Making a surface plot of a 3D statistical map

In this example, we will project a 3D statistical map onto a cortical mesh using vol_to_surf, display a surface plot of the projected map using plot_surf_stat_map with different plotting engines, and add contours of regions of interest using plot_surf_contours.

Get a statistical map

from nilearn import datasets

motor_images = datasets.fetch_neurovault_motor_task()
stat_img = motor_images.images[0]

Get a cortical mesh

fsaverage = datasets.fetch_surf_fsaverage()

Sample the 3D data around each node of the mesh

from nilearn import surface

texture = surface.vol_to_surf(stat_img, fsaverage.pial_right)

Plot the result

You can visualize the texture on the surface using the function plot_surf_stat_map which uses matplotlib as the default plotting engine:

from nilearn import plotting

fig = plotting.plot_surf_stat_map(
    fsaverage.infl_right, texture, hemi='right',
    title='Surface right hemisphere', colorbar=True,
    threshold=1., bg_map=fsaverage.sulc_right
)
fig.show()

Interactive plotting with Plotly

If you have a recent version of Nilearn (>=0.8.2), and if you have plotly installed, you can easily configure plot_surf_stat_map to use plotly instead of matplotlib:

engine = 'plotly'
# If plotly is not installed, use matplotlib
try:
    import plotly.graph_objects as go  # noqa: F401
except ImportError:
    engine = 'matplotlib'

print(f"Using plotting engine {engine}.")

fig = plotting.plot_surf_stat_map(
    fsaverage.infl_right, texture, hemi='right',
    title='Surface right hemisphere', colorbar=True,
    threshold=1., bg_map=fsaverage.sulc_right,
    engine=engine  # Specify the plotting engine here
)
fig.show()  # Display the figure as with matplotlib figures

Using plotting engine plotly.
/home/yasmin/nilearn/nilearn/nilearn/plotting/js_plotting_utils.py:81: UserWarning: vmin cannot be chosen when cmap is symmetric
  warnings.warn('vmin cannot be chosen when cmap is symmetric')