I’m attempting to use SUMA to visualize the results of a few analyses, including 3dANOVA3 and 3dLME. This issue that I am running into is that the statistical results being projected into SUMA do not appear to display the gradient of t values as it does in the AFNI images.
For example, I have several GLT contrasts in the ANOVA bucket file. After setting the t-stat from a contrast as an overlay and also the threshold (using color scheme #12), I get a gradient of negative t values that go from dark blue to lighter blue in areas as expected (the image is attached here displaying this). However, the issue occurs when I then link AFNI to SUMA; in the SUMA window, the results are now two static colors that do not show the variation in t-values across regions (see attached image). Changing the overlay to the contrast and then thresholding by the t-stat does not change things.
The only exception to this issue is that when overlaying the one “diff” specified in the ANOVA command and then thresholding it by its t-stat, it does display properly. I don’t know if this is related, but turning off “autoRange” yields the same dichotomous colorization in AFNI as is being displayed in SUMA. However, for all of the contrasts specified SUMA will only display the dichotomous colors.
Here is my ANOVA script if it helps:
#!/bin/csh -f set top_dir = /Volumes/netapp/Myerslab/Dave/Cthulhu/data # For this analysis, both groups are treated equally # a levels = SoundType; 1=Sine, 2=Vowel # b levels = Continuum Point: 1=step1, 2=step3 3=step5 4=step7 # for sine, =sinestep1; =sinestep3; =sinestep5; =sinestep7; # for vowel, =vowelstep1; =vowelstep3; =vowelstep5; =vowelstep7; cd /Volumes/netapp/Myerslab/Dave/Cthulhu/data 3dANOVA3 -type 4 \ -mask $top_dir/group/group_mask+tlrc \ -alevels 2 \ -blevels 4 \ -clevels 26 \ -dset 1 1 1 cth1/cth1.preproc/'stats.1+tlrc' \ .... many datasets abridged for readability \ -amean 1 Sine \ -amean 2 Vowel \ \ -bmean 1 step1 \ -bmean 2 step3 \ -bmean 3 step5 \ -bmean 4 step7 \ \ -fab SoundTypebyContinuumStep \ \ -adiff 2 1 Vowel-Sine \ \ -bcontr -0.5 0.5 0.5 -0.5 Boundary-Endpoint \ -Abcontr 1 : -0.5 0.5 0.5 -0.5 SINE_Boundary-Endpoint \ -Abcontr 2 : -0.5 0.5 0.5 -0.5 VOWEL_Boundary-Endpoint \ \ -bucket SoundTypebyContinuumStepANOVA
I appreciate any insight that can be provided. Thank you in advance!