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_localizer_calculation_task

nilearn.datasets.fetch_localizer_calculation_task(n_subjects=1, data_dir=None, verbose=1, legacy_format=True)

Fetch calculation task contrast maps from the localizer.

Parameters:

n_subjectsint, default=1

The number of subjects to load. If None is given, all 94 subjects are used.

data_dirpathlib.Path or str, 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.

verboseint, default=1

Verbosity level (0 means no message).

legacy_formatbool, default=True

If set to True, the fetcher will return recarrays. Otherwise, it will return pandas dataframes.

Returns:

dataBunch

Dictionary-like object, the interest attributes are : ‘cmaps’: string list, giving paths to nifti contrast maps

See also

nilearn.datasets.fetch_localizer_button_task

nilearn.datasets.fetch_localizer_contrasts

Notes

This function is only a caller for the fetch_localizer_contrasts in order to simplify examples reading and understanding. The ‘calculation (auditory and visual cue)’ contrast is used.

Examples using nilearn.datasets.fetch_localizer_calculation_task

Statistical testing of a second-level analysis

Statistical testing of a second-level analysis

Massively univariate analysis of a calculation task from the Localizer dataset

Massively univariate analysis of a calculation task from the Localizer dataset