Bridging the Brain and Data Sciences.

Big Data
John Darrell Van Horn

Abstract

Brain scientists are now capable of collecting more data in a single experiment than researchers a generation ago might have collected over an entire career. Indeed, the brain itself seems to thirst for more and more data. Such digital information not only comprises individual studies but is also increasingly shared and made openly available for secondary, confirmatory, and/or combined analyses. Numerous web resources now exist containing data across spatiotemporal scales. Data processing workflow technologies running via cloud-enabled computing infrastructures allow for large-scale processing. Such a move toward greater openness is fundamentally changing how brain science results are communicated and linked to available raw data and processed results. Ethical, professional, and motivational issues challenge the whole-scale commitment to data-driven neuroscience. Nevertheless, fueled by government investments into primary brain data collection coupled with increased sharing and community pressure challenging the dominant publishing model, large-scale brain and data science is here to stay.

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Methods Mentioned

BETA
SMA
dissections

Clinical Trials Mentioned

NCT00756821

Software Mentioned

Kepler
ENIGMA
BIDS
Taverna
Amazon AWS
Microsoft Azure
Paraview
LONI
FreeSurfer
Galaxy

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