Cross-hemispheric Euclidean distance w/ SurfDist

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1

Hello,

I want to find the Euclidean distance between a node in one hemisphere and the location of every surface node in both hemispheres.

For example, for node 105 in the left hemisphere, I want to know how far this is from every node in the right hemisphere and left hemisphere of the pial surface. I am using this command:


SurfDist -I std.141.${hemisphere}.pial.gii -from_node 105L -input nodes.1D -Euclidean

Nodes.1D is a list of number [0,198812). When $hemisphere is set to “lh” vs. “rh”, I get different output distances, but I am concerned that the function is ignoring the L in “from_node 105L” and just looking at the distances between node 105 to every other node within each hemisphere’s surface. How can I find euclidean distances across the hemisphere?

Thanks!

2

Hi-

For SurfDist, I don’t think you can find cross-hemispheric distances. Each hemisphere is a separate mesh. There isn’t a principled way to “hop” between meshes, as far as I know.

To calculate distances between nodes within a given hemisphere is doable. Here is an AFNI Academy video playlist about calculating distances between/among nodes, part of the SUMA playlist (there are links to scripts if you expand the section just below the video):
https://www.youtube.com/watch?v=XEQqz9EKVhE&list=PL_CD549H9kgqSs51SCNZQ4q57IguXvFI8&index=7

–pt

3

While it’s hard to say how one might come up with a geodesic distance, you can compute a euclidean distance pretty simply. It’s just a distance between two xyz coordinates with sqrt((x1-x2)^2+(y1-y2)^2+(z1-z2)^2). You only need to put the coordinates of interest into a file for each surface.

If you want all distances between every pair, then use 1d_tool.py -show_distmat. This works well for a reasonably short list of coordinates.
https://afni.nimh.nih.gov/afni/community/board/read.php?1,167419,167422#msg-167422

You can get the coordinates for each surface, and then compute distances from selected ones to the other. Extract surface node coordinates in the ways shown here:
https://afni.nimh.nih.gov/afni/community/board/read.php?1,160172,160183#msg-160183

4

Ah, I see, I misread the question; it isn’t concerned with distance constrained along the surface mesh, just the “as a crow flies”* distance between two points ?

–pt

  • NB: this is not a recommendation to have birds fly within someone’s cortex.
5

That’s right. It is a fairly simple problem. Just to make this a little simpler, here is an example of one way to compute the euclidean distance within AFNI. The distance is computed pairwise from two 1D text files each with 3 columns of x,y,z coordinates. You would have to duplicate the rows in one of these files to find distance to a single xyz coordinate.

create some sample coordinates

echo “1 2 3” > testxyz1.1D
echo “3 2 3” > testxyz2.1D

compute distance between each pair

1deval -a testxyz1.1D’[0]’ -b testxyz1.1D’[1]’ -c testxyz1.1D’[2]’
-d testxyz2.1D’[0]’ -e testxyz2.1D’[1]’ -f testxyz2.1D’[2]'.
-expr ‘sqrt((a-d)^2 + (b-e)^2 + (c-f)^2)’ |& tee dist_crow.1D
2

6

Thanks for the help! I ended up using “SurfMeasures -func coord_A” to retrieve the coordinates for every node in both hemispheres. Then, I wrote a python script to find all of the Euclidean distances that I needed. I appreciate your responsiveness.