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Hi,
I am trying to measure the hippocampus activity by creating the mixed
source spaces. I mean to say, mixed source space includes two surfaces and
two volumes(left and right hippocampus). I could generate the inverse
solution but i am unable to visualise it.
I tried using the the following lines to visualise the inverse solution:
img = stc.as_volume(src, mri_resolution=False) # src includes the
sources from surface as well as from the volume
t1_fname = data_path + '/subjects/sample/mri/T1.mgz'
# Plotting with nilearn plot_stat_map
<http://nilearn.github.io/modules/generated/nilearn.plotting.plot_stat_map.html#nilearn.plotting.plot_stat_map>(index_img
<http://nilearn.github.io/modules/generated/nilearn.image.index_img.html#nilearn.image.index_img>(img,
200), t1_fname, threshold=8.)plt.show
<https://matplotlib.org/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show>()
It terminated with a error:
'MixedSourceEstimate' object has no attribute 'as_volume'.
Is there any (other) way that i can visualise the inverse solution of mixed
source spaces on MRI using MNE python?
Hope i am clear with my question!
Thank you in advance