Tutorial 2: Types of Surfaces

This tutorial covers what types of surfaces that can be plotted with surfplot.

Types of surfaces

Put briefly, surfplot can take file paths to any valid surface file(s) with geometry data. Under the hood, Plot runs brainspace.mesh.mesh_io.read_surface() to load files. Typically, these will be Freesurfer or GIFTI files.

plottingPlot can also read instances of brainspace.vtk_interface.wrappers.data_object.BSPolyData, which are returned by read_surface(). So, pre-loaded surfaces with read_surface() can be plotted as well.

Beyond that, surfplot is invariant to the actual brain surfaces you wish to use. Common human surfaces include fsaverage surfaces packaged with Freesurfer, and Human Connectome Project fsLR surfaces (downloadable here). Several different human surfaces can also all be found on OSF here. Non-human surfaces can also be plotted, such as the NMTv2 Macaque surfaces.

Note that throughout these tutorials, surfaces are automatically fetched using neuromaps or Brainspace to avoid having to specify local files. It is also possible to fetch fsaverage surfaces using nilearn. These are all great options to automically get surfaces in your workflow, and make reproducibility and portability of your code a bit more feasible.

Note

Make sure to always use the correct surface for your data. Double check the number of vertices in both your data and the surfaces you are using for plotting.

In Tutorial 1: Quick Start we plotted fsLR surfaces. For the sake of demonstration, let’s plot Freesurfer’s fsaverage here, again using neuromaps fetching functions.

from neuromaps.datasets import fetch_fsaverage
from surfplot import Plot

surfaces = fetch_fsaverage(density='164k')
lh, rh = surfaces['inflated']

# make figure
p = Plot(lh, rh)
fig = p.build()
fig.show()

Brightness

By default, Plot will plot a medium-gray surface, typical of most surface plotting packages like Connectome Workbench. The brightness of the blank surface can be adjusted using the brightness parameter, if desired. Values range from 0 (black) to 1 (white). For example:

p = Plot(lh, rh, brightness=.8)
fig = p.build()
fig.show()