Management and data analysis

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Management and analysis of the very large data sets with ultra-high information content acquired by the neurolmaging and neurophysiology Cores requires specialized expertise and resources. Core 4 implements and supports usage of state-of-the-art image processing and data analysis programs for neuroscientists using Cores 1, 2 and 3. While a large number of software analysis packages and methods have been developed for human MRI data, the packages available for animal MRI and MRS have been limited. To address these limitations Core 4 created a suite of tools optimized for processing of small animal MR data and integrated them with various commercial and in-house software, which together provides support for all software needs of QNMR Core Center scientists and collaborating Pis. Users rely on a server-based high-performance cluster that provides rapid data access, backup, and sharing. The qualifying user group of Core 4 consists of 11 Pis funded by NINDS who along with 17 other NIH-funded Pis use multi-modal MR/neurophysiology software tools to process data to answer fundamental questions in basic and clinical neuroscience. The impact of Core 4 of Yale's QNMR Core Center is evidenced by its support of 32 NIH grants and 9 new research initiatives that led to papers and grants, the training of 5 neuroscientists (3 in NINDS PI laboratories) in advanced MRI/MRS data analysis and processing, and the use of Core 4 developed software in 51 papers that led to 388 citations (for Core 4 alone this represents 32% of the total citations for 106 papers for all Cores). For the next cycle, we will continue to implement, maintain, arid support innovative advanced and user-specific data analysis tools for Core 4 users, support new research initiatives, train and provide mentorship for neuroscience Pis and their personnel for Core 4 usage, facilitate synergistic use of MR/neurophysiological measurements and project specific data analysis, implement new image processing and data analysis methods to support neuroscience Pis, and track Core 4 activities and disseminate/share resources to NIH community. The implemented methods include user-specific tools needed to efficiently analyze cross-modal data to enhance NINDS- and NIH-funded research.