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Evaluating the consistency and specificity of neuroimaging data using meta-analysis

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Wager, Tor D., Lindquist, Martin A., Nichols, Thomas E., Kober, Hedy and Van Snellenberg, Jared X. (2008) Evaluating the consistency and specificity of neuroimaging data using meta-analysis. NeuroImage, Vol.45 (No.1). S210-S221. doi:10.1016/j.neuroimage.2008.10.061 ISSN 1053-8119.

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Official URL: http://dx.doi.org/10.1016/j.neuroimage.2008.10.061

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Abstract

Making sense of a neuroimaging literature that is growing in scope and complexity will require increasingly sophisticated tools for synthesizing findings across studies. Meta-analysis of neuroimaging studies fills a unique niche in this process: It can be used to evaluate the consistency of findings across different laboratories and task variants, and it can be used to evaluate the specificity of findings in brain regions or networks to particular task types. This review discusses examples, implementation, and considerations when choosing meta-analytic techniques. It focuses on the multilevel kernel density analysis (MKDA) framework, which has been used in recent studies to evaluate consistency and specificity of regional activation, identify distributed functional networks from patterns of co-activation, and test hypotheses about functional cortical-subcortical pathways in healthy individuals and patients with mental disorders. Several tests of consistency and specificity are described.

Item Type: Journal Article
Subjects: Q Science > QA Mathematics
R Medicine > R Medicine (General)
R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry
Divisions: Faculty of Science, Engineering and Medicine > Science > Statistics
Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group)
Library of Congress Subject Headings (LCSH): Brain -- Imaging -- Data processing, Magnetic resonance imaging -- Data processing, Tomography, Emission -- Data processing, Meta-analysis
Journal or Publication Title: NeuroImage
Publisher: Elsevier
ISSN: 1053-8119
Official Date: March 2008
Dates:
DateEvent
March 2008Published
Volume: Vol.45
Number: No.1
Number of Pages: 12
Page Range: S210-S221
DOI: 10.1016/j.neuroimage.2008.10.061
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Funder: National Science Foundation (U.S.) (NSF), National Institute of Mental Health (U.S.) (NIMH)
Grant number: SES631637 (NSF), R01MH076136 (NIMH)

Data sourced from Thomson Reuters' Web of Knowledge

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