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, url=None, verbose=1, legacy_format=True)[source]#

Fetch calculation task contrast maps from the localizer.

Parameters:
n_subjectsint, optional

The number of subjects to load. If None is given, all 94 subjects are used. Default=1.

data_dirpathlib.Path or str, optional

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

urlstr, optional

URL of file to download. Override download URL. Used for test only (or if you setup a mirror of the data). Default=None.

verboseint, optional

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

legacy_formatbool, optional

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

Returns:
dataBunch

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

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

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

Massively univariate analysis of a calculation task from the Localizer dataset