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A new meta-analytic method for neuroimaging studies that combines reported peak coordinates and statistical parametric maps

Published online by Cambridge University Press:  11 June 2011

J. Radua
Affiliation:
Department of psychosis Studies, institute of psychiatry, King's College London, PO 69, London, SE5 8AF, UK FIDMAG, CIBERSAM, Sant Boi de Llobregat, Spain
D. Mataix-Cols
Affiliation:
Department of psychosis Studies, institute of psychiatry, King's College London, PO 69, London, SE5 8AF, UK
M.L. Phillips
Affiliation:
Department of psychiatry, western psychiatric institute and clinic, university of Pittsburgh school of medicine, Pittsburgh, USA Department of psychological medicine, Cardiff university school of medicine, Cardiff, UK
W. El-Hage
Affiliation:
Inserm U930 ERL CNRS 3106, université François-Rabelais, Tours, France
D.M. Kronhaus
Affiliation:
Cygnet Health Care, UK
N. Cardoner
Affiliation:
Despartment of psychiatry, Bellvitge university hospital-IDIBELL, CIBERSAM, Barcelona, Spain
S. Surguladze
Affiliation:
Department of psychosis Studies, institute of psychiatry, King's College London, PO 69, London, SE5 8AF, UK Cygnet Health Care, UK
Corresponding
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Abstract

Meta-analyses are essential to summarize the results of the growing number of neuroimaging studies in psychiatry, neurology and allied disciplines. Image-based meta-analyses use full image information (i.e. the statistical parametric maps) and well-established statistics, but images are rarely available making them highly unfeasible. Peak-probability meta-analyses such as activation likelihood estimation (ALE) or multilevel kernel density analysis (MKDA) are more feasible as they only need reported peak coordinates. Signed-differences methods, such as signed differential mapping (SDM) build upon the positive features of existing peak-probability methods and enable meta-analyses of studies comparing patients with controls. In this paper we present a new version of SDM, named Effect Size SDM (ES-SDM), which enables the combination of statistical parametric maps and peak coordinates and uses well-established statistics. We validated the new method by comparing the results of an ES-SDM meta-analysis of studies on the brain response to fearful faces with the results of a pooled analysis of the original individual data. The results showed that ES-SDM is a valid and reliable coordinate-based method, whose performance might be additionally increased by including statistical parametric maps. We anticipate that ES-SDM will be a helpful tool for researchers in the fields of psychiatry, neurology and allied disciplines.

Type
Original articles
Copyright
Copyright © European Psychiatric Association 2012

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