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

SDM exploration of the results

Multimodal meta-analyses

This procedure allows the combination of two meta-analyses of studies conducted in different modalities, e.g. VBM and fMRI.

To conduct a multimodal meta-analysis

Conduct the two unimodal (i.e. standard) meta-analyses separately.

Press the button [Multimodal]


Select [Multimodal] in the Statistics menu, to open the following dialog:

Dialog picture


Command-line and batch usage

multi probability map1, probability map2,

. . . maximum voxel probability, maximum peak probability, minimum number of voxels,

. . . assume error (0 or 1), best scenario (0 or 2), tolerable meta-analytic probabilities

Assuming error ('1') makes the analysis conservative, for what you may consider adjusting the p-values to the best scenario ('2'). This latter option means that the p-values will be more liberal, but the analysis is STILL an overlap (please see Radua et al 2013 for details). To avoid being too liberal, specify the tolerable p-values in the unimodal meta-analyses.


multi meta1, meta2, 0.00250, 0.00025, 10, 1, 2, 0.10000

Please note that you should have previously creted a folder and copied there "meta1" (a map of probabilities from the first meta-analysis) and "meta2" (a map of probabilities from the second meta-analysis).


(multimodal meta-analyses): Radua J, Romeo M, Mataix-Cols D and Fusar-Poli P. A general approach for combining voxel-based meta-analyses conducted in different neuroimaging modalities. Curr Med Chem 2013; 20:462-466. link .