[Mne_analysis] hcp-mne head_mri trans

[Maximilien Chaumon]

        External Email - Use Caution        

ok. So I assume things are just fine.
Only the device helmet, represented in blue in the figure is somehow tilted
90° off, but it's just an aesthetic thing if I understand correctly, right?

Le ven. 11 janv. 2019 à 17:46, Denis A. Engemann <
denis-alexander.engemann at inria.fr> a écrit :

>         External Email - Use Caution
>
> 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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