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_miyawaki2008

nilearn.datasets.fetch_miyawaki2008(data_dir=None, url=None, resume=True, verbose=1)

Download and loads Miyawaki et al. 2008 dataset (153MB).

See Miyawaki et al.[1].

Parameters:

data_dirpathlib.Path or str or None, optional

Path where data should be downloaded. By default, files are downloaded in a nilearn_data folder in the home directory of the user. See also nilearn.datasets.utils.get_data_dirs.

urlstr or None, default=None

URL of file to download. Override download URL. Used for test only (or if you setup a mirror of the data).

resumebool, default=True

Whether to resume download of a partly-downloaded file.

verbosebool or int, default=1

Verbosity level (0 or False means no message).

Returns:

dataBunch

Dictionary-like object, the interest attributes are :

• ‘func’: list of str

  Paths to nifti file with BOLD data

• ‘label’: list of str

  Paths to text file containing run and target data

• ‘mask’: str

  Path to nifti mask file to define target volume in visual cortex

• ‘background’: str

  Path to nifti file containing a background image usable as a background image for miyawaki images.

Notes

If the dataset files are already present in the user’s Nilearn data directory, this fetcher will not re-download them. To force a fresh download, you can remove the existing dataset folder from your local Nilearn data directory.

For more details on how Nilearn stores datasets.

This dataset is available on the brainliner website

See additional information

References

[1]

Yoichi Miyawaki, Hajime Uchida, Okito Yamashita, Masa-aki Sato, Yusuke Morito, Hiroki C. Tanabe, Norihiro Sadato, and Yukiyasu Kamitani. Visual image reconstruction from human brain activity using a combination of multiscale local image decoders. Neuron, 60(5):915–929, 2008. doi:10.1016/j.neuron.2008.11.004.

Examples using nilearn.datasets.fetch_miyawaki2008

Encoding models for visual stimuli from Miyawaki et al. 2008

Encoding models for visual stimuli from Miyawaki et al. 2008

Reconstruction of visual stimuli from Miyawaki et al. 2008

Reconstruction of visual stimuli from Miyawaki et al. 2008

Understanding NiftiMasker and mask computation

Understanding NiftiMasker and mask computation