RCN: A Research Coordinaton Network for X-ray Motion Analysis

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Newly developed x-ray technologies can now reveal the rapid, three-dimensional (3D) movements of bones during running, swimming, flying, breathing, and feeding activities of diverse animals. X-ray Motion Analysis (XMA) and X-ray Reconstruction of Moving Morphology (XROMM) are poised to transform the way biologists investigate how muscles and bones interact to produce rapid and complex movements in animals. The goal of this project is to develop a Research Coordination Network of scientists and students working with these new technologies. This RCN-XMA will: (1) offer technical training to reduce barriers to XMA/XROMM use for scientists and students, including those from colleges and universities with limited resources for research; (2) make it possible to share data and work together by developing community consensus on data formats; (3) create a centralized computer storage system and database for XMA/XROMM research. With the x-ray facilities at Brown University and University of Nevada at Las Vegas as training and collaborative research centers, the RCN-XMA seeks to advance and extend XMA/XROMM technology to a national and global community of zoologists and biomechanists. The RCN-XMA will contribute to broadening the participation of underrepresented groups by bringing high-school science teachers from Providence Public School system (demographics of PPS students: 81% from groups underrepresented in the sciences, 80% free or reduced-price lunch) into this highly collaborative and interdisciplinary research enterprise. Teachers will gain first-hand research experience and develop learning modules that integrate biology with math/physical sciences, one of the goals of the Rhode Island's "Physics First" educational initiative. This project has the potential to transform research in the field of comparative biomechanics by: (1) introducing a new and powerful set of x-ray measurement technologies; and (2) by developing new data management standards that could vastly increase the value of all existing and new comparative biomechanics data, not just XMA/XROMM data, by making them available in databases for data mining and collaborative research.