SurfClust Question

AFNI Message Board
1

Hi there,

I am an AFNI newbie and have exported a MEG source estimate time series into a GIFTI (using stc2gii_hack) and then have aligned that to the corresponding SUMA volume (following this tutorial here: Best practice to get NIML/GIfTI or NIfTI from STC - #2 by pmolfese - 💬 Support & Discussions - MNE Forum).

I am now looking to create spatial clusters from the source estimate data with SurfClust. I am specifically wondering if input dataset can be the output from this tutorial (a .niml.dset file) or if I will need to convert it to another form for use.

Thanks in advance for the help!

2

Howdy-

*.niml.dset files can be used with clustering. They contain information at nodes, values that can be thresholded, for example. You also need the information of the topology/relatedness of mesh nodes, which are contained in *.gii files or in groups of GII files, the latter of which can be loaded in with *.spec files.

From this Message Board question, here is an example call to SurfClust:

SurfClust                                     \
    -i      ./std.60.lh.smoothwm.gii          \
    -input  ./std.60.lh.thickness.niml.dset 0 \
    -rmm    -1.000000  \
    -thresh_col 0      \
    -athresh 3.580000  \
    -amm2 50.000000    \
    -sort_area         \
    -no_cent

… where the following are input: a dset (./std.60.lh.thickness.niml.dset, which is the dset that is thresholded (here at 3.58) + clusterized (here with NN=1, from ‘-rmm -1’)), which is overlaid on the “underlay” data set (std.60.lh.smoothwm.gii) that contains the mesh information, and the other options are described in the help file. Note how with the -input .. dset, you also specify which subvolume is used for clusterizing (even if there is only a single volume there, so you select the 0-th vol):

     -input inData.dset dcol_index: The input dataset
                                  and the index of the
                                  datacolumn to use
                                  (index 0 for 1st column).
                                  Values of 0 indicate 
                                  inactive nodes.

If your -input .. dset had more than one value per node (like a time series, for example), you could select a different subvolume from it for clusterizing.

–pt

2 Likes
4

Thank you very much @ptaylor !

I am wondering if there is a way to see which nodes belong to which clusters when you use the -out_fulllist parameter. I want to preserve the row-to-node correspondence since I'll be comparing across multiple datasets, but want to know if I can tell nodes apart by their specific cluster. I thought the -out_roidset parameter does something like this, but that doesn't seem to be the case...

Many thanks!

5

Nodes are recorded for each cluster in the out_roidset dataset - nodes in Cluster 1 get a value of 1, cluster 2 get a value of 2 at every node and so on ....

Add the -out_roidset and the -prefix option to Paul's example command to name the output.


SurfClust                                     \                                                                      
    -i      ./std.60.lh.smoothwm.gii          \
    -input  ./std.60.lh.thickness.niml.dset 0 \
    -rmm    -1.000000  \
    -thresh_col 0      \
    -athresh 3.580000  \
    -amm2 50.000000    \
    -sort_area         \
    -no_cent -out_roidset -prefix surfclust_thick

There are two new output files. You can visualize the clusters in suma.

image
image1200×830 91.2 KB

On the command line, you can see the cluster report (a simple text file) with

cat surfclust_thick_ClstTable_e1_a50.0.1D

image
image1920×572 168 KB

You can see all nodes in any or some of the clusters with 3dmaskdump. The mrange is an option to limit to only a particular range of cluster values in the mask (here limiting to just cluster 2). The output shows i j k indices for the mask values, but only the i index is useful for surface mesh nodes.

3dmaskdump -quiet -mrange 2 2                       \
   -mask surfclust_thick_ClstMsk_e1_a50.0.niml.dset \
             surfclust_thick_ClstMsk_e1_a50.0.niml.dset

1047 0 0 2

1048 0 0 2

1049 0 0 2

1050 0 0 2

1051 0 0 2

1052 0 0 2

1053 0 0 2

1054 0 0 2