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_haxby#

nilearn.datasets.fetch_haxby(data_dir=None, subjects=(2,), fetch_stimuli=False, url=None, resume=True, verbose=1)[source]#

Download and loads complete haxby dataset.

See 1.

Parameters
data_dirpathlib.Path or str, optional

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

subjectslist or int, optional

Either a list of subjects or the number of subjects to load, from 1 to 6. By default, 2nd subject will be loaded. Empty list returns no subject data. Default=(2,).

fetch_stimuliboolean, optional

Indicate if stimuli images must be downloaded. They will be presented as a dictionary of categories. Default=False.

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.

resumebool, optional

Whether to resume download of a partly-downloaded file. Default=True.

verboseint, optional

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

Returns
datasklearn.datasets.base.Bunch

Dictionary-like object, the interest attributes are :

  • ‘anat’: string list. Paths to anatomic images.

  • ‘func’: string list. Paths to nifti file with bold data.

  • ‘session_target’: string list. Paths to text file containing session and target data.

  • ‘mask’: string. Path to fullbrain mask file.

  • ‘mask_vt’: string list. Paths to nifti ventral temporal mask file.

  • ‘mask_face’: string list. Paths to nifti ventral temporal mask file.

  • ‘mask_house’: string list. Paths to nifti ventral temporal mask file.

  • ‘mask_face_little’: string list. Paths to nifti ventral temporal mask file.

  • ‘mask_house_little’: string list. Paths to nifti ventral temporal mask file.

Notes

PyMVPA provides a tutorial making use of this dataset: http://www.pymvpa.org/tutorial.html

More information about its structure: http://dev.pymvpa.org/datadb/haxby2001.html

See additional information <http://www.sciencemag.org/content/293/5539/2425>

Run 8 in subject 5 does not contain any task labels. The anatomical image for subject 6 is unavailable.

References

1

James V. Haxby, M. Ida Gobbini, Maura L. Furey, Alumit Ishai, Jennifer L. Schouten, and Pietro Pietrini. Distributed and overlapping representations of faces and objects in ventral temporal cortex. Science, 293(5539):2425–2430, 2001. URL: https://science.sciencemag.org/content/293/5539/2425, arXiv:https://science.sciencemag.org/content/293/5539/2425.full.pdf, doi:10.1126/science.1063736.

Examples using nilearn.datasets.fetch_haxby#

Advanced decoding using scikit learn

Advanced decoding using scikit learn

Advanced decoding using scikit learn