Hi Alfonso,

I should note that I performed the preprocessing steps including denoising and smoothing outside conn in a custom in-house pipeline, then I imported the data into conn using batch scripting skipping preprocessing and denoising steps. In my preprocessing I used 3dBlurToFWHM smooting with a kernel size of 6mm.

Would this have caused problems for smoothing when importing into conn? I also have non-smoothed, denoised image files, should I have used these in the conn analysis and used smoothing in conn? If these do not work I will try nonparametrics.

I ran the second level as follows:

Subject effects: [AllSubjects behav age_mean_centered male female mean_fd], contrast = [0 1 0 0 0 0]
   Where behav is the outcome measure of interest (it is a continuous measures with a fairly small range between 1 and 10 and is not mean-centered); for the covariates, age has been mean centered, male and female are two binary indicators with values of 0 or 1 for being male or female (and vice versa), and mean_fd is the subject motion measure (not mean-centered since I think 0 is meaningful here indicating subjects without motion).

Conditions: Rest [1]

For Sources I entered my ROIs of interest and run a F-test contrast (eye(n)). I also tried running separate t-tests for each source ROI and bonferroni correct for the cluster FDR alpha-level, the resulting clusters are all small.

Thanks!