[Mne_analysis] hcp-mne head_mri trans

Denis A. Engemann denis-alexander.engemann at inria.fr
Fri Jan 11 11:45:38 EST 2019
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Hey Max,

Checkout this tutorial: http://mne-tools.github.io/mne-hcp/auto_examples/plot_coregistration.html#sphx-glr-auto-examples-plot-coregistration-py

The default mne plotter does not work. You need to manage the hcp transforms differently from how mne thinks it should be done.

Let me know if it helps.

Denis

> On 11 Jan 2019, at 17:38, Maximilien Chaumon <maximilien.chaumon at gmail.com> wrote:
> 
>         External Email - Use Caution        
> 
> Hello,
> 
> I'm starting to play around with mne-hcp
> I'm picking code in the examples of mne-hcp to create in each subjec:
> mne_anatomy. fine
> bem_model and _solution. fine
> head_mri_t. fine
> check that everything is in place with mne.viz.plot_alignment, and I get this:
> https://drive.google.com/open?id=17altWLQIfyZMxUcvnsxgzJp9zN0qcET0
> I understand that the head_mri_t is not applied to the helmet. is that correct? how impactfull is that for upcoming computations? how can I fix it?
> 
> Many thanks,
> Max
> 
> This is my code:
> 
> import os.path as op
> import glob
> import mne
> import hcp
> 
> storage_dir = op.expanduser('~/owncloud/Lab/Projects/SOLID_MEEG/data/HCPunzipped')
> subjects_dir = op.expanduser('~/owncloud/Lab/Projects/SOLID_MEEG/data/HCPsubjects')
> recordings_dir = op.expanduser('~/owncloud/Lab/Projects/SOLID_MEEG/data/HCPmeg')
> 
> subjects = glob.glob(op.join(storage_dir,'[0-9][0-9][0-9][0-9][0-9][0-9]'))
> 
> src_fsaverage = mne.setup_source_space(
>     subject='fsaverage', subjects_dir='/network/lustre/iss01/cenir/software/meeg/freesurfer/subjects', add_dist=False,
>     spacing='oct6')
> 
> for subject in subjects:
>     hcp_params = dict(
>         hcp_path=storage_dir,
>         subject=subject,
>         data_type='rest')
>     
>     run_index = 0
>     
>     hcp.make_mne_anatomy(
>         subject, subjects_dir = subjects_dir,
>         hcp_path = storage_dir,
>         recordings_path = recordings_dir)
> 
>     bems = mne.make_bem_model(subject, conductivity=(0.3,),
>                               subjects_dir=subjects_dir,
>                               ico=None)  # ico = None for morphed SP.
>     mne.write_bem_surfaces(op.join(subjects_dir,subject,'bem',subject+'-bem.fif'),bems)
>     
>     bem_sol = mne.make_bem_solution(bems)
>     bem_sol['surfs'][0]['coord_frame'] = 5
>     
>     mne.write_bem_solution(op.join(subjects_dir,subject,'bem',subject+'-bem-sol.fif'),bem_sol)
>     
>     head_mri_t = mne.read_trans(
>         op.join(recordings_dir, subject, '{}-head_mri-trans.fif'.format(subject)))
>     
>     mne.write_trans(op.join(subjects_dir,subject,'bem',subject+'-trans.fif'),head_mri_t)
>     
>     info = hcp.read_info(run_index=run_index, **hcp_params)
>     picks = mne.pick_types(info, meg=True, ref_meg=False)
>     info = mne.pick_info(info, picks)
>     
>     mne.viz.plot_alignment(info,head_mri_t,subject=subject,subjects_dir=subjects_dir,surfaces=('inner_skull','white'))
> 
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