I have an issues finding the most optimal way of analyzing this. I have a Lesion mask (L1) and a whole set of control lesion (n=230). I want to compare L1-MACM map against the whole set of 230 MACM maps. Do you have any ideas how to do so? I’m wondering if the 230 MACM maps could be used a a null-distribution? I know SCALE but it’s computationally expensive given the 230 maps.

Can I get a couple more details about your analysis?

What database are you using to run the MACM? (e.g., neurosynth, neuroquery, an internal dataset of studies with certain criteria such as every study is related to some psychiatric illness such as depression?)

What question are you trying answer? Is the null hypothesis that the MACM for lesion mask (L1) is not detectably different from the other 230 MACMs for the other 230 lesion masks?

It’s an internal dataset of studies on a specific disorder >300 experiments

I really just want to get voxelwise map showing differences in MACM between L1 and the other 230. The null hypothesis would be that the MACM for lesion mask (L1) is not detectably different from the other MACMs lesion masks (n=230, as a whole set, each lesion mask are different in terms of location and size).