How to create a template_data to be able to use the code bellow:?

[acamargofb]

from brainspace.gradient import GradientMaps from brainspace.plotting import plot_hemispheres from brainspace.mesh import mesh_io as mio

Create a GradientMaps object for the template

Gt = GradientMaps(kernel='cosine', approach='dm')

Apply to template data

Gt.fit(template_data)

Create a GradientMaps object for the individuals

Gs = GradientMaps(approach='dm', kernel='cosine', alignment='procrustes')

Compute gradients for all subjects and align to template

Gs.fit([subject1_data, subject2_data], reference=Gt.gradients_)

Load surfaces

left_surface = mio.read_surface('left_surface_file.obj') right_surface = mio.read_surface('right_surface_file.obj')

Plot the first aligned gradient for subject 2

plot_hemispheres(left_surface, right_surface, Gs.aligned_[1][:, 0])

[OualidBenkarim]

You would, for example, need an NxN matrix where N=n_vertices_left + n_vertices_right

[acamargofb]

I was thinking to create NxN matrix that would be the average of all the connectivity matrix for all my subjects. I have two groups: Group 1: NC subjects and Group 2: AD subjects. I want to use the template, but I am not sure whether create a template for NC and AD subjects (2 templates in total) or create only one template for NC and AD?

[OualidBenkarim]

That would depend on your research question. If you want to compare, you would need to create one for each group

[Patricklv]

Should not both groups be aligned to the same template to enable comparability? Why one for each group?

[hannahhac]

I have the same question. Do groups have to be aligned to the same template for comparability or does it reduce differences, we might want to see when comparing groups?