Improving the analysis, storage and sharing of neuroimaging data using relational databases and distributed computing.
The increasingly complex research questions addressed by neuroimaging research impose substantial demands on computational infrastructures. These infrastructures need to support management of massive amounts of data in a way that affords rapid and precise data analysis, to allow collaborative research, and to achieve these aims securely and with minimum management overhead. Here we present an approach that overcomes many current limitations in data analysis and data sharing. This approach is based on open source database management systems that support complex data queries as an integral part of data analysis, flexible data sharing, and parallel and distributed data processing using cluster computing and Grid computing resources. We assess the strengths of these approaches as compared to current frameworks based on storage of binary or text files. We then describe in detail the implementation of such a system and provide a concrete description of how it was used to enable a complex analysis of fMRI time series data.
Hasson
Uri
U
Department of Neurology, The University of Chicago, Chicago, IL 60637, USA. uhasson@uchicago.edu
Skipper
Jeremy I
JI
Wilde
Michael J
MJ
Nusbaum
Howard C
HC
Small
Steven L
SL
D003195:Computer Communication Networks / Q000706:statistics & numerical data*; D003628:Database Management Systems; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods* / Q000706:statistics & numerical data; D016247:Information Storage and Retrieval / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000706:statistics & numerical data; D009420:Nervous System / Q000033:anatomy & histology* / Q000473:pathology; D049268:Positron-Emission Tomography / Q000706:statistics & numerical data