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Thanks for your reply. The conjunction method that you have recommended seems to be the most accepted in the literature, but my question is regarding the principle in this technique. In this method, we are not doing any statistical analysis to estimate the degree of overlap and merely looking at the common regions. Is there any method by which we can get a statistical heat map representing the degree of overlap between the different conditions. Thanks in advance, Atesh > (1) I would run 3 one-sample t-tests, one for each condition. > (2) I would threshold each condition and save the map of significant > voxels. > (3) I would convert each of those to a binary image using imcalc (i1>0). > (4) I would then create a combined image using imcalc (i1+2.*i2+4.*i3) > from > the binary value images. > > Voxels with a 7 are sig. in all 3 conditions, 6 are sig. in conditions > 2&3, > 5 are sig. in conditions 1&3, 4 is sig. in condition 3, 3 are sig. in > conditions 1 and 2, 2 is sig. in condition 2, and 1 is sig. in condition > 1. > > > > Best Regards, Donald McLaren > ================= > D.G. McLaren, Ph.D. > Research Fellow, Department of Neurology, Massachusetts General Hospital > and > Harvard Medical School > Postdoctoral Research Fellow, GRECC, Bedford VA > Website: http://www.martinos.org/~mclaren > Office: (773) 406-2464 > ===================== > This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED > HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is > intended only for the use of the individual or entity named above. If the > reader of the e-mail is not the intended recipient or the employee or > agent > responsible for delivering it to the intended recipient, you are hereby > notified that you are in possession of confidential and privileged > information. Any unauthorized use, disclosure, copying or the taking of > any > action in reliance on the contents of this information is strictly > prohibited and may be unlawful. If you have received this e-mail > unintentionally, please immediately notify the sender via telephone at > (773) > 406-2464 or email. > > > > On Sun, Jul 8, 2012 at 2:16 AM, Atesh Koul <[log in to unmask]> wrote: > >> Dear all, >> >> I have a fairly simple question but have got a bit confused with the >> different options people have suggested on the mailing list. I want to >> do >> a conjunction analysis and find regions which are common in three >> experiments. In my results, I want a heat map that represents the level >> of >> overlap between the three experiments. However, reading through some of >> the approaches that people have suggested on the mailing list, I have >> come >> up with more than one ways to do this. I would like to know which >> approach >> is better and would give me correct results: >> >> 1. Inclusive masking: I select Results from one experiment, then use >> inclusive masking using a thresholded t-map and see the regions common >> in >> the two experiments. Then use this t-map to mask my result from third >> experiment. (In this case however, I have found that the regions depend >> slightly on which experiments' results you use first and the heat map is >> not an indication of extent of overlap) >> >> 2. Use Imcalc to mask two t-maps and get the results. (In this case as >> well, heat map is not an indication of extent of overlap). >> >> 3. Using single contrasts: I take only the single condition contrasts >> (use >> a contrast vector 1 0 0 etc.) for all participants, take it to group >> level >> for all conditions and experiments, then run a random effects analysis >> on >> them (an approach I am not familiar with). >> >> I would highly appreciate any help in this regard. >> >> >> Atesh Koul >> Graduate student, >> National Brain Research Centre, India >> >