.. _sphx_glr_auto_examples_make_mne_anatomy.py:


.. _tut_make_anatomy:

=====================================
Extract essential anatomy information
=====================================

The HCP anatomy data needed for MNE based source analysis
Live in different places and subfolders.
MNE-HCP has a convenience function that exctracts the required
files and information and creates a "subjects_dir" as known from
MNE and freesurfer.

The most essential contents are
- freesurfer surfaces
- the MRI
- the headmodel
- the coregistration transform

This function is your friend prior to running any source analysis.



.. code-block:: python

    # Author: Denis A. Engemann
    # License: BSD 3 clause

    import os.path as op
    import hcp
    storage_dir = op.expanduser('~/mne-hcp-data')

    # This is where the data are after downloading from HCP
    hcp_path = storage_dir + '/HCP'

    # this is the new directory to be created
    subjects_dir = storage_dir + '/hcp-subjects'

    # it will make the subfolders 'bem', 'mir', 'surf' and 'label'
    # and populate it with symbolic links if possible and write some files
    # where information has to be presented in a different format to satisfy MNE.

    # this is where the coregistration matrix is written as
    # `105923-head_mri-transform.fif`
    recordings_path = storage_dir + '/hcp-meg'

    # comment out to write files on your disk
    # hcp.make_mne_anatomy(
    #     subject='105923', hcp_path=hcp_path,
    #     recordings_path=recordings_path,
    #     subjects_dir=subjects_dir)

**Total running time of the script:** ( 0 minutes  0.000 seconds)



.. container:: sphx-glr-download

    :download:`Download Python source code: make_mne_anatomy.py <make_mne_anatomy.py>`



.. container:: sphx-glr-download

    :download:`Download Jupyter notebook: make_mne_anatomy.ipynb <make_mne_anatomy.ipynb>`

.. rst-class:: sphx-glr-signature

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