Note
Go to the end to download the full example code.
Basic brain region properties
siibra makes no distinction between brain regions and region trees: Each Region object represents a subtree with a (possibly empty) set of child regions, and has a pointer to its parent region in the hierarchy. As mentioned before, Parcellation objects are also special regions, with no parent and additional functionalities. Consequently, the parcellation of a region can be accessed as the region’s “root” attribute (but “parcellation” is also provided as a shortcut property to this)
Start by importing the package.
import siibra
Let’s fetch the region from the Julich-Brain parcellation representing the primary visual cortex.
v1 = siibra.get_region('julich 2.9', 'v1')
The corresponding parcellation is just the root region:
print(v1.root)
print(v1.parcellation)
Julich-Brain Cytoarchitectonic Atlas (v2.9)
Julich-Brain Cytoarchitectonic Atlas (v2.9)
The primary visual cortex is part of the occipital cortex:
v1.parent
<Region(identifier='minds/core/parcellationatlas/v1.0.0/94c1125b-b87e-45e4-901c-00daee7f2579-290_OCCIPITAL_CORTEX', name='occipital cortex', species='Homo sapiens')>
It represents a subtree, with its children being the respective areas on each hemisphere:
Area hOc1 (V1, 17, CalcS)
├── Area hOc1 (V1, 17, CalcS) left
╰── Area hOc1 (V1, 17, CalcS) right
[<Region(identifier='minds/core/parcellationatlas/v1.0.0/94c1125b-b87e-45e4-901c-00daee7f2579-290_AREA_HOC1_V1_17_CALCS_LEFT', name='Area hOc1 (V1, 17, CalcS) left', species='Homo sapiens')>]
Total running time of the script: (0 minutes 0.649 seconds)
Estimated memory usage: 103 MB