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

Examples using nilearn.datasets.fetch_haxby#

A introduction tutorial to fMRI decoding

A introduction tutorial to fMRI decoding

A introduction tutorial to fMRI decoding
NeuroImaging volumes visualization

NeuroImaging volumes visualization

NeuroImaging volumes visualization
Plot Haxby masks

Plot Haxby masks

Plot Haxby masks
Plotting tools in nilearn

Plotting tools in nilearn

Plotting tools in nilearn
More plotting tools from nilearn

More plotting tools from nilearn

More plotting tools from nilearn
Show stimuli of Haxby et al. dataset

Show stimuli of Haxby et al. dataset

Show stimuli of Haxby et al. dataset
Decoding with FREM: face vs house object recognition

Decoding with FREM: face vs house object recognition

Decoding with FREM: face vs house object recognition
Decoding with ANOVA + SVM: face vs house in the Haxby dataset

Decoding with ANOVA + SVM: face vs house in the Haxby dataset

Decoding with ANOVA + SVM: face vs house in the Haxby dataset
Cortical surface-based searchlight decoding

Cortical surface-based searchlight decoding

Cortical surface-based searchlight decoding
The haxby dataset: different multi-class strategies

The haxby dataset: different multi-class strategies

The haxby dataset: different multi-class strategies
Searchlight analysis of face vs house recognition

Searchlight analysis of face vs house recognition

Searchlight analysis of face vs house recognition
Decoding of a dataset after GLM fit for signal extraction

Decoding of a dataset after GLM fit for signal extraction

Decoding of a dataset after GLM fit for signal extraction
Setting a parameter by cross-validation

Setting a parameter by cross-validation

Setting a parameter by cross-validation
ROI-based decoding analysis in Haxby et al. dataset

ROI-based decoding analysis in Haxby et al. dataset

ROI-based decoding analysis in Haxby et al. dataset
Different classifiers in decoding the Haxby dataset

Different classifiers in decoding the Haxby dataset

Different classifiers in decoding the Haxby dataset
Computing a Region of Interest (ROI) mask manually

Computing a Region of Interest (ROI) mask manually

Computing a Region of Interest (ROI) mask manually
Massively univariate analysis of face vs house recognition

Massively univariate analysis of face vs house recognition

Massively univariate analysis of face vs house recognition
Advanced decoding using scikit learn

Advanced decoding using scikit learn

Advanced decoding using scikit learn