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

doi:10.3389/neuro.11.023.2009

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

Department of Radiology

Research output: Contribution to journal › Article › peer-review

306 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 language	English (US)
Article number	23
Journal	Frontiers in Neuroinformatics
Volume	3
Issue number	JUL
DOIs	https://doi.org/10.3389/neuro.11.023.2009
State	Published - 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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10.3389/neuro.11.023.2009

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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.",

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AU - Fox, Peter M.

AU - Uecker, Angela M.

AU - Turner, Jessica A.

AU - Robinson, Jennifer L.

AU - Lancaster, Jack L.

AU - Fox, Peter T.

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

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

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