• Randy L Gollub, Jody M Shoemaker, Margaret D King, Tonya White, Stefan Ehrlich, Scott R Sponheim, Vincent P Clark, Jessica A Turner, Bryon A Mueller, Vince Magnotta, Daniel O'Leary, Beng C Ho, Stefan Brauns, Dara S Manoach, Larry Seidman, Juan R Bustillo, John Lauriello, Jeremy Bockholt, Kelvin O Lim, Bruce R Rosen, S Charles Schulz, Vince D Calhoun, and Nancy C Andreasen.
• Department of Psychiatry, Massachusetts General Hospital, Building 120, Suite 101D, Charlestown, MA 02129-2000, USA. RGOLLUB@PARTNERS.ORG
• Neuroinformatics. 2013 Jul 1;11(3):367-88.

AbstractExpertly collected, well-curated data sets consisting of comprehensive clinical characterization and raw structural, functional and diffusion-weighted DICOM images in schizophrenia patients and sex and age-matched controls are now accessible to the scientific community through an on-line data repository (coins.mrn.org). The Mental Illness and Neuroscience Discovery Institute, now the Mind Research Network (MRN, http://www.mrn.org/ ), comprised of investigators at the University of New Mexico, the University of Minnesota, Massachusetts General Hospital, and the University of Iowa, conducted a cross-sectional study to identify quantitative neuroimaging biomarkers of schizophrenia. Data acquisition across multiple sites permitted the integration and cross-validation of clinical, cognitive, morphometric, and functional neuroimaging results gathered from unique samples of schizophrenia patients and controls using a common protocol across sites. Particular effort was made to recruit patients early in the course of their illness, at the onset of their symptoms. There is a relatively even sampling of illness duration in chronic patients. This data repository will be useful to 1) scientists who can study schizophrenia by further analysis of this cohort and/or by pooling with other data; 2) computer scientists and software algorithm developers for testing and validating novel registration, segmentation, and other analysis software; and 3) educators in the fields of neuroimaging, medical image analysis and medical imaging informatics who need exemplar data sets for courses and workshops. Sharing provides the opportunity for independent replication of already published results from this data set and novel exploration. This manuscript describes the inclusion/exclusion criteria, imaging parameters and other information that will assist those wishing to use this data repository.

32 keywords...

hide…