surface_to_parcel ROI labels

[araikes]

Hi @saratheriver

Can you clarify something for me? I was using my own data and following the examples for surface_to_parcel using aparc_fsa5. The output I get from that has 71 values whereas I would expect 68 parcels. Likewise schaefer_100_fsa5 has 101, rather than 100.

I assume the first value to be unparcellated areas (label = 0), but for aparc_fsa5, what are the extra 2 values and are they on the front end or back end of the data? Would it be possible for surface_to_parcel to have the ROI label names for export to CSV?

[saratheriver]

Hello @araikes,

The aparc parcellation has 71 values - in ENIGMA they remove the midline mask and both corpus callosum.

If you do:

from enigmatoolbox.utils import parcel_to_surface, surface_to_parcel
a = parcel_to_surface(np.ones(68,), 'aparc_fsa5')
b = surface_to_parcel(a, 'aparc_fsa5')

You can see where the extra values are being added. And if plot them on the surface you'll see where they are on the brain as they will have a value of 0.

As for the labels, the only function that we have currently is as follows:

from enigmatoolbox.datasets import load_fc
_, labels, _, _ = load_fc(parcellation='aparc')

Please note however these labels do not include the midline mask nor the CC (for aparc).

Hope this helps,

Sara.