SDM   Seed-based d Mapping
formerly "Signed Differential Mapping"
Share on Facebook:   Facebook

SDM preparation


This is the last step of the preparations, and it consists in, for peak coordinates studies, compute the images of the lower bounds and upper bounds of possible effect size for each voxel. For studies from which the raw image is available, the only step performed, when needed, is the conversion of the raw images to effect-size images.

To preprocess the studies

Press the button [Preprocessing]


Select [Preprocessing] in the Meta-analyses menu, to open the following dialog:

Preprocessing dialog


Please be aware that this will remove the previous meta-analysis in this folder.

A maximum and a minimum of each study will be written in a text file called pp.htm (note that these may not be the absolute maximum and minimum), and the recreated images will be separately saved in a set of NIfTI file called pp_(study).nii.gz, e.g. pp_Smith2000.nii.gz. These files are useful for checking that coordinates have been correctly read.

Several ?mm X ?mm X ?mm (where ? is one of the available voxel sizes, at the time of writing this text only 2mm X 2mm X 2mm) MNI-based masks and correlation templates are included in SDM software: gray matter (also usefull for fMRI and PET), white matter, fractional anisotropy, cerebrospinal fluid, brain and intracranial. Please contact should you need another mask or template.

Command-line and batch usage

pp correlation_template,degree_of_anisotropy,isotropic_fwhm,mask,voxel_size


pp fractional_anisotropy,0.8,20,white_matter,2


(current method): Albajes-Eizagirre A, Solanes A, Vieta E and Radua J. Voxel-based meta-analysis via permutation of subject images (PSI): Theory and implementation for SDM. NeuroImage 2019; 186:174. link

(effect-sizes and variances): Radua J, Mataix-Cols D, Phillips ML, El-Hage W, Kronhaus DM, Cardoner N and Surguladze S. A new meta-analytic method for neuroimaging studies that combines reported peak coordinates and statistical parametric maps. Eur Psychiatry 2012; 27:605–611. link .

(anisotropic kernels): Radua J, Rubia K, Canales-Rodriguez EJ, Pomarol-Clotet E, Fusar-Poli P and Mataix-Cols D. Anisotropic kernels for coordinate-based meta-analyses of neuroimaging studies. Front Psychiatry 2014; 5:13. link .

(white matter template:) Radua J, Via E, Catani M and Mataix-Cols D. Voxel-based meta-analysis of regional white-matter volume differences in autism spectrum disorder versus healthy controls. Psychol Med 2011; 41:1539-1550. link .

(TBSS preprocessing): Peters BD, Szeszko PR, Radua J, Ikuta T, Gruner P, DeRosse P, Zhang JP, Giorgio A, Qiu D, Tapert SF, Brauer J, Asato MR, Khong PL, James AC, Gallego JA and Malhotra AK. White matter development in adolescence: diffusion tensor imaging and meta-analytic results. Schizophrenia Bull 2012; 38:1308-1317. link .

(FreeSurfer template): Li Q, Zhao Y, Chen Z, Long J, Dai J, Huang X, Lui S, Radua J, Vieta E, Kemp GJ, Sweeney JA, Li F and Gong Q. Meta-analysis of cortical thickness abnormalities in medication-free patients with major depressive disorder. Neuropsychopharmacology 2019; in Press. link .