Note
This page is a reference documentation. It only explains the function signature, and not how to use it. Please refer to the user guide for the big picture.
nilearn.datasets.fetch_coords_seitzman_2018¶
- nilearn.datasets.fetch_coords_seitzman_2018(ordered_regions=True)[source]¶
Load the Seitzman et al. 300 ROIs.
These ROIs cover cortical, subcortical and cerebellar regions and are assigned to one of 13 networks (Auditory, CinguloOpercular, DefaultMode, DorsalAttention, FrontoParietal, MedialTemporalLobe, ParietoMedial, Reward, Salience, SomatomotorDorsal, SomatomotorLateral, VentralAttention, Visual) and have a regional label (cortexL, cortexR, cerebellum, thalamus, hippocampus, basalGanglia, amygdala, cortexMid).
See Seitzman et al.[1].
Added in version 0.5.1.
- Parameters:
- ordered_regions
bool, default=True ROIs from same networks are grouped together and ordered with respect to their locations (anterior to posterior).
- ordered_regions
- Returns:
- data
sklearn.utils.Bunch Dictionary-like object, contains:
‘rois’:
pandas.DataFramewith the coordinates of the 300 ROIs in MNI space.- ‘radius’:
numpy.ndarrayofint Radius of each ROI in mm.
- ‘radius’:
- ‘networks’:
numpy.ndarrayofstr Names of the corresponding network for each ROI.
- ‘networks’:
- ‘regions’:
numpy.ndarrayofstr Names of the regions.
- ‘regions’:
- ‘description’
str Description of the dataset.
- ‘description’
- data
References