Visualising connectivity results on a brain surface

1

Dear all,

I am trying to visualise intersubject functional connectivity correlation results on the brain surface.
Here is what I have done so far.

I have extracted the BOLD timeseries for all subjects from all ROIs of the AAL atlas. I am using to use Precuneus as my seed region which gives me an array of 116 correlation values (after averaging across subjects).

Now I want to plot these values on a brain surface. Both my data and the atlas are on the same MNI dimension. I do not want to plot it as nodes and edges but visualise it as a stat-map.

I have tried using other atlases but I am stuck at the same point.
I have also tried using https://sidchop.shinyapps.io/braincodepy/, but it doesn’t have aal in its datasets.

I am using nilean and python.

Any pointers would be really helpful!! Thank you in advance

2

Hi,
Using Nilearn, you can create an image (a volume) of the per-region connectivity to the seed you picked, and then project this image to the fsaverage5 surface, a use case that is well illustrated in Nilearn examples.
Ideally, if you want to plot results on the surface, you hshould also run the analysis on the cortical surface.
HTH,
Bertrand

3

Dear Bertrand,

Thank you for your reply…

Sorry for the late reply. I wanted to carry out the analyses in the volume and plot it as a stat map. I achieved this by computing the connectivity between the ROI-seed timeseries with all voxels and then plotted it using stat_map.

But thank you for your suggestion

4

Well, you can rely on the plot_img_on_surf function in Nilearn:

HTH,
Bertrand