabilities and quantitative, theoretical frameworks in preparation for a future competition for larger-scale, multi-component, Team-Research Circuit Programs (U19) awards.

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.

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.

This FOA invites applications from multidisciplinary teams to perform secondary data analysis, using existing datasets from two or more multi-site clinical research projects, to address scientific and clinical hypotheses relevant to neurological disorders and conditions within the NINDS mission. In this phased funding mechanism, applications are required to systematically and comprehensively perform cross-project data harmonization and curation, assessed using Go/No-go data-quality metrics, prior to funding of the second phase of data analyses. Consistent with the FAIR (findable, accessible, interoperable and reusable) data principles, this funding opportunity expects open-source cataloging of the processes and tools used for harmonization, curation, and analysis, as well as controlled access to the curated datasets.

The purpose of this Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative Funding Opportunity Announcement (FOA) is to encourage the transfer of new technologies and new data analysis techniques into a research laboratory.  One of the key goals of the BRAIN Initiative is to develop new technologies to improve our understanding of the brain.  In order for those technologies to be useful, they need to be broadly disseminated beyond the laboratory or company where they originated.  This FOA promotes this goal by providing funds to enable the incorporation of new technologies or data analysis techniques into research programs that further the aims of the BRAIN initiative.

Understanding the dynamic activity of neural circuits is central to the NIH BRAIN Initiative. 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 FOA 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. Also listed under R01

This Funding Opportunity Announcement (FOA) invites applications to continue the operations of the NIA Genome Center for Alzheimer's Disease (GCAD) to facilitate and support the Alzheimer's Disease Sequencing Project (ADSP) activities. GCAD will serve as the focal point for all phases of ADSP quality control checking, data harmonization, and meta-analysis. The FOA is intended to support a major component of the full range of analysis for the ADSP. The spectrum of the Center's activities comprises a multidisciplinary attack on Alzheimer's disease (AD) and AD-related dementias (ADRD), in keeping with NIA's programmatic needs. The Center will serve as a national resource for the specific purpose of identifying potential avenues for therapeutic approaches and prevention of the disease.

This Funding Opportunity Announcement (FOA) invites applications to continue the operations of the NIA Genome Center for Alzheimer's Disease (GCAD) to facilitate and support the Alzheimer's Disease Sequencing Project (ADSP) activities. GCAD will serve as the focal point for all phases of ADSP quality control checking, data harmonization, and meta-analysis. The FOA is intended to support a major component of the full range of analysis for the ADSP. The spectrum of the Center's activities comprises a multidisciplinary attack on Alzheimer's Disease (AD) and AD Related Dementias (ADRD) in keeping with NIA's programmatic needs. The Center will serve as a national resource for the specific purpose of identifying potential avenues for therapeutic approaches and prevention of the disease.

The purpose of this Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative is to encourage applications that will develop and validate novel tools to facilitate the detailed analysis of complex circuits and provide insights into cellular interactions that underlie brain function. The new tools and technologies should inform and/or exploit cell-type and/or circuit-level specificity. Plans for validating the utility of the tool/technology will be an essential feature of a successful application. The development of new genetic and non-genetic tools for delivering genes, proteins and chemicals to cells of interest or approaches that are expected to target specific cell types and/or circuits in the nervous system with greater precision and sensitivity than currently established methods are encouraged. Tools that can be used in a number of species/model organisms rather than those restricted to a single species are highly desired. Applications that provide approaches that break through existing technical barriers to substantially improve current capabilities are highly encouraged.

The purpose of this Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative is to encourage applications that will develop and validate novel tools to facilitate the detailed analysis of complex circuits and provide insights into cellular interactions that underlie brain function. The new tools and technologies should inform and/or exploit cell-type and/or circuit-level specificity. Plans for validating the utility of the tool/technology will be an essential feature of a successful application. The development of new genetic and non-genetic tools for delivering genes, proteins and chemicals to cells of interest or approaches that are expected to target specific cell types and/or circuits in the nervous system with greater precision and sensitivity than currently established methods are encouraged. Tools that can be used in a number of species/model organisms rather than those restricted to a single species are highly desired. Applications that provide approaches that break through existing technical barriers to substantially improve current capabilities are highly encouraged.

