- Main
The Function Biomedical Informatics Research Network Data Repository.
- Keator, David B;
- van Erp, Theo GM;
- Turner, Jessica A;
- Glover, Gary H;
- Mueller, Bryon A;
- Liu, Thomas T;
- Voyvodic, James T;
- Rasmussen, Jerod;
- Calhoun, Vince D;
- Lee, Hyo Jong;
- Toga, Arthur W;
- McEwen, Sarah;
- Ford, Judith M;
- Mathalon, Daniel H;
- Diaz, Michele;
- O'Leary, Daniel S;
- Jeremy Bockholt, H;
- Gadde, Syam;
- Preda, Adrian;
- Wible, Cynthia G;
- Stern, Hal S;
- Belger, Aysenil;
- McCarthy, Gregory;
- Ozyurt, Burak;
- Potkin, Steven G;
- FBIRN
- et al.
Published Web Location
https://doi.org/10.1016/j.neuroimage.2015.09.003Abstract
The Function Biomedical Informatics Research Network (FBIRN) developed methods and tools for conducting multi-scanner functional magnetic resonance imaging (fMRI) studies. Method and tool development were based on two major goals: 1) to assess the major sources of variation in fMRI studies conducted across scanners, including instrumentation, acquisition protocols, challenge tasks, and analysis methods, and 2) to provide a distributed network infrastructure and an associated federated database to host and query large, multi-site, fMRI and clinical data sets. In the process of achieving these goals the FBIRN test bed generated several multi-scanner brain imaging data sets to be shared with the wider scientific community via the BIRN Data Repository (BDR). The FBIRN Phase 1 data set consists of a traveling subject study of 5 healthy subjects, each scanned on 10 different 1.5 to 4 T scanners. The FBIRN Phase 2 and Phase 3 data sets consist of subjects with schizophrenia or schizoaffective disorder along with healthy comparison subjects scanned at multiple sites. In this paper, we provide concise descriptions of FBIRN's multi-scanner brain imaging data sets and details about the BIRN Data Repository instance of the Human Imaging Database (HID) used to publicly share the data.
Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. Let us know how this access is important for you.
Main Content
Enter the password to open this PDF file:
-
-
-
-
-
-
-
-
-
-
-
-
-
-