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An alternative approach: Save the thresholded maps. Then use the following equation in imcalc: (i1>0)+2*(i2>0) This will show you where significant clusters are located for the 2 groups and where the clusters overlap. On Mon, Dec 2, 2013 at 2:31 PM, Colin Hawco <[log in to unmask]> wrote: > Hah, SPM does so many strange things! > > I don't have a script for this, but I can give you the code to use. You > need to generate t-maps separately for each contrast. Then, lets call the > first contrast FileA, and the second FileB. > > %masks file B with A, and output t-value from fileB, butonly for voxels > overlapping with significant voxels in FileA. Note that an extent threshold > is not applied. > fileA = 'spmT_0001.img' %for example > fileB = 'spmT_0002.img' %for example again > > v=spm_vol(fileA) > data = spm_read_vols(v); > > v2= spm_vol(fileB) > data2 = spm_read_vols(v2); > t_thresh = 3.5 %% significant t-stat threshold, change as needed > data2(data<=t_thresh) = 0; > > v2.fname = 'spmt_conjunction.img' %renames the output file > spm_write_vol(v2, data2) > %% done > > > Now, here is a trick I think should work. If you load the SPM.mat file and > rename the name of the T-map, it will then load this image into SPM results > and you can get the activation tables, etc. > > SPM.xCon(1).Vspm.fname = 'spmt_conjunction.img' > > i am not 100% sure if that will work. Alternately if instead of changing > v2.fname you leave it the same, SPM should load the conjunction map if you > select the contrast from fileB. > > Let me know if you need a bit more help. > Colin > > > On 2 December 2013 13:55, M.Momenian <[log in to unmask]> wrote: > >> Dear Colin >> >> Thanks a lot for your kind reply. I ran the inclusive masking two times >> in the following order: once I inclusively masked A with B, and once B with >> A. The results were again different. They should be. You said inclusive >> masking is fit for "detecting things which are significant in both groups". >> I guess inclusive masking is putting all significant voxels from two >> contrasts together, rather than coming up with the ovarlap between the two >> contrasts. I am interested in the overlap in the two groups. I wonder if I >> can have your script written to detect the overlap as well. It would be so >> kind of you. >> >> Best wishes >> Mohammad >> >> >> On Monday, December 2, 2013 9:58 PM, Colin Hawco <[log in to unmask]> >> wrote: >> Hello Mohammed, >> >> I have never run a conjunction analysis in SPM, so I cannot directly >> address your issue. However, for what it is worth, I would prefer to use an >> inclusive masking approach, in which the results of one t-map are used to >> mask another, provided a masked conjunction of the results. I have used >> a similar approach in some of my work, but I wrote a script to find overlap >> rather than using SPM. This is a very valid form of conjunction analysis >> for detecting things which are significant in both groups. >> >> I also believe it is a very statistically robust approach to use >> inclusive masking, assuming the two analysis you are using are properly >> corrected for multiple comparisons. >> >> The reason your results are different between conjunction and masking is >> due to the nature of the "conjunction" analysis, which is a statistical >> approach. It attempts to find voxels where Beta A and Beta B are both not >> zero. However, it can potentially detect a conjunction in which the voxels >> from Beta B, while non-zero, do not survive statistical significance in an >> analysis of only Beta B. This may happen when Beta B is small and Beta A is >> very large. At least according to my admittedly limited understanding. >> >> So, my 2 cents, you can't go wrong using inclusive masking, a "masked >> conjunction". You know for sure that all voxels are significant in >> both contrasts. >> >> Colin. >> >> >> On 2 December 2013 11:49, M.Momenian <[log in to unmask]> wrote: >> >> Dear SPMers >> >> I just sent an email yesterday, but there was no answer. I know my >> question was simple. but I couldn't find a clear answer to the question. I >> read in SPM8 manual that if I want to see the effects which are common across >> the two groups in my study, I can either use inclusive masking or >> conjunction analysis. I did both of them, but the results are different. I >> also searched the list, but it did not soothe my confusion. I decided to >> write again and ask how I should solve this problem of mine. I want to see >> the brain activations which are common across my two groups in Task A. >> Then, I want to see these common areas in Task B across the two groups. >> Which method is more reliable? I highly appreciate your comments dear all. >> >> Reading you soon >> Mohammad >> >> >> >> >> >