mvpa2.misc.surfing.volsurf.VolSurfMapping

class mvpa2.misc.surfing.volsurf.VolSurfMapping(vg, white, pial, intermediate=None, nsteps=10, start_fr=0.0, stop_fr=1.0, start_mm=0, stop_mm=0)

General mapping between volume and surface.

Subclasses have to implement node2voxels

Methods

coordinates_to_grey_distance_mm(nodes, xyz)	Computes the grey position of coordinates in metric units
get_node2voxels_mapping()	Returns:
get_parameter_dict()	Returns a dictionary with the most important parameters
surf_project_nodewise(xyz)	Projects coordinates on lines connecting pial and white matter.
surf_project_weights(nodes, xyz)	Computes relative position of xyz on lines from pial to white matter.
surf_project_weights_nodewise(xyz)	Computes relative position of xyz on lines from pial to white matter.
surf_unproject_weights_nodewise(weights)	Maps relative positions in grey matter to coordinates
voxel_count_nifti_image()	Returns a NIFTI image indicating how often each voxel is selected.

Parameters:

volgeom: volgeom.VolGeom :

Volume geometry

white: surf.Surface :

Surface representing white-grey matter boundary

pial: surf.Surface :

Surface representing pial-grey matter boundary

intermediate: surf.Surface (default: None). :

Surface representing intermediate surface. If omitted it is the node-wise average of white and pial.

nsteps: int (default: 10) :

Number of steps from white to pial surface

start_fr: float (default: 0) :

Relative start position of line in gray matter, 0.=white surface, 1.=pial surface.

stop_fr: float (default: 1) :

Relative stop position of line (as in see start).

start_mm: float (default: 0) :

Absolute start position offset (as in start_fr).

stop_mm: float (default: 0) :

Absolute start position offset (as in start_fr).

Notes

‘pial’ and ‘white’ should have the same topology.

Methods

coordinates_to_grey_distance_mm(nodes, xyz)	Computes the grey position of coordinates in metric units
get_node2voxels_mapping()	Returns:
get_parameter_dict()	Returns a dictionary with the most important parameters
surf_project_nodewise(xyz)	Projects coordinates on lines connecting pial and white matter.
surf_project_weights(nodes, xyz)	Computes relative position of xyz on lines from pial to white matter.
surf_project_weights_nodewise(xyz)	Computes relative position of xyz on lines from pial to white matter.
surf_unproject_weights_nodewise(weights)	Maps relative positions in grey matter to coordinates
voxel_count_nifti_image()	Returns a NIFTI image indicating how often each voxel is selected.

get_node2voxels_mapping()

Returns:

n2v: dict :

A mapping from node indices to voxels. In this mapping, the :

‘i’-th node is associated with ‘n2v[i]=v2p’ which contains the :

mapping from linear voxel indices to grey matter positions. In :

other words, ‘n2v[i][idx]=v2p[idx]=pos’ means that the voxel with :

linear index ‘idx’ is associated with node ‘i’ and has has :

relative position ‘pos’ in the gray matter. :

If node ‘i’ is outside the volume, then ‘n2v[i]=None’. :

Notes

The typical use case is selecting voxels in the grey matter. The rationale of this method is that (assuming a sufficient dense cortical surface mesh, combined with a sufficient number of nsteps, the grey matter is sampled dense enough so that ‘no voxels are left out’.

get_parameter_dict()

Returns a dictionary with the most important parameters of this instance

voxel_count_nifti_image()

Returns a NIFTI image indicating how often each voxel is selected.

Parameters:

n2v: dict :

Node to voxel mapping, typically from node2voxels. If omitted then the output from node2voxels() is used.

Returns:

img: nifti.Nifti1Image :

Image where the value in each voxel indicates how often each voxel was selected by n2v.