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.
Thanks a lot
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?
We have a tentative action plan that may yield reasonable results.
- Combine all 231 masks into (the mask of interest and the 230 control masks) one.
- Identify all studies that report at least one peak in the combined mask.
- Identify all studies that report at least one peak in the target lesion. This becomes the test Dataset.
- Extract XYZ coordinates from the selected studies.
- Use these XYZ coordinates as the
xyz parameter to a SCALE, with the Dataset being analyzed being the single-lesion test Dataset.
I’ll write up some pseudo code to make the steps clearer.
!!! Ohhhh my good lord, you guys are genius. Thank you very much.