Open science resources for ‘Big Data’ analyses of the human connectome Cameron Craddock, PhD Computational Neuroimaging Lab Center for Biomedical Imaging and Neuromodulation Nathan S. Kline Institute for Psychiatric Research Center for the Developing Brain Child Mind Institute
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Open science resources for `Big Data' Analyses of the human connectome
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Discovery science of human brain function1. Characterizing inter-individual variation in connectomes (Kelly et al. 2012)
2. Identifying biomarkers of disease state, severity, and prognosis (Craddock 2009)
3. Re-defining mental health in terms of neurophenotypes, e.g. RDOC (Castellanos 2013)
Data is often shared only in its raw form – must be preprocessed to remove nuisance variation and to be made comparable across individuals and sites.
No consensus on preprocessing
This is particularly complicated for “post-hoc” aggregated datasets
A variety of analyses
The cost of discovery“Best practice” r-fMRI preprocessing: ~ 2 hours
Discovery dataset: ~1,000 subjects“Point and click” processing: 2,000 person hours (1 year)
Scripted processing: 2,000 CPU hours (84 days to minutes)
Different derivatives and analyses add timeDifferent preprocessing strategies scale time
Configurable Pipeline for the Analysis of Connectomes (CPAC)
• Pipeline to automate preprocessing and analysis of large-scale datasets
• Most cutting edge functional connectivity preprocessing and analysis algorithms
• Configurable to enable “plurality” – evaluate different processing parameters and strategies
• Automatically identifies and takes advantage of parallelism on multi-threaded, multi-core, and cluster architectures
• “Warm restarts” – only re-compute what has changed• Open science – open source• http://fcp-indi.github.io
Nypipe
• 33 datasets acquired with a variety of different test-retest designs– Intra- and inter-session re-tests– 1629 subjects– 3357 anatomical MRI scans– 5093 resting state fMRI scans– 1302 diffusion MRI scans
Regional Brainhacks• One event that linked 8 Cities, 3
Countries, 2 continents– Ann Arbor– Boston– Miami– Montreal– New York City– Porto Alegre, Brazil– Toronto– Washington DC
AcknowledgementsCPAC Team: Daniel Clark, Steven Giavasis and Michael Milham.
Quality Assessment Protocol: Zarrar Shehzad, Daniel Lurie, Steven Giavasis, and Sang Han Lee.
ABIDE Preprocessed: Pierre Bellec, Yassine Benhajali, Francois Chouinard, Daniel Clark, R. Cameron Craddock, Alan Evans, Steven Giavasis, Budhachandra Khundrakpam, John Lewis, Qingyang Li, Zarrar Shezhad, Aimi Watanabe, Ting Xu, Chao-Gan Yan, Zhen Yang, Xinian Zuo, and the ABIDE consortium.
Brainhack Organizers: Pierre Bellec, Daniel Margulies, Maarten Mennes, Donald McLauren, Satra Ghosh, Matt Hutchison, Robert Welsh, Scott Peltier, Jonathan Downer, Stephen Strother, Katie Dunlop, Angie Laird, Lucina Uddin, Benjamin De Leener, Julien Cohen-Adad, Andrew Gerber, Alex Franco, Caroline Froehlich, Felipe Meneguzzi, John VanMeter, Lei Liew, Ziad Saad, Prantik Kundu
CPAC-NDAR integration was funded by a contract from NDAR.ABIDE Preprocessed data is hosted in a Public S3 Bucket provided by AWS.