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Open Access Highly Accessed Technical Note

The BrainMap strategy for standardization, sharing, and meta-analysis of neuroimaging data

Angela R Laird1*, Simon B Eickhoff23, P Mickle Fox1, Angela M Uecker1, Kimberly L Ray1, Juan J Saenz14, D Reese McKay1, Danilo Bzdok23, Robert W Laird4, Jennifer L Robinson56, Jessica A Turner7, Peter E Turkeltaub8, Jack L Lancaster1 and Peter T Fox1

Author Affiliations

1 Research Imaging Institute, University of Texas Health Science Center, San Antonio, TX, USA

2 Department of Psychiatry and Psychotherapy, RWTH Aachen University, Germany

3 Institute of Neuroscience and Medicine (INM - 2), Research Center Jülich, Jülich, Germany

4 Department of Physics and Earth Sciences, St. Mary's University, San Antonio, TX, USA

5 Scott & White Memorial Hospital, Neuroscience Institute, Temple, TX, USA

6 Texas A&M Health Science Center, College of Medicine, Temple, TX, USA

7 The Mind Research Network, Albuquerque, NM, USA

8 Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA

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BMC Research Notes 2011, 4:349  doi:10.1186/1756-0500-4-349

Published: 9 September 2011

Abstract

Background

Neuroimaging researchers have developed rigorous community data and metadata standards that encourage meta-analysis as a method for establishing robust and meaningful convergence of knowledge of human brain structure and function. Capitalizing on these standards, the BrainMap project offers databases, software applications, and other associated tools for supporting and promoting quantitative coordinate-based meta-analysis of the structural and functional neuroimaging literature.

Findings

In this report, we describe recent technical updates to the project and provide an educational description for performing meta-analyses in the BrainMap environment.

Conclusions

The BrainMap project will continue to evolve in response to the meta-analytic needs of biomedical researchers in the structural and functional neuroimaging communities. Future work on the BrainMap project regarding software and hardware advances are also discussed.

Keywords:
functional neuroimaging; structural neuroimaging; meta-analysis; BrainMap; neuroinformatics; activation likelihood estimation; ALE