Note

This page is a reference documentation. It only explains the class signature, and not how to use it. Please refer to the user guide for the big picture.

nilearn.surface.SurfaceImage¶

class nilearn.surface.SurfaceImage(mesh, data)[source]¶

Surface image containing meshes & data for both hemispheres.

Parameters:

meshnilearn.surface.PolyMesh, or dict of nilearn.surface.SurfaceMesh, str, pathlib.Path: Meshes for the both hemispheres.
datanilearn.surface.PolyData, or dict of numpy.ndarray, str, pathlib.Path: Data for the both hemispheres.

Attributes:

shape(int, int): shape of the surface data array

__init__(mesh, data)[source]¶: Create a SurfaceImage instance.

classmethod from_volume(mesh, volume_img, inner_mesh=None, **vol_to_surf_kwargs)[source]¶

Create surface image from volume image.

Parameters:

meshnilearn.surface.PolyMesh or dict of nilearn.surface.SurfaceMesh, str, pathlib.Path: Surface mesh.
volume_imgNiimg-like object: 3D or 4D volume image to project to the surface mesh.
inner_meshnilearn.surface.PolyMesh or dict of nilearn.surface.SurfaceMesh, str, pathlib.Path, default=None: Inner mesh to pass to nilearn.surface.vol_to_surf.
vol_to_surf_kwargsdict[str, Any]: Dictionary of extra key-words arguments to pass to nilearn.surface.vol_to_surf.

Examples

>>> from nilearn.surface import SurfaceImage
>>> from nilearn.experimental.surface import load_fsaverage
>>> from nilearn.datasets import load_sample_motor_activation_image

>>> fsavg = load_fsaverage()
>>> vol_img = load_sample_motor_activation_image()
>>> img = SurfaceImage.from_volume(fsavg["white_matter"], vol_img)
>>> img
<SurfaceImage (20484,)>
>>> img = SurfaceImage.from_volume(
...     fsavg["white_matter"], vol_img, inner_mesh=fsavg["pial"]
... )
>>> img
<SurfaceImage (20484,)>

Examples using `nilearn.surface.SurfaceImage`¶

Working with Surface images

Loading and plotting of a cortical surface atlas

Seed-based connectivity on the surface

Making a surface plot of a 3D statistical map

Cortical surface-based searchlight decoding

Example of surface-based first-level analysis

Surface-based dataset first and second level analysis of a dataset

A short demo of the surface images & maskers

nilearn.surface.SurfaceImage¶

Examples using nilearn.surface.SurfaceImage¶

Examples using `nilearn.surface.SurfaceImage`¶