Plot a cortical parcellation

In this example, we download the HCP-MMP1.0 parcellation [1] and show it on fsaverage. We will also download the customized 448-label aparc parcellation from [2].

Note

The HCP-MMP dataset has license terms restricting its use. Of particular relevance:

“I will acknowledge the use of WU-Minn HCP data and data derived from WU-Minn HCP data when publicly presenting any results or algorithms that benefitted from their use.”

# Author: Eric Larson <larson.eric.d@gmail.com>
#         Denis Engemann <denis.engemann@gmail.com>
#
# License: BSD-3-Clause

import mne

Brain = mne.viz.get_brain_class()

subjects_dir = mne.datasets.sample.data_path() / "subjects"
mne.datasets.fetch_hcp_mmp_parcellation(subjects_dir=subjects_dir, verbose=True)

mne.datasets.fetch_aparc_sub_parcellation(subjects_dir=subjects_dir, verbose=True)

labels = mne.read_labels_from_annot(
    "fsaverage", "HCPMMP1", "lh", subjects_dir=subjects_dir
)

brain = Brain(
    "fsaverage",
    "lh",
    "inflated",
    subjects_dir=subjects_dir,
    cortex="low_contrast",
    background="white",
    size=(800, 600),
)
brain.add_annotation("HCPMMP1")
aud_label = [label for label in labels if label.name == "L_A1_ROI-lh"][0]
brain.add_label(aud_label, borders=False)

Reading labels from parcellation...
   read 181 labels from /home/circleci/mne_data/MNE-sample-data/subjects/fsaverage/label/lh.HCPMMP1.annot

We can also plot a combined set of labels (23 per hemisphere).

brain = Brain(
    "fsaverage",
    "lh",
    "inflated",
    subjects_dir=subjects_dir,
    cortex="low_contrast",
    background="white",
    size=(800, 600),
)
brain.add_annotation("HCPMMP1_combined")

We can add another custom parcellation

brain = Brain(
    "fsaverage",
    "lh",
    "inflated",
    subjects_dir=subjects_dir,
    cortex="low_contrast",
    background="white",
    size=(800, 600),
)
brain.add_annotation("aparc_sub")

References

[1]

Matthew F. Glasser, Timothy S. Coalson, Emma C. Robinson, Carl D. Hacker, John Harwell, Essa Yacoub, Kamil Ugurbil, Jesper Andersson, Christian F. Beckmann, Mark Jenkinson, Stephen M. Smith, and David C. Van Essen. A multi-modal parcellation of human cerebral cortex. Nature, 536(7615):171–178, 2016. doi:10.1038/nature18933.

[2]

Sheraz Khan, Javeria A. Hashmi, Fahimeh Mamashli, Konstantinos Michmizos, Manfred G. Kitzbichler, Hari Bharadwaj, Yousra Bekhti, Santosh Ganesan, Keri-Lee A. Garel, Susan Whitfield-Gabrieli, Randy L. Gollub, Jian Kong, Lucia M. Vaina, Kunjan D. Rana, Steven M. Stufflebeam, Matti S. Hämäläinen, and Tal Kenet. Maturation trajectories of cortical resting-state networks depend on the mediating frequency band. NeuroImage, 174:57–68, 2018. doi:10.1016/j.neuroimage.2018.02.018.

Estimated memory usage: 26 MB