Hello, AFNI mindhive –

I’m currently analyzing a set of fMRI data and am running into some trouble implementing a gPPI analysis. My apologies in advance if a similar question has already been posted – I couldn’t find anything when I ran a search.

(Some background if it’s useful: We’ve got a 2x3 design, and we functionally defined seed regions based on sensitivity to the 2-level factor. We’re interested in examining functional connectivity differences as a function of the 3-level factor.)

I’ve worked through Gang Chen’s very helpful guide on implementing gPPI and have run my deconvolution analyses for each subject. Here’s where I’m having trouble:

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[li] I’m not sure whether to be running the ANOVA on the beta values or the r values. Step 6 of the guide says to output the r coefficient in the deconvolution because the r value will be used in the group analysis, but Step 7 says to run the group analysis on the beta coefficients.

[/li][li] Once I’ve run the ANOVA and identified regions whose functional connectivity to the seed varies based on the task, I’d like to get a sense of which conditions involve greater connectivity and which ones involve less. To do that, I assume I need to extract values from the regions using something like 3dmaskave and examine the pattern of activity. I’m unsure whether it would be appropriate to extract beta values or r values (and, if the latter, what sorts of conclusions I can draw from the values I extract).

[/li][/ul]

Any help you can provide would be incredibly helpful! I’m happy to provide more information if it would be helpful.

Thanks in advance!

Sahil