%A Laird,Angela %A Eickhoff,Simon %A Kurth,Florian %A Fox,Peter %A Uecker,Angela %A Turner,Jessica %A Robinson,Jennifer %A Lancaster,Jack %A Fox,Peter %D 2009 %J Frontiers in Neuroinformatics %C %F %G English %K activation likelihood estimation,BrainMap,functional atlas,Meta-analysis,ontology %Q %R 10.3389/neuro.11.023.2009 %W %L %M %P %7 %8 2009-July-09 %9 Original Research %+ Dr Angela Laird,University of Texas Health Science Center San Antonio,Research Imaging Center,San Antonio,United States,angie.laird@mac.com %# %! ALE meta-analysis workflows via BrainMap %* %< %T ALE meta-analysis workflows via the BrainMap database: progress towards a probabilistic functional brain atlas %U https://www.frontiersin.org/articles/10.3389/neuro.11.023.2009 %V 3 %0 JOURNAL ARTICLE %@ 1662-5196 %X 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.