Professional services are required to develop and evaluate techniques for analyzing anatomical and functional brain data using deformable shape and appearance volume models (Metamorphs/Active Volume Models), stretching open active contours (SOAX), and advanced classification methods, including deep learning.  These methods will be investigated and state-of-the-art tools developed for the segmentation of brain MRI and diffusion imaging data and the analysis of fMRI data, with the aim of supporting research into understanding functional brain circuits and their anatomical correlations. Functional-anatomical atlases will be developed to facilitate comparisons across individuals and for statistical modeling.  The required work is projected to be a multi-year effort, with the first year concentrating on feasibility and prototype development.  Subsequent two-year work, if justified by first-year results, will concentrate on the  development and further evaluation of the prototypes as mature tools that contribute to the wider national research initiative to accurately model functioning of the human brain.

This Funding Opportunity Announcement (FOA) invites applications that propose Artificial Intelligence (AI), Machine Learning (ML), and/or Deep Learning (DL) approaches, collectively referred to here as "cognitive systems," that lead to the identification of gene mutations/variants that cause or contribute to the risk of or protection against the development of Alzheimer's disease (AD) and Alzheimer's disease related dementias (ADRD) via analysis of a variety of genetic, genomic, and biomarker data that are currently available to the research community.

DLS supports fundamental research that increases our understanding of cognitive, linguistic, social, cultural, and biological processes related to children's and adolescents' development and learning.  Research supported by this program will add to our basic knowledge of how people learn and the underlying developmental processes that support learning, with the objective of leading to better educated children and adolescents who grow up to take productive roles as workers and as citizens. Among the many research topics supported by DLS are: developmental cognitive neuroscience; development of higher-order cognitive processes; transfer of knowledge from one domain or situation to another; use of molecular genetics to study continuities and discontinuities in development; development of peer relations and family interactions; multiple influences on development, including the impact of family, school, community, social institutions, and the media; adolescents' preparation for entry into the workforce; cross-cultural research on development and learning; and the role of cultural influences and demographic characteristics on development. Additional priorities include research that: incorporates multidisciplinary, multi-method, microgenetic, and longitudinal approaches; develops new methods, models, and theories for studying learning and development; and integrates different processes (e.g., learning, memory, emotion), levels of analysis (e.g., behavioral, social, neural), and time scales (e.g. infancy, middle childhood, adolescence).

The Klarman Family Foundation is interested in providing strategic investment in translational research that will accelerate progress in developing effective treatments for anorexia nervosa, bulimia nervosa and binge eating disorder. The Program's short-term goal is to support the most outstanding science and expand the pool of scientists whose research explores the basic biology of feeding, anorexia nervosa, bulimia nervosa, and/or binge eating disorder. The long-term goal is to improve the lives of patients suffering from these conditions. Examples of funding areas include but are not limited to molecular genetic analysis of relevant neural circuit assembly and function; genetic and epigenetic research; animal models created by genetically altering neural circuits; and testing of new chemical entities that might be used in animal models as exploratory treatments.  Please note that imaging studies involving humans are not eligible. Investigators conducting research in the neuro-circuitry of fear conditioning or reward behavior may also apply but must justify the relevance of their research projects to the basic biology of eating disorders. Clinical psychotherapeutic studies, medication trials and research in the medical complications of these disorders are outside the scope of this Program.

The purpose of this Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative is to encourage applications that will develop and validate novel tools to facilitate the detailed analysis of complex circuits and provide insights into cellular interactions that underlie brain function. The new tools and technologies should inform and/or exploit cell-type and/or circuit-level specificity. 

The institute seeks teams of researchers working at different levels of analysis and employing integrative, novel, and creative experimental approaches to address high-risk, high-impact questions in basic neuroscience research, or in translational research with the primary objectives of: (a) advancing the state of the science in basic brain and behavior research that will uncover and dissect the underlying mechanisms that will ultimately provide the foundation for understanding mental disorders; (b) supporting the integration and translation of basic and clinical neuroscience research on severe mental illnesses; and/or (c) advancing our understanding of the neurobehavioral developmental mechanisms and trajectories of psychopathology that begin in childhood and adolescence.