The experiments proposed in the Center include extensive use of neuroimaging in both normal control participants and patient groups. Core C will support the individual projects in data acquisition and quality control, implementation of processing pipelines, and capture of raw data for cross-project analyses and eventual broader distribution to the community.
Aim 1 : The core will assist in implementation of MRI acquisition procedures and anticipated transitions in MR hardware. All project sites currently have available similar Siemens Trio scanners and anticipate transition to the PRISMA system in coming years. The uniformity of hardware and expected transitions provides an opportunity to unify data acquisition and facilitate transition to next-generation functional MRI data acquisition procedures. Optimization of target PRISMA sequences will be performed including direct analysis of comparability to existing Trio sequences.
Aim 2 : A centralized database will capture all neuroimaging data collected across sites. The neuroinformatics backbone will be based on a custom implementation of the Extensible Neuroimaging Archive Toolkit (XNAT; Marcus et al., 2007). The installation will store each subject's data with metadata about the data types, etc to allow future uses. These data will be accessible to project investigators and stored ready for wide data sharing.
Aim 3 : The core will provide quality control data assessments. Data quality and uniformity is important to MRI data acquisition, in particular for functional MRI data that is notorious plagued by artifacts of subject compliance and head motion. The core will assess all neuroimaging data acquired in P1-4 for artifacts and make recommendations to improve data quality. Quantitative quality control measures will include assessment of motion and overall signal-to-noise characteristics. The quality control procedures are modeled after those adopted by the NIMH EMBARC trial and implemented in the Simons VIP projects studying autism.
Aim 4 : The core will develop novel statistical models and computational tools for an fcMRI test for differences between populations (OCD vs healthy controls), effects of treatment (cingulotomy; TMS; direct and indirect modulation) while accounting for between-subject variation.
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