The Function Biomedical Informatics Research Network Data Repository | JoVE Visualize

Area of Science:

Biomedical Informatics
Neuroimaging
Data Science

Background:

Multi-scanner functional magnetic resonance imaging (fMRI) studies face challenges due to variations in instrumentation, acquisition protocols, and analysis methods.
The Function Biomedical Informatics Research Network (FBIRN) was established to address these challenges and facilitate large-scale, multi-site neuroimaging research.

Purpose of the Study:

To develop methods and tools for conducting reliable multi-scanner fMRI studies.
To assess sources of variation in fMRI data acquired across different scanners and sites.
To create a distributed network infrastructure and federated database for sharing large fMRI and clinical datasets.

Main Methods:

FBIRN developed standardized protocols and analysis tools to mitigate variability in fMRI data acquisition and processing.
A federated database, the BIRN Data Repository (BDR), was implemented using the Human Imaging Database (HID) to host and query shared data.
Data were generated through multi-site studies, including a traveling subject study (Phase 1) and studies involving subjects with schizophrenia and healthy controls (Phase 2 and 3).

Main Results:

FBIRN successfully generated multi-scanner brain imaging datasets, including traveling subject data and clinical datasets.
These datasets, comprising fMRI and clinical information from healthy and patient populations, are now publicly available through the BIRN Data Repository.
The developed methods and tools aim to improve the consistency and comparability of fMRI studies conducted across different research sites and scanner platforms.

Conclusions:

FBIRN has provided valuable resources, including standardized methods, tools, and multi-site datasets, to the neuroimaging community.
The public sharing of these datasets through the BDR facilitates collaborative research and the advancement of understanding brain function and disorders.
This initiative enhances the capability for large-scale, multi-site fMRI research by addressing critical issues of data standardization and accessibility.