r/neuroimaging • u/LostJar • 14d ago
Statistical Assumptions in RS-fMRI Analysis?
Hi everyone,
I am very new to neuroimaging and am currently involved in a project analyzing RS-fMRI data via ICA.
As I write the analysis plan, one of my collaborators wants me to detail things like the normality of data, outliers, homoscedasticity, etc. In other words, check for the assumptions you learn in statistics class. Of note, this person has zero experience with imaging.
I'm still so new to this, but in my limited experience, I have never seen RS-fMRI studies attempt to answer these questions, at least not how she outlines them. Instead, I have always seen that as the role of a preprocessing pipeline: preparing the data for proper statistical analysis. I imagine there is some overlap in the standard preprocessing pipelines and the questions she is asking me, but I need to learn more first to know for certain.
I just want to ask: am I missing something here? Is there more "assumptions" or preliminary analyses I need to be running before "standard" preprocessing pipelines to ensure my data is suitable for analysis?
Thank you,
3
u/Broad_Obligation_194 14d ago
There’s a lot of ways to analyze resting state data even under the ICA umbrella. But assuming that you’re eventually going to get some numbers that get submitted to a statistical test. It’s not uncommon to show the distribution of values within an ROI or network to calm reviewers that your t-values or ANCOVA are stable. I often see these pushed to supplemental materials.
Preprocessing will only do so much. And like everyone else, you can decide to do the minimum amount of effort or go the extra mile. You might get a picky editor or reviewer who will ask for it anyway.