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. 2010 Apr 21:3:36.
doi: 10.3389/neuro.11.036.2009. eCollection 2010.

Mining the mind research network: a novel framework for exploring large scale, heterogeneous translational neuroscience research data sources

Henry J Bockholt  1 , Mark Scully, William Courtney, Srinivas Rachakonda, Adam Scott, Arvind Caprihan, Jill Fries, Ravi Kalyanam, Judith M Segall, Raul de la Garza, Susan Lane, Vince D Calhoun
Affiliations

Mining the mind research network: a novel framework for exploring large scale, heterogeneous translational neuroscience research data sources

Henry J Bockholt et al. Front Neuroinform. .

Abstract

A neuroinformatics (NI) system is critical to brain imaging research in order to shorten the time between study conception and results. Such a NI system is required to scale well when large numbers of subjects are studied. Further, when multiple sites participate in research projects organizational issues become increasingly difficult. Optimized NI applications mitigate these problems. Additionally, NI software enables coordination across multiple studies, leveraging advantages potentially leading to exponential research discoveries. The web-based, Mind Research Network (MRN), database system has been designed and improved through our experience with 200 research studies and 250 researchers from seven different institutions. The MRN tools permit the collection, management, reporting and efficient use of large scale, heterogeneous data sources, e.g., multiple institutions, multiple principal investigators, multiple research programs and studies, and multimodal acquisitions. We have collected and analyzed data sets on thousands of research participants and have set up a framework to automatically analyze the data, thereby making efficient, practical data mining of this vast resource possible. This paper presents a comprehensive framework for capturing and analyzing heterogeneous neuroscience research data sources that has been fully optimized for end-users to perform novel data mining.

Keywords: Mind Clinical Imaging Consortium; XCEDE; XML; data mining; magnetic resonance imaging.

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Figures

Figure 1
Figure 1
Neuroinformatics data tools.
Figure 2
Figure 2
Overview of MRN Neuroinformatics System.
Figure 3
Figure 3
Real-time annotation tool.
Figure 4
Figure 4
Data querying application tool.
Figure 5
Figure 5
Quality control chart example.
Figure 6
Figure 6
First level analysis planning.
Figure 7
Figure 7
One sample t-test calculated on 12 images (six healthy and six schizophrenics) with a T-threshold of 1. 5 applied to the t-map.
Figure 8
Figure 8
Class mean run on five healthy, five schizophrenics and two images unknowns. Image shown is the mean image of group 1 thresholded at 1.0.
See this image and copyright information in PMC

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