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_abide_pcp#
- nilearn.datasets.fetch_abide_pcp(data_dir=None, n_subjects=None, pipeline='cpac', band_pass_filtering=False, global_signal_regression=False, derivatives=['func_preproc'], quality_checked=True, url=None, verbose=1, legacy_format=True, **kwargs)[source]#
Fetch ABIDE dataset.
Fetch the Autism Brain Imaging Data Exchange (ABIDE) dataset wrt criteria that can be passed as parameter. Note that this is the preprocessed version of ABIDE provided by the preprocess connectome projects (PCP). See 1.
- Parameters
- data_dir
pathlib.Pathorstr, optional Path where data should be downloaded. By default, files are downloaded in home directory.
- n_subjectsint, optional
The number of subjects to load. If None is given, all available subjects are used (this number depends on the preprocessing pipeline used).
- pipelinestring {‘cpac’, ‘css’, ‘dparsf’, ‘niak’}, optional
Possible pipelines are “ccs”, “cpac”, “dparsf” and “niak”. Default=’cpac’.
- band_pass_filteringboolean, optional
Due to controversies in the literature, band pass filtering is optional. If true, signal is band filtered between 0.01Hz and 0.1Hz. Default=False.
- global_signal_regressionboolean optional
Indicates if global signal regression should be applied on the signals. Default=False.
- derivativesstring list, optional
Types of downloaded files. Possible values are: alff, degree_binarize, degree_weighted, dual_regression, eigenvector_binarize, eigenvector_weighted, falff, func_mask, func_mean, func_preproc, lfcd, reho, rois_aal, rois_cc200, rois_cc400, rois_dosenbach160, rois_ez, rois_ho, rois_tt, and vmhc. Please refer to the PCP site for more details. Default=[‘func_preproc’].
- quality_checkedboolean, optional
If true (default), restrict the list of the subjects to the one that passed quality assessment for all raters. Default=True.
- url
str, optional URL of file to download. Override download URL. Used for test only (or if you setup a mirror of the data). Default=None.
- verbose
int, optional Verbosity level (0 means no message). Default=1.
- legacy_format
bool, optional If set to
True, the fetcher will return recarrays. Otherwise, it will return pandas dataframes. Default=True.- kwargsparameter list, optional
Any extra keyword argument will be used to filter downloaded subjects according to the CSV phenotypic file. Some examples of filters are indicated below.
- SUB_IDlist of integers in [50001, 50607], optional
Ids of the subjects to be loaded.
- DX_GROUPinteger in {1, 2}, optional
1 is autism, 2 is control.
- DSM_IV_TRinteger in [0, 4], optional
O is control, 1 is autism, 2 is Asperger, 3 is PPD-NOS, 4 is Asperger or PPD-NOS.
- AGE_AT_SCANfloat in [6.47, 64], optional
Age of the subject.
- SEXinteger in {1, 2}, optional
1 is male, 2 is female.
- HANDEDNESS_CATEGORYstring in {‘R’, ‘L’, ‘Mixed’, ‘Ambi’}, optional
R = Right, L = Left, Ambi = Ambidextrous.
- HANDEDNESS_SCOREinteger in [-100, 100], optional
Positive = Right, Negative = Left, 0 = Ambidextrous.
- data_dir
Notes
Code and description of preprocessing pipelines are provided on the PCP website <http://preprocessed-connectomes-project.github.io/>.
References
- 1
Jared Nielsen, Brandon Zielinski, P Fletcher, Andrew Alexander, Nicholas Lange, Erin Bigler, Janet Lainhart, and Jeffrey Anderson. Multisite functional connectivity mri classification of autism: abide results. Frontiers in Human Neuroscience, 7:599, 2013. URL: https://www.frontiersin.org/article/10.3389/fnhum.2013.00599, doi:10.3389/fnhum.2013.00599.