This is an update of Gem12 for SPM99, originally by Stefan Kiebel.
> Is it possible to instruct spm99 to search all voxels within a given > mask image rather than all above a fixed or a %mean threshold? Yes, with SPM2 it's possible to use several masking options. To recap, there are 3 sorts of masks used in SPM2: 1. an analysis threshold 2. implicit masking 3. explicit masking 1: One can set this threshold for each image to -Inf to switch off this threshold. 2: If the image allows this, NaN at a voxel position masks this voxel from the statistics, otherwise the mask value is zero (and the user can choose, whether implicit masking should be used at all). 3: Use mask image file(s), where NaN (when image format allows this) or a non-positive value masks a voxel. On top of this, SPM automatically removes any voxels with constant values over time. So what you want is an analysis, where one only applies an explicit mask. In SPM2 for PET, you can do this by going for the Full Monty and choosing -Inf for the implicit mask and no 0-thresholding. Specify one or more mask images. (You could also define a new model structure, controlling the way SPM for PET asks questions). With fMRI data/models, SPM2 is fully capable of doing explicit masking, but the user interface for fMRI doesn't ask for it. One way to do this type of masking anyway is to change the SPM.mat file *after* you specify your model, but *before* clicking 'Estimate'. Specifically: 1. Load the SPM.mat file, load SPM set the SPM.xM.TH values all to -Inf, SPM.xM.TH = -Inf*SPM.xM.TH; and, in case that you have an image format not allowing NaNs, set SPM.xM.I to 0 SPM.xM.I = 0; 2. If using a mask image, set SPM.xM.VM to a vector of structures, where each structure element is the output of spm_vol. For instance: SPM.xM.VM = spm_vol('Maskimage'); 3. Finally, save by save SPM SPM