ALE meta-analysis workfl ows via the BrainMap database: Progress towards a probabilistic functional brain atlas

Angela R. Laird, Simon B. Eickhoff, Florian Kurth, Peter M. Fox, Angela M. Uecker, Jessica A. Turner, Jennifer L. Robinson, Jack L. Lancaster, Peter T. Fox

Research output: Contribution to journalArticlepeer-review

228 Scopus citations

Abstract

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.

Original languageEnglish (US)
Article number23
JournalFrontiers in Neuroinformatics
Volume3
Issue numberJUL
DOIs
StatePublished - Jul 9 2009

Keywords

  • Activation likelihood estimation
  • BrainMap
  • Functional atlas
  • Meta-analysis
  • Ontology

ASJC Scopus subject areas

  • Neuroscience (miscellaneous)
  • Biomedical Engineering
  • Computer Science Applications

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