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Cite this (CCHMC Pediatric Brain Templates, RRID:SCR_003276)


Resource Type: Resource, atlas, image collection, reference atlas, data or information resource

Brain imaging data collected from a large population of normal, healthy children that have been used to construct pediatric brain templates, which can be used within statistical parametric mapping for spatial normalization, tissue segmentation and visualization of imaging study results. The data has been processed and compiled in various ways to accommodate a wide range of possible research approaches. The templates are made available free of charge to all interested parties for research purposes only. When processing imaging data from children, it is important to take into account the fact that the pediatric brain differs significantly from the adult brain. Therefore, optimized processing requires appropriate reference data be used because adult reference data will introduce a systematic bias into the results. We have shown that, in the in the case of spatial normalization, the amount of non-linear deformation is dramatically less when a pediatric template is used (left, see also HBM 2002; 17:48-60). We could also show that tissue composition is substantially different between adults and children, and more so the younger the children are (right, see also MRM 2003; 50:749-757). We thus believe that the use of pediatric reference data might be more appropriate.

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Cite this (ConnectomeDB, RRID:SCR_004830)


Resource Type: Resource, database, image collection, service resource, storage service resource, image repository, data repository, data or information resource

Data management platform that houses all data generated by the Human Connectome Project - image data, clinical evaluations, behavioral data and more. ConnectomeDB stores raw image data, as well as results of analysis and processing pipelines. Using the ConnectomeDB infrastructure, research centers will be also able to manage Connectome-like projects, including data upload and entry, quality control, processing pipelines, and data distribution. ConnectomeDB is designed to be a data-mining tool, that allows users to generate and test hypotheses based on groups of subjects. Using the ConnectomeDB interface, users can easily search, browse and filter large amounts of subject data, and download necessary files for many kinds of analysis. ConnectomeDB is designed to work seamlessly with Connectome Workbench, an interactive, multidimensional visualization platform designed specifically for handling connectivity data. De-identified data within ConnectomeDB is publicly accessible. Access to additional data may be available to qualified research investigators. ConnectomeDB is being hosted on a BlueArc storage platform housed at Washington University through the year 2020. This data platform is based on XNAT, an open-source image informatics software toolkit developed by the NRG at Washington University. ConnectomeDB itself is fully open source.

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Cite this (Spatially unbiased atlas template of the cerebellum and brainstem, RRID:SCR_004969)


Resource Type: Resource, atlas, software resource, reference atlas, data or information resource

High-resolution atlas template of the human cerebellum and brainstem, based on the anatomy of 20 young healthy individuals. The atlas is spatially unbiased, i.e. the location of each structure is equal to the expected location of that structure across individuals in MNI space. At the same time, the new template preserves the anatomical detail of cerebellar structures through a nonlinear atlas-generation algorithm. By using automated nonlinear normalization methods, a more accurate intersubject-alignment than current whole-brain methods can be achieved. The toolbox allows you to: * Automatically isolate cerebellar structures from the cerebral cortex based on an anatomical image * Achieve accurate anatomical normalization of cerebellar structures * Normalize functional imaging data for fMRI group analysis * Normalize focal cerebellar lesions for lesion-symptom mapping * Use Voxel-based morphometry (VBM) to determine patterns of cerebellar degeneration or growth * Use a probabilisitc atlas in SUIT space to assign locations to different cerebellar lobuli in an unbiased and informed way * Automatically define ROIs for specific cerebellar lobuli and summarize function and anatomical data * Improve normalization of the deep cerebellar nuclei using an ROI-driven normalization. The suit-toolbox requires Matlab (Version 6.5 and higher) and SPM. The newest version only supports SPM8, although it likely runs under SPM2 or 5 as well. A standalone version for the suit-toolbox is not planned. Usage of the isolation or normalization functions, however, does not require that the analysis is conducted under SPM.

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