Raduà Castaño, JoaquimMataix-Cols, DavidPhillips, Mary L.El-Hage, WissamKronhaus, Dina M.Cardoner, NarcísSurguladze, Simon2026-01-302026-01-302012-11-011778-3585https://hdl.handle.net/2445/226468Meta-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.22 p.application/pdfengcc-by-nc-nd (c) Elsevier Masson SAS, 2012https://creativecommons.org/licenses/by-nc-nd/4.0/Mapes estadísticsPotenciometriaMetamatemàticaStatistical mapsPotentiometryMetamathematicsinfo:eu-repo/semantics/article2026-01-20info:eu-repo/semantics/openAccess944478121658917