A Neuroinformatics Framework For Linking Genetic and Neuroimaging Data

Exploring the relation between genetics, behavior and cognition requires a system for capturing and vetting data, deriving measures, and linking data types. The Neuroinformatics Framework described here was developed to facilitate investigation through automated processing pipelines and enabling access to raw, quality control, and computationally derived data. The framework is built upon a custom installation of XNAT (Marcus et al., 2007), advancements in MRI acquisition methods, automated data processing, and online cognitive, personality and behavioral assessments. The framework has been utilized over the past two years to support the Brain Genomics Superstruct Project that has captured neuroimaging data from over 3100 human participants acquired across 24 investigators and 4 institutions. This large sample has enabled researchers to reveal relations between brain structure and personality traits (Holmes et al., 2011), expose the organization of large-scale networks (Yeo et al., 2011; Buckner et al., 2011), and quantify hemispheric asymmetry of functional networks (Liu et al., 2009). In this poster we describe the general strategies adopted within the framework. Center for Brain Science, Harvard University 1, Neuroinformatics Research Group 2, Athinoula A. Martinos Center for Biomedical Imaging 3, HHMI 4