Dear FSL experts,
I have a few questions regarding Melodic and dual regression:
I am looking at resting state network differences between patients and healthy controls using Melodic with 70 components (estimating the maps from the control subjects only) and dual regression to observe group differences.
In other studies there seem to be two different approaches to what components are used as input for the dual regression:
1. Use all ICs (including those identified as noise) for dual regression
2. Delete noise components and only use identified network ICs for further analysis
Can someone please explain what exactly the difference is between the two approaches? I.e. what difference does it make statistically if the noise components are included? Which one would you recommend to use in my case?
Any comments are very much appreciated!
Thanks,
Julia
|