A OHBM Satellite meeting, Friday, June 19, 2015, Honolulu.

Organizers

Michelle Freund, National Insitutes of Health; Jessica Turner, Georgia State University; and Thomas Nichols, University of Warwick

About the meeting

The volume of neuroimaging data produced is increasing steadily, as are explicit "big data" projects, where 100's or 1000's of subjects are studied and shared with the community. Even for small studies, it is increasingly required that the imaging data are shared. However the value of this quantity of data will be limited if a constellation of different methodologies are used in its preparation. For many aspects of brain imaging, the imaging and analysis techniques have matured so that best-practice options are easily identifiable.

Meeting Purpose

The purpose of the workshop is to bring together experts methodologists and leaders of neuroimaging studies large and small to discuss ways to harmonize practice. From image acquisition sequence, to quality control methods, to statistical analyses, NIMH is seeking ways to maximize the utility of shared resources. It is seeking input on how to publicize the existing tools that could be embraced to minimize site-to-site variability, and to identify shortcomings in existing tools that make it more difficult for users to produce high quality and comparable neuroimaging results. A series of short presentations will be followed by a lengthy discussion from all participants.

Talks

• Workshop Goals and Overview of Existing Resources
  • Workshop Intro
    Michelle Freund, NIMH
  • What we are trying to do
    Jessica Turner, Georgia State University
  • Prospective Harmonization
    Thomas Nichols, University of Warwick
• Aggregation by modality
  • Coordinated Analysis of Brain Imaging, Genomic, and Clinical Data in the ENIGMA Consortium
    Derrek Hibar, University of Southern California
  • Intersite effects in task-based fMRI: the fBIRN Traveling Subjects
    Doug Greve, Harvard University
  • Prospective Harmonization
    Michael Milham, Child Mind Institute
  • Homogenizing data using ENIGMA-MEGA analysis
    Peter Kochunov, Maryland Psychiatric Research Center
• QC & Analysis considerations
  • Harmonizing DTI data: Mind Research Network, Oxford, and Rotterdam, a view from the trenches 
    Tonya White, Erasmus MC, Rotterdam
  • Assessing the quality of ongoing acquisitions
    Doug Greve, Harvard University
  • Harmonizing sMRI Data via Robust Preprocessing
    Aristeidis Sotiras, University of Pennyslyvania
  • Brain Imaging Data Structure: Data organization standard for neuroimaging experiments
    Chris Gorgolewski, Stanford University