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.

7.2.16. nilearn.datasets.fetch_development_fmri

nilearn.datasets.fetch_development_fmri(n_subjects=None, reduce_confounds=True, data_dir=None, resume=True, verbose=1, age_group='both')

Fetch movie watching based brain development dataset (fMRI)

The data is downsampled to 4mm resolution for convenience. The origin of the data is coming from OpenNeuro. See Notes below.

New in version 0.5.2.

n_subjects: int, optional (default None)

The number of subjects to load. If None, all the subjects are loaded. Total 155 subjects.

reduce_confounds: bool, optional (default True)

If True, the returned confounds only include 6 motion parameters, mean framewise displacement, signal from white matter, csf, and 6 anatomical compcor parameters. This selection only serves the purpose of having realistic examples. Depending on your research question, other confounds might be more appropriate. If False, returns all fmriprep confounds.

data_dir: str, optional (default None)

Path of the data directory. Used to force data storage in a specified location. If None, data are stored in home directory.

resume: bool, optional (default True)

Whether to resume download of a partly-downloaded file.

verbose: int, optional (default 1)

Defines the level of verbosity of the output.

age_group: str, optional (default ‘both’)

Which age group to fetch - ‘adults’ = fetch adults only (n=33, ages 18-39) - ‘child’ = fetch children only (n=122, ages 3-12) - ‘both’ = fetch full sample (n=155)

data: Bunch

Dictionary-like object, the interest attributes are :

  • ‘func’: list of str (Nifti files)

    Paths to downsampled functional MRI data (4D) for each subject.

  • ‘confounds’: list of str (tsv files)

    Paths to confounds related to each subject.

  • ‘phenotypic’: numpy.ndarray

    Contains each subject age, age group, child or adult, gender, handedness.


The original data is downloaded from OpenNeuro

This fetcher downloads downsampled data that are available on Open Science Framework (OSF). Located here:

Preprocessing details:

Note that if n_subjects > 2, and age_group is ‘both’, fetcher will return a ratio of children and adults representative of the total sample.


Please cite this paper if you are using this dataset. Richardson, H., Lisandrelli, G., Riobueno-Naylor, A., & Saxe, R. (2018). Development of the social brain from age three to twelve years. Nature communications, 9(1), 1027.