Hello, does anyone know if its possible to convert a 3d+T bold image into a 2d+T flat map?
basically, i want a flat map time series, instead of a volume time series.
i have some experience with SUMA and freesurfer, but i couldn’t find any easy way to do this…i’ve mostly just used these tools to visualize 3d correlation maps on the inflated surface.
i assume its possible however, because people do surface smoothing.
i’m trying a new approach to the deep image reconstruction database on openneuro, maybe a 2d convnet directly from flat map to image space.
I actually just replied to your NeuroStars question about this earlier today (sorry for the delay); I am posting the content here, as well.
You can use afni_proc.py to include projection onto your FreeSurfer-generated surface as part of your EPI+anatomical processing. This is done by including the “surf” block in afni_proc.py. Your final output stats from your GLM model are then surface dsets; these would give you your “2D+t” maps of EPIs on the surface (fitts* and errts* files), as well as your stats dset output on the surface.
Examples of this are included in the AFNI Bootcamp demos and lectures; you can see AFNI_data6/FT_analysis/s03.ap.surface, which is also Example 8 in the afni_proc.py help:
There is also a video lecture of teaching this in a Bootcamp here:
… with lectures 24-28 talking about SUMA usage in general, and lectures 26 (starting at about 29:00) through 28 talking about doing the surface projection with afni_proc.py explicitly.
In the AFNI Academy YouTube channel:
… a set of SUMA-related lectures will also be up soon.