netneurotools.datasets.fetch_yerkes19

netneurotools.datasets.fetch_yerkes19(force=False, data_dir=None, verbose=1)[source]

Download files for Donahue et al., 2016 Yerkes19 template.

This dataset contains midthickness, inflated, and very inflated surface files in GIFTI format for the Yerkes19 macaque template in fsLR32k space. The Yerkes19 atlas is a population-average surface template for macaque monkeys derived from high-resolution anatomical scans.

If you used this data, please cite 1.

Returns:

filenames – Dictionary-like object with keys [‘midthickness’, ‘inflated’, ‘vinflated’], where corresponding values are Surface namedtuples containing filepaths for the left (L) and right (R) hemisphere GIFTI surface files.

Return type:

sklearn.utils.Bunch

Other Parameters:

  • force (bool, optional) – If True, will overwrite existing dataset. Default: False

  • data_dir (str, optional) – Path to use as data directory. If not specified, will check for environmental variable ‘NNT_DATA’; if that is not set, will use ~/nnt-data instead. Default: None

  • verbose (int, optional) – Modifies verbosity of download, where higher numbers mean more updates. Default: 1

Notes

The Yerkes19 template is a macaque cortical surface atlas using the fsLR32k mesh (approximately 32k vertices per hemisphere). It was developed to facilitate comparative neuroanatomy studies between human and non-human primates.

The returned files include:

  • midthickness: Midthickness surface geometry (.surf.gii), halfway between white and pial surfaces.

  • inflated: Inflated surface geometry (.surf.gii) for improved visualization of sulci and gyri.

  • vinflated: Very inflated surface geometry (.surf.gii) providing additional smoothing for visualization.

Example directory tree:

~/nnt-data/tpl-yerkes19
├── tpl-yerkes19_space-fsLR32k_inflated.L.surf.gii
├── tpl-yerkes19_space-fsLR32k_inflated.R.surf.gii
├── tpl-yerkes19_space-fsLR32k_midthickness.L.surf.gii
├── tpl-yerkes19_space-fsLR32k_midthickness.R.surf.gii
├── tpl-yerkes19_space-fsLR32k_vinflated.L.surf.gii
└── tpl-yerkes19_space-fsLR32k_vinflated.R.surf.gii

0 directories, 6 files

Examples

Load the Yerkes19 template surfaces:

>>> surfaces = fetch_yerkes19()
>>> surfaces.keys()
dict_keys(['midthickness', 'inflated', 'vinflated'])

Access the midthickness surface GIFTI files:

>>> surfaces.midthickness
Surface(L=PosixPath('~/nnt-data/tpl-yerkes19/tpl-yerkes19_space-fsLR32k_midthickness.L.surf.gii'),
        R=PosixPath('~/nnt-data/tpl-yerkes19/tpl-yerkes19_space-fsLR32k_midthickness.R.surf.gii'))

Load the left midthickness surface with nibabel:

>>> import nibabel as nib
>>> gii = nib.load(surfaces.midthickness.L)
>>> vertices = gii.agg_data('pointset')
>>> faces = gii.agg_data('triangle')
>>> print(f"Vertices: {vertices.shape}, Faces: {faces.shape}")
Vertices: (32492, 3), Faces: (64980, 3)

References