Siibra mapping off by one

I want to use the newest julich atlas for functional connectivity analysis (newer as in nilearn)

import siibra
from nilearn.maskers import NiftiLabelsMasker

julich_mpm = siibra.get_map(space="icbm 2009c", parcellation="julich 2.9", maptype="labelled") 
mapimg_r = julich_mpm.fetch(fragment='right')

atlas_masker_rh = NiftiLabelsMasker(mapimg_r)
atlas_time_series_rh = atlas_masker_rh.fit_transform(func_filename)

The extracted atlas_time_series_rh has a shape of (#volumes, 147) and len(centroids.keys()) = 296 = 148 per hemisphere.

Wich region is missing in my time_series?

You may be able to check which regions are missing by using the labels_ attribute of the NiftiLabelsMasker → see the answers provided in this thread: Nilearn NiftiLabelsMasker returns less timecourses than labels (by more than 1...)

1 Like