Improving the analysis, storage and sharing of neuroimaging data using relational databases and distributed computing
被引:26
作者:
Hasson, Uri
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机构:
Univ Chicago, Dept Neurol, Chicago, IL USA
Univ Chicago, Dept Psychol, Chicago, IL USAUniv Chicago, Dept Neurol, Chicago, IL USA
Hasson, Uri
[1
,2
]
Skipper, Jeremy I.
论文数: 0引用数: 0
h-index: 0
机构:
Univ Chicago, Dept Neurol, Chicago, IL USA
Univ Chicago, Dept Psychol, Chicago, IL USAUniv Chicago, Dept Neurol, Chicago, IL USA
Skipper, Jeremy I.
[1
,2
]
Wilde, Michael J.
论文数: 0引用数: 0
h-index: 0
机构:
Univ Chicago, Computat Inst, Chicago, IL USA
Argonne Natl Lab, Div Math & Comp Sci, Argonne, IL USAUniv Chicago, Dept Neurol, Chicago, IL USA
Wilde, Michael J.
[3
,4
]
Nusbaum, Howard C.
论文数: 0引用数: 0
h-index: 0
机构:
Univ Chicago, Dept Psychol, Chicago, IL USA
Univ Chicago, Ctr Cognit & Soc Neurosci, Chicago, IL USAUniv Chicago, Dept Neurol, Chicago, IL USA
Nusbaum, Howard C.
[2
,5
]
Small, Steven L.
论文数: 0引用数: 0
h-index: 0
机构:
Univ Chicago, Dept Neurol, Chicago, IL USA
Univ Chicago, Dept Psychol, Chicago, IL USA
Univ Chicago, Brain Res Imaging Ctr, Chicago, IL USAUniv Chicago, Dept Neurol, Chicago, IL USA
Small, Steven L.
[1
,2
,6
]
机构:
[1] Univ Chicago, Dept Neurol, Chicago, IL USA
[2] Univ Chicago, Dept Psychol, Chicago, IL USA
[3] Univ Chicago, Computat Inst, Chicago, IL USA
[4] Argonne Natl Lab, Div Math & Comp Sci, Argonne, IL USA
[5] Univ Chicago, Ctr Cognit & Soc Neurosci, Chicago, IL USA
[6] Univ Chicago, Brain Res Imaging Ctr, Chicago, IL USA
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. (C) 2007 Elsevier Inc. All rights reserved.
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页码:693 / 706
页数:14
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