Plot Activation Foci¶
Plot spheroids at positions on the surface manifold according to coordinates or vertex ids.
Python source code:
import os import os.path as op from numpy import arange from numpy.random import permutation import nibabel as nib from surfer import Brain print(__doc__) subject_id = "fsaverage" subjects_dir = os.environ["SUBJECTS_DIR"] """ Bring up the visualization. """ brain = Brain(subject_id, "lh", "inflated") """ First we'll get a set of stereotaxic foci in the MNI coordinate system. These might be peak activations from a volume based analysis. """ coords = [[-36, 18, -3], [-43, 25, 24], [-48, 26, -2]] """ Now we plot the foci on the inflated surface. We will map the foci onto the surface by finding the vertex on the "white" mesh that is closest to the coordinate of each point we want to display. While this is not a perfect transformation, it can give you some idea of where peaks from a volume-based analysis would be located on the surface. You can use any valid matplotlib color for the foci; the default is white. """ brain.add_foci(coords, map_surface="white", color="gold") """ You can also plot foci with a set of surface vertex ids. For instance, you might want to plot the peak activation within an ROI for each of your indivdiual subjects over the group activation map. Here, we will just demonstrate with a set of randomly choosen vertices from within the superior temporal sulcus. First, we load in the Destrieux parcellation annotation file and find 10 random vertices within the STS. """ annot_path = op.join(subjects_dir, subject_id, "label/lh.aparc.a2009s.annot") ids, ctab, names = nib.freesurfer.read_annot(annot_path) verts = arange(0, len(ids)) coords = permutation(verts[ids == 74])[:10] """ You can also control the size of the focus glpyhs. We'll make these a little bit smaller than our other foci. """ scale_factor = 0.7 """ Finally, plot the foci using the coords_as_verts option to center each sphereoid at its vertex id. """ brain.add_foci(coords, coords_as_verts=True, scale_factor=scale_factor, color="#A52A2A")