.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "auto_examples/07_advanced/plot_neurovault_meta_analysis.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note Click :ref:`here ` to download the full example code or to run this example in your browser via Binder .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_examples_07_advanced_plot_neurovault_meta_analysis.py: NeuroVault meta-analysis of stop-go paradigm studies. ===================================================== This example shows how to download statistical maps from NeuroVault See :func:`nilearn.datasets.fetch_neurovault_ids` documentation for more details. .. GENERATED FROM PYTHON SOURCE LINES 12-21 .. code-block:: default # Author: Ben Cipollini # License: BSD import scipy from nilearn.datasets import fetch_neurovault_ids from nilearn import plotting from nilearn.image import new_img_like, load_img, math_img, get_data .. GENERATED FROM PYTHON SOURCE LINES 22-24 Fetch images for "successful stop minus go"-like protocols. ----------------------------------------------------------- .. GENERATED FROM PYTHON SOURCE LINES 24-47 .. code-block:: default # These are the images we are interested in, # in order to save time we specify their ids explicitly. stop_go_image_ids = (151, 3041, 3042, 2676, 2675, 2818, 2834) # These ids were determined by querying neurovault like this: # from nilearn.datasets import fetch_neurovault, neurovault # nv_data = fetch_neurovault( # max_images=7, # cognitive_paradigm_cogatlas=neurovault.Contains('stop signal'), # contrast_definition=neurovault.Contains('succ', 'stop', 'go'), # map_type='T map') # print([meta['id'] for meta in nv_data['images_meta']]) nv_data = fetch_neurovault_ids(image_ids=stop_go_image_ids) images_meta = nv_data['images_meta'] collections = nv_data['collections_meta'] .. rst-class:: sphx-glr-script-out Out: .. code-block:: none Reading local neurovault data. Already fetched 1 image Already fetched 2 images Already fetched 3 images Already fetched 4 images Already fetched 5 images Already fetched 6 images Already fetched 7 images 7 images found on local disk. .. GENERATED FROM PYTHON SOURCE LINES 48-50 Visualize the data ------------------ .. GENERATED FROM PYTHON SOURCE LINES 50-58 .. code-block:: default print('\nplotting glass brain for collected images\n') for im in images_meta: plotting.plot_glass_brain( im['absolute_path'], title='image {0}: {1}'.format(im['id'], im['contrast_definition'])) .. rst-class:: sphx-glr-horizontal * .. image-sg:: /auto_examples/07_advanced/images/sphx_glr_plot_neurovault_meta_analysis_001.png :alt: plot neurovault meta analysis :srcset: /auto_examples/07_advanced/images/sphx_glr_plot_neurovault_meta_analysis_001.png :class: sphx-glr-multi-img * .. image-sg:: /auto_examples/07_advanced/images/sphx_glr_plot_neurovault_meta_analysis_002.png :alt: plot neurovault meta analysis :srcset: /auto_examples/07_advanced/images/sphx_glr_plot_neurovault_meta_analysis_002.png :class: sphx-glr-multi-img * .. image-sg:: /auto_examples/07_advanced/images/sphx_glr_plot_neurovault_meta_analysis_003.png :alt: plot neurovault meta analysis :srcset: /auto_examples/07_advanced/images/sphx_glr_plot_neurovault_meta_analysis_003.png :class: sphx-glr-multi-img * .. image-sg:: /auto_examples/07_advanced/images/sphx_glr_plot_neurovault_meta_analysis_004.png :alt: plot neurovault meta analysis :srcset: /auto_examples/07_advanced/images/sphx_glr_plot_neurovault_meta_analysis_004.png :class: sphx-glr-multi-img * .. image-sg:: /auto_examples/07_advanced/images/sphx_glr_plot_neurovault_meta_analysis_005.png :alt: plot neurovault meta analysis :srcset: /auto_examples/07_advanced/images/sphx_glr_plot_neurovault_meta_analysis_005.png :class: sphx-glr-multi-img * .. image-sg:: /auto_examples/07_advanced/images/sphx_glr_plot_neurovault_meta_analysis_006.png :alt: plot neurovault meta analysis :srcset: /auto_examples/07_advanced/images/sphx_glr_plot_neurovault_meta_analysis_006.png :class: sphx-glr-multi-img * .. image-sg:: /auto_examples/07_advanced/images/sphx_glr_plot_neurovault_meta_analysis_007.png :alt: plot neurovault meta analysis :srcset: /auto_examples/07_advanced/images/sphx_glr_plot_neurovault_meta_analysis_007.png :class: sphx-glr-multi-img .. rst-class:: sphx-glr-script-out Out: .. code-block:: none plotting glass brain for collected images .. GENERATED FROM PYTHON SOURCE LINES 59-61 Compute statistics ------------------ .. GENERATED FROM PYTHON SOURCE LINES 61-96 .. code-block:: default def t_to_z(t_scores, deg_of_freedom): p_values = scipy.stats.t.sf(t_scores, df=deg_of_freedom) z_values = scipy.stats.norm.isf(p_values) return z_values # Compute z values mean_maps = [] z_imgs = [] current_collection = None print("\nComputing maps...") # convert t to z for all images for this_meta in images_meta: if this_meta['collection_id'] != current_collection: print("\n\nCollection {0}:".format(this_meta['id'])) current_collection = this_meta['collection_id'] # Load and validate the downloaded image. t_img = load_img(this_meta['absolute_path']) deg_of_freedom = this_meta['number_of_subjects'] - 2 print(" Image {1}: degrees of freedom: {2}".format( "", this_meta['id'], deg_of_freedom)) # Convert data, create new image. z_img = new_img_like( t_img, t_to_z(get_data(t_img), deg_of_freedom=deg_of_freedom)) z_imgs.append(z_img) .. rst-class:: sphx-glr-script-out Out: .. code-block:: none Computing maps... Collection 3042: Image 3042: degrees of freedom: 22 Collection 2818: Image 2818: degrees of freedom: 18 Image 2834: degrees of freedom: 18 Collection 2675: Image 2675: degrees of freedom: 6 Image 2676: degrees of freedom: 6 Collection 151: Image 151: degrees of freedom: 13 Image 3041: degrees of freedom: 13 .. GENERATED FROM PYTHON SOURCE LINES 97-99 Plot the combined z maps ------------------------ .. GENERATED FROM PYTHON SOURCE LINES 99-110 .. code-block:: default cut_coords = [-15, -8, 6, 30, 46, 62] meta_analysis_img = math_img( 'np.sum(z_imgs, axis=3) / np.sqrt(z_imgs.shape[3])', z_imgs=z_imgs) plotting.plot_stat_map(meta_analysis_img, display_mode='z', threshold=6, cut_coords=cut_coords, vmax=12) plotting.show() .. image-sg:: /auto_examples/07_advanced/images/sphx_glr_plot_neurovault_meta_analysis_008.png :alt: plot neurovault meta analysis :srcset: /auto_examples/07_advanced/images/sphx_glr_plot_neurovault_meta_analysis_008.png :class: sphx-glr-single-img .. rst-class:: sