Dear AFNI experts,
I got outputs from 3dNetCorr and would like to do group analyses. To my best understanding, fat_mvm_prep.py and fat_mvm_scripter.py should be used to perform group analysis. Could you please let me know if I understand correctly or if there is any other option to conduct group analyses for the 3dNetCorr outputs?
To my best understanding, fat_mvm_prep.py and fat_mvm_scripter.py should be used to perform group analysis.
Yes, I believe that you can use those programs. Another alternative is RBA (https://afni.nimh.nih.gov/pub/dist/doc/program_help/RBA.html).
Thank you for the suggestion. I took a look at both the RBA and MBA pages including your youtube instruction (https://www.youtube.com/watch?v=K2nW8M3sYNY), which were very helpful.
Could I ask follow-up questions?
- I am interested in performing within and between network analysis so I assume I need to use MBA?
- More specifically, I have several ROIs from each network. On the MBA page, all the examples have two ROIs. If I would like to have more than two ROIs (for example five ROIs from network #1), could you please let me know how the txt file should look like?
I am interested in performing within and between network analysis so I assume I need to use MBA?
Could you describe the data structure? How many ROIs do you have? For each subject, do you have a full (and symmetric) matrix for those ROIs or do you have missing data for the matrix? What do you mean by “within and between network analysis”?
Sorry for the confusion. So I used coordinates from Power et al. 2011 (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3222858/) to create nodes for the default mode network, salience network, and frontoparietal network based on resting-state functional data which were collected for both pre- and post-intervention. The default mode network has 59 ROIs, salience network 18 ROIs, and frontoparietal network 25 ROIs (so 102 ROIs in total). I ran 3dNetCorr using these ROIs and have a full and symmetric matrix (z score) for these ROIs (102 x 102) for each subject. Within network means averaging z score between the same network - for example, z score between ROI #1 to # 59 for the default mode network. Between network means averaging z score between different network - for example, z score between the default mode network nodes and salience network nodes.
Please let me know if you need more infromation.
It would be interesting to try out MBA and see how it performs.
On the MBA page, all the examples have two ROIs.
Practically the modeling approach with MBA can take a few up to 100 regions. Those two columns in the help are meant to indicate the two regions for each region pair (matrix element), not the number of regions allowed.
have a full and symmetric matrix (z score) for these ROIs (102 x 102) for each subject
With about 100 ROIs, use the option -WCP to speed up the computation.