hcp.compute_forward_stack¶

hcp.compute_forward_stack(subjects_dir, subject, recordings_path, info_from=(('data_type', 'rest'), ('run_index', 0)), fwd_params=None, src_params=None, hcp_path='.', n_jobs=1, verbose=None)¶

Convenience function for conducting standard MNE analyses.

Note

this function computes bem solutions, source spaces and forward models optimized for connectivity computation, i.e., the fsaverage space is morphed onto the subject’s space.

subject : str

The subject name.

hcp_path : str

The directory containing the HCP data.

recordings_path : str

The path where MEG data and transformations are stored.

subjects_dir : str

The directory containing the extracted HCP subject data.

info_from : tuple of tuples | dict

The reader info concerning the data from which sensor positions should be read. Must not be empty room as sensor positions are in head coordinates for 4D systems, hence not available in that case. Note that differences between the sensor positions across runs are smaller than 12 digits, hence negligible.

fwd_params : None | dict

The forward parameters

src_params : None | dict

The src params. Defaults to:

dict(subject=’fsaverage’, fname=None, spacing=’oct6’, n_jobs=2,

surface=’white’, subjects_dir=subjects_dir, add_dist=True)

hcp_path : str

The prefix of the path of the HCP data.

n_jobs : int

The number of jobs to use in parallel.

verbose : bool, str, int, or None

If not None, override default verbose level (see mne.verbose)

out : dict

A dictionary with the following keys:

fwd : instance of mne.Forward

The forward solution.

src_subject : instance of mne.SourceSpace

The source model on the subject’s surface

src_fsaverage : instance of mne.SourceSpace

The source model on fsaverage’s surface

bem_sol : dict

The BEM.

info : instance of mne.io.meas_info.Info

The actual measurement info used.