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.