CRNC - Training Core Project Abstract Our proposed BTRC resource, the Center for Reproducible Neuroimaging Computation (CRNC), aims to improve the way neuroimaging research is performed and reported. By developing and implementing technology to support a comprehensive set of data management, analysis and utilization frameworks for basic research and clinical activities, we seek to improve the reproducibility of neuroimaging science and extend the value of our national investment in neuroimaging research. Reproducibility is critical because the current literature is fraught with published ?results? that are false positives. This is mostly due to the lack of statistical power as well as analysis or software errors (occasionally misconduct). More importantly, given the current publication system, null findings are not published making it exceedingly difficult to discern between false positive and true positive finding as data is hard to aggregate, and exact methods are hard to replicate. In this Training and Dissemination Core, we provide training and education to the community to foster continued use and development of the reproducible framework in neuroimaging research. In neuroimaging, training is often focused on teaching the specificities of a particular tool, such as a single analysis software. Short workshops tend to be more a demonstration of a series of tools than the acquisition of in depth knowledge. We seek a new scalable strategy for training, by considering that core online courses focused on the CRNC reproducible research tools can be complemented by more foundational knowledge. To accomplish this, we will: 1) Provide specific training on the CRNC concepts, products and tools necessary for a full cycle of reproducible research; 2) Provide complementary training on the computational and statistical frameworks and techniques underlying our tools and train power users on the CRNC products. We will work in partnership with the other TR&D projects and the Collaborator and Service Project users to teach this reproducible analysis system and to foster the use of the reproducible framework and collaborations in the neuroimaging research community.
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