{
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      "cell_type": "markdown",
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      "source": [
        "\n\n# Plot a cortical parcellation\n\nIn this example, we download the HCP-MMP1.0 parcellation\n:footcite:`GlasserEtAl2016` and show it on ``fsaverage``.\nWe will also download the customized 448-label aparc\nparcellation from :footcite:`KhanEtAl2018`.\n\n<div class=\"alert alert-info\"><h4>Note</h4><p>The HCP-MMP dataset has license terms restricting its use.\n          Of particular relevance:\n\n              \"I will acknowledge the use of WU-Minn HCP data and data\n              derived from WU-Minn HCP data when publicly presenting any\n              results or algorithms that benefitted from their use.\"</p></div>\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
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      "source": [
        "# Author: Eric Larson <larson.eric.d@gmail.com>\n#         Denis Engemann <denis.engemann@gmail.com>\n#\n# License: BSD-3-Clause\n# Copyright the MNE-Python contributors."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "import mne\n\nBrain = mne.viz.get_brain_class()\n\nsubjects_dir = mne.datasets.sample.data_path() / \"subjects\"\nmne.datasets.fetch_hcp_mmp_parcellation(subjects_dir=subjects_dir, verbose=True)\n\nmne.datasets.fetch_aparc_sub_parcellation(subjects_dir=subjects_dir, verbose=True)\n\nlabels = mne.read_labels_from_annot(\n    \"fsaverage\", \"HCPMMP1\", \"lh\", subjects_dir=subjects_dir\n)\n\nbrain = Brain(\n    \"fsaverage\",\n    \"lh\",\n    \"inflated\",\n    subjects_dir=subjects_dir,\n    cortex=\"low_contrast\",\n    background=\"white\",\n    size=(800, 600),\n)\nbrain.add_annotation(\"HCPMMP1\")\naud_label = [label for label in labels if label.name == \"L_A1_ROI-lh\"][0]\nbrain.add_label(aud_label, borders=False)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "We can also plot a combined set of labels (23 per hemisphere).\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "brain = Brain(\n    \"fsaverage\",\n    \"lh\",\n    \"inflated\",\n    subjects_dir=subjects_dir,\n    cortex=\"low_contrast\",\n    background=\"white\",\n    size=(800, 600),\n)\nbrain.add_annotation(\"HCPMMP1_combined\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "We can add another custom parcellation\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "brain = Brain(\n    \"fsaverage\",\n    \"lh\",\n    \"inflated\",\n    subjects_dir=subjects_dir,\n    cortex=\"low_contrast\",\n    background=\"white\",\n    size=(800, 600),\n)\nbrain.add_annotation(\"aparc_sub\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## References\n.. footbibliography::\n\n"
      ]
    }
  ],
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