High Resolution, Comprehensive Atlases of the Human Brain Morphology

项目总结

Project Summary The past decade has brought an explosion in the development of precise acquisition and analytic tools (both mathematical and statistical) that allow for investigating in-vivo brain imaging data in the context of interconnected networks, or connectomes. This rapid advancement, fueled by additional funds from Congress (BRAIN initiative), however, is not mirrored by the development of neuroanatomy atlases and ontology tools that would make in-vivo connectivity analysis more accurate. For one, the advent of the Human Connectome Project, generating large high-resolution datasets, is creating a need for development of corresponding, high definition atlases. This, however, requires time, and interdisciplinary anatomical knowledge. In addition, the atlases that exist are rarely portable, flexible, or easily transferable between image analysis tools, and do not follow a common standard of neuroanatomy. The overall aim of this project is to generate and disseminate state-of-the-art, high-resolution full brain MR atlases, as the extension of the previous version of the Harvard-Oxford Atlas (HOA), a popular and widely available atlas through FMRIB Software Library (FSL) atlas, developed in our labs over a decade ago. As part of this project, we will: 1. Consolidate expert neuroanatomical knowledge into a single ontology. This will include the development of a graphical representation of regions' structural relationships, both hierarchical (lobes, lobules, gyri and subcortical structures) and network-based; 2. Manually parcellate (using developed ontologies) 200 MR datasets provided as part of the publicly available Human Connectome Project dataset; and 3. Refine a software platform for storing, editing and disseminating the atlases that will include version control and the ability for the neuroanatomical community to contribute new atlases or modifications to this 2nd Generation HOA atlas. Upon the successful completion of this project, we will have provided the neuroscientific community with an unprecedented data set of 200 high definition MR data parcellated into 392 gray and white matter PUs using structural MRI and 189 white matter fascicles using diffusion MRI. All structures will be described in a comprehensive taxonomy based on decades of neuroanatomical expertise. Importantly, the data set will be freely available to the community and distributed in an atlas-tailored revision control system, that will track changes in atlas image data and metadata and will integrate with tools for atlas release and distribution.