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.

nilearn.datasets.fetch_spm_auditory#

nilearn.datasets.fetch_spm_auditory(data_dir=None, data_name='spm_auditory', subject_id='sub001', verbose=1)[source]#

Function to fetch SPM auditory single-subject data.

See 1.

Parameters
data_dirpathlib.Path or str, optional

Path where data should be downloaded. By default, files are downloaded in home directory.

data_namestring, optional

Name of the dataset. Default=’spm_auditory’.

subject_idstring, optional

Indicates which subject to retrieve. Default=’sub001’.

verboseint, optional

Verbosity level (0 means no message). Default=1.

Returns
datasklearn.datasets.base.Bunch

Dictionary-like object, the interest attributes are: - ‘func’: string list. Paths to functional images - ‘anat’: string list. Path to anat image

References

1

Spm auditory single-subject data. http://www.fil.ion.ucl.ac.uk/spm/data/auditory/. Accessed: 2021-05-19.

Examples using nilearn.datasets.fetch_spm_auditory#

Intro to GLM Analysis: a single-session, single-subject fMRI dataset

Intro to GLM Analysis: a single-session, single-subject fMRI dataset

Intro to GLM Analysis: a single-session, single-subject fMRI dataset
Predicted time series and residuals

Predicted time series and residuals

Predicted time series and residuals