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ALE Meta-Analysis Workflows Via the Brainmap Database: Progress Towards A Probabilistic Functional Brain Atlas.

Angela R Laird¹, Simon B Eickhoff, Florian Kurth

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

Frontiers in Neuroinformatics

|July 29, 2009

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The BrainMap database synthesizes neuroimaging data for large-scale modeling. It supports quantitative meta-analyses using activation likelihood estimation (ALE) to map brain function and structure.

Area of Science:

Neuroscience
Brain Mapping
Data Science

Background:

Human functional brain mapping generates vast amounts of data.
Existing data requires synthesis and large-scale modeling.
The BrainMap database archives neuroimaging study coordinates and metadata.

Purpose of the Study:

To discuss potential analyses using the BrainMap database.
To explore coordinate-based activation likelihood estimation (ALE) meta-analyses.
To demonstrate applications in creating probabilistic atlases and ontological systems for function-structure correspondences.

Main Methods:

Utilizing the BrainMap database for data aggregation.
Applying the activation likelihood estimation (ALE) method for meta-analysis.

Keywords:

BrainMap activation likelihood estimation functional atlas meta-analysis ontology

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Developing probabilistic atlases and ontological systems.

Main Results:

Demonstration of quantitative meta-analysis capabilities.
Examples of creating functional brain atlases.
Illustrations of ontological systems for brain function-structure relationships.

Conclusions:

The BrainMap database and ALE methods facilitate large-scale synthesis of neuroimaging data.
These tools enable the creation of valuable resources like probabilistic brain atlases.
Potential for advancing the understanding of brain function-structure correspondences.