Dear CONN developers,
I’m writing to share an issue I ran into with CONN’s surface-based pipeline, in case it is useful for the documentation. I have since moved my analysis outside CONN, so I’m not asking for troubleshooting, only for clarification of the intended workflow.
I used CONN (25b) with SPM (25.01.02), MATLAB on Linux, to
preprocess and denoise surface-based resting-state data from 40
subjects with two sessions each, using longitudinal FreeSurfer
reconstructions. My analysis required time series from small
subject-specific surface ROIs: functional-localizer patches of
69-106 vertices and Wang atlas labels. All of them are FreeSurfer
.mgz files defined on each subject’s native surface
(123,674 vertices per hemisphere).
When I added these files as ROIs, I could not obtain usable time
series. The functional outputs (*.surf.nii) are [42 ×
83 × 94 × 210] volumes with no spatial transform that I could use
to relate native-surface ROIs to them. The sampling used for
surface ROIs also appeared far too sparse for ROIs of this size, on
the order of 1,000 points across the surface. CONN’s own atlas ROIs
extracted without problems.
The volume size may explain this. 42 × 83 × 94 = 327,684, which is exactly twice the 163,842 vertices of one fsaverage hemisphere. I therefore suspect that CONN’s surface data lives in fsaverage space and that surface ROIs are expected there, not on a subject’s native surface. If so, native-surface ROIs would be incompatible with the stored data by design.
Is this the intended workflow? If so, it would help users if the surface-analysis documentation stated which space and format ROI files must use, and whether subject-specific native-surface ROIs are supported. Such ROIs are common in visual neuroscience, for example with retinotopic atlases and functional localizers, so support for them would be a valuable feature.
The manual and tutorials present surface-based analysis as supported, which is why I expected this to work.
Thank you for the toolbox and for your time.
Best regards,
Yagmur