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', verbose=1)[source]

Fetch SPM auditory single-subject data.

See SPM auditory single-subject data[1].

Parameters:
%(data_dir)s
data_namestr, default=’spm_auditory’

Name of the dataset.

%(verbose)s
Returns:
datasklearn.utils.Bunch

Dictionary-like object, the interest attributes are:

  • ‘anat’: list of str.

    Paths to anat images

  • ‘func’: list of str.

    Paths to functional images

  • ‘events’: list of str.

    Paths to events.tsv files

  • ‘description’: str.

    Data description

  • ‘t_r’float.

    Repetition time in seconds of the functional images.

References

Examples using nilearn.datasets.fetch_spm_auditory

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

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

Plotting images with transparent thresholding

Plotting images with transparent thresholding

Predicted time series and residuals

Predicted time series and residuals