Note

This page is a reference documentation. It only explains the function signature, and not how to use it. Please refer to the user guide for the big picture.

fetch_spm_multimodal_fmri

nilearn.datasets.fetch_spm_multimodal_fmri(data_dir=None, data_name='spm_multimodal_fmri', verbose=1)[source]

Fetcher for Multi-modal Face Dataset.

For more information, see the dataset description.

Parameters:
data_dirpathlib.Path or str or None, optional

Path where data should be downloaded. By default, files are downloaded in a nilearn_data folder in the home directory of the user. See also nilearn.datasets.utils.get_data_dirs.

data_namestr, default=’spm_multimodal_fmri’

Name of the dataset.

Deprecated since Nilearn 0.15.0.

verbosebool or int, default=1

Verbosity level (0 or False means no message).

Returns:
datasklearn.utils.Bunch

Dictionary-like object, contains:

  • anat: str. Full path to 3D nifti image (in .img format) of the anatomical image.

  • events1: str. Full path to a TSV file describing the paradigm of the run 1.

  • events2: str. Full path to a TSV file describing the paradigm of the run 2.

  • func1: list of str. List of full paths to 3D nifti image (in .img format) for the functional image of the run 1 (one file per time point).

  • func2: list of str. List of full paths to 3D nifti image (in .img format) for the functional image of the run 2 (one file per time point).

  • slice_order: str. Order in which the slices of the functional runs were acquired.

  • t_r: float. Repetition time in seconds.

  • trials_ses1: str. Full path to .mat file containing onsets for run 1.

  • trials_ses2: str. Full path to .mat file containing onsets for run 2.

Notes

If the dataset files are already present in the user’s Nilearn data directory, this fetcher will not re-download them. To force a fresh download, you can remove the existing dataset folder from your local Nilearn data directory.

For more details on how Nilearn stores datasets.

Examples using nilearn.datasets.fetch_spm_multimodal_fmri

Single-subject data (two runs) in native space

Single-subject data (two runs) in native space