The last few steps for creating beta series correlation maps is practically identical to what we did before with other functional connectivity maps:

1. Load your beta series map into the AFNI interface and set it as the underlay;

2. Click on "Graph" to scroll around to different voxels and examine different timeseries;

3. Once you find a voxel in a region that you are interested in, write out the timeseries by clicking FIM -> Edit Ideal -> Set Ideal as Center; and then FIM -> Edit Ideal -> Write Ideal to 1D File. (In this case, I am doing it for the right motor cortex, and labeling it RightM1.1D.)

4. Note that you can also average the timeseries within a mask defined either anatomically (e.g., from an atlas), or functionally (e.g., from a contrast). Again, the idea is the same as what we did with previous functional connectivity analyses.

5. Use 3drefit to trick AFNI into thinking that your beta series map is a 3d+time dataset (which by default is not what is output by 3dbucket):

3drefit -TR 2 Left_Betas+tlrc

6. Use 3dfim+ to create your beta series correlation map:

3dfim+ -input Left_Betas+tlrc -polort 1 -ideal_file RightM1.1D -out Correlation -bucket RightM1_BetaSeries

7. Convert this to a z-score map using Fisher's r-to-z transformation:

3dcalc -a Corr_subj01+tlrc -expr 'log((1+a)/(1-a))/2' -prefix Corr_subj01_Z+tlrc

8. Do this for all subjects, and use the results with a second-level tool such as 3dttest++.

9. Check the freezer for HotPockets.

That's it; you're done!

1. Load your beta series map into the AFNI interface and set it as the underlay;

2. Click on "Graph" to scroll around to different voxels and examine different timeseries;

3. Once you find a voxel in a region that you are interested in, write out the timeseries by clicking FIM -> Edit Ideal -> Set Ideal as Center; and then FIM -> Edit Ideal -> Write Ideal to 1D File. (In this case, I am doing it for the right motor cortex, and labeling it RightM1.1D.)

4. Note that you can also average the timeseries within a mask defined either anatomically (e.g., from an atlas), or functionally (e.g., from a contrast). Again, the idea is the same as what we did with previous functional connectivity analyses.

5. Use 3drefit to trick AFNI into thinking that your beta series map is a 3d+time dataset (which by default is not what is output by 3dbucket):

3drefit -TR 2 Left_Betas+tlrc

6. Use 3dfim+ to create your beta series correlation map:

3dfim+ -input Left_Betas+tlrc -polort 1 -ideal_file RightM1.1D -out Correlation -bucket RightM1_BetaSeries

7. Convert this to a z-score map using Fisher's r-to-z transformation:

3dcalc -a Corr_subj01+tlrc -expr 'log((1+a)/(1-a))/2' -prefix Corr_subj01_Z+tlrc

8. Do this for all subjects, and use the results with a second-level tool such as 3dttest++.

9. Check the freezer for HotPockets.

That's it; you're done!