Our understanding of nervous system function is critically dependent on visualizing the three-dimensional structure of the brain. The brain is composed of many cell types that are organized into complex networks to produce neural functions such as cognition. The brains of patients with neuropsychiatric illness often display disorganized cell placement as compared to brains of healthy individuals. It is therefore fundamentally important to determine how the details of cell type and organization relate to cognition and behavior. Recent advances in structural brain imaging have enabled the possibility for creating digital data sets of complete intact brain specimens at cellular resolution. However, given the enormous number of neurons in the mammalian brain, the data sets produced with these techniques are so large as to hamper the research process. In this project, we will present a novel computational infrastructure framework that addresses this challenge, with the ultimate aim of facilitating collaboration among laboratories that generate and use these large cellular imaging data sets for neuroscience discovery. This project therefore aligns with the NSF mission to promote the progress of science and to advance the national health, prosperity and welfare.
Recent innovations in tissue clearing techniques and light sheet microscopy allow the rapid acquisition of three-dimensional micron resolution images in fluorescently labeled brain samples. However, the enormous size of the resulting information-dense data sets present great computational challenges to sharing, analysis, and visualization of these data in a standardized manner across multiple laboratories. In this project, the combined expertise of three connected and complementary centers associated with the University of North Carolina at Chapel Hill will be leveraged to address this issue through development of a unified and highly scalable computational infrastructure framework that can be harnessed by the neuroscience community. The several aims are to develop cyberinfrastructure for the distributed storage, sharing and analysis of high-dimensional images; develop high throughput computational tools for quantitative analysis of 3D microscopy images; provide the means for efficient visualization of results using immersive environments; and demonstrate the utility of these tools by applying them to the analysis, sharing, and visualization of brain structure deficits in an autism mouse model.
This Early-concept Grants for Exploratory Research (EAGER) award by the CISE Division of Advanced Cyberinfrastructure is jointly supported by the CISE Division of Information and Intelligent Systems, with funds associated with the NSF Understanding the Brain, BRAIN Initiative activities, and developing national research infrastructure for neuroscience. This project also aligns with NSF objectives under the National Strategic Computing Initiative.
