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|a pmc:PMC2715269
024 7 _ |2 DOI
|a 10.3389/neuro.11.023.2009
024 7 _ |2 ISSN
|a 1662-5196
037 _ _ |a PreJuSER-5390
041 _ _ |a eng
082 _ _ |a 610
100 1 _ |0 P:(DE-HGF)0
|a Laird, A.R.
|b 0
245 _ _ |a ALE meta-analysis workflows via the BrainMap database: progress towards a probabilistic functional brain altlas
260 _ _ |a Lausanne
|b Frontiers Research Foundation
|c 2009
300 _ _ |a 1 - 11
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|a Frontiers in Neuroinformatics
|v 3
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|y 23
500 _ _ |a Record converted from VDB: 12.11.2012
520 _ _ |a With the ever-increasing number of studies in human functional brain mapping, an abundance of data has been generated that is ready to be synthesized and modeled on a large scale. The BrainMap database archives peak coordinates from published neuroimaging studies, along with the corresponding metadata that summarize the experimental design. BrainMap was designed to facilitate quantitative meta-analysis of neuroimaging results reported in the literature and supports the use of the activation likelihood estimation (ALE) method. In this paper, we present a discussion of the potential analyses that are possible using the BrainMap database and coordinate-based ALE meta-analyses, along with some examples of how these tools can be applied to create a probabilistic atlas and ontological system of describing function-structure correspondences.
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|a Eickhoff, S. B.
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|a Kurth, F.
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|a Fox, P.M.
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|a Uecker, A.M.
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|a Turner, J.A.
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|a Robinson, J.L.
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700 1 _ |0 P:(DE-HGF)0
|a Lancaster, J.L.
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700 1 _ |0 P:(DE-HGF)0
|a Fox, P.T.
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|x 1662-5196
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856 7 _ |2 Pubmed Central
|u http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2715269
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