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.

8.2.8. nilearn.datasets.fetch_atlas_smith_2009

nilearn.datasets.fetch_atlas_smith_2009(data_dir=None, mirror='origin', url=None, resume=True, verbose=1)

Download and load the Smith ICA and BrainMap atlas (dated 2009) [1] [2].

Parameters
data_dirstring, optional

Path of the data directory. Used to force data storage in a non- standard location. Default: None (meaning: default)

mirrorstring, optional

By default, the dataset is downloaded from the original website of the atlas. Specifying “nitrc” will force download from a mirror, with potentially higher bandwith. Default=’origin’.

urlstring, optional

Download URL of the dataset. Overwrite the default URL.

resumebool, optional

Whether to resumed 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, contains:

  • 20-dimensional ICA, Resting-FMRI components:

    • all 20 components (rsn20)

    • 10 well-matched maps from these, as shown in PNAS paper (rsn10)

  • 20-dimensional ICA, BrainMap components:

    • all 20 components (bm20)

    • 10 well-matched maps from these, as shown in PNAS paper (bm10)

  • 70-dimensional ICA, Resting-FMRI components (rsn70)

  • 70-dimensional ICA, BrainMap components (bm70)

Notes

For more information about this dataset’s structure: http://www.fmrib.ox.ac.uk/datasets/brainmap+rsns/

References

1

S.M. Smith, P.T. Fox, K.L. Miller, D.C. Glahn, P.M. Fox, C.E. Mackay, N. Filippini, K.E. Watkins, R. Toro, A.R. Laird, and C.F. Beckmann. Correspondence of the brain’s functional architecture during activation and rest. Proc Natl Acad Sci USA (PNAS), 106(31):13040-13045, 2009.

2

A.R. Laird, P.M. Fox, S.B. Eickhoff, J.A. Turner, K.L. Ray, D.R. McKay, D.C Glahn, C.F. Beckmann, S.M. Smith, and P.T. Fox. Behavioral interpretations of intrinsic connectivity networks. Journal of Cognitive Neuroscience, 2011