Get proportion of each voxel that exists within a named ROI (this constitutes a probability map for the ROI, with values ranging from 0-1). Plot this probablistic roi mask onto a flatmap.

In order for this to work, the specified ROI must exist in the overlays.svg file in the pycortex filestore for this subject.

Out:

Found 100.00% of EBA
Cutting 0 overlapping voxels (should be < ~50)
Generating a flatmap cache


import cortex
import matplotlib.pyplot as plt

subject = "S1"
roi = "EBA"

# Get the map of which voxels are inside of our ROI
roi_list=[roi],
gm_sampler='cortical-conservative', # Select only voxels mostly within cortex
split_lr=False, # No separate left/right ROIs
threshold=None, # Leave roi mask values as probabilites / fractions
return_dict=True
)

# Plot the mask for one ROI onto a flatmap
vmin=0, # This is a probability mask, so only
vmax=1, # so scale btw zero and one
cmap="inferno", # For pretty
)

cortex.quickflat.make_figure(roi_data,
thick=1, # select a single depth (btw white matter & pia)
sampler='nearest', # no interpolation
with_curvature=True,
with_colorbar=True,
)

plt.show()


Total running time of the script: ( 0 minutes 9.668 seconds)

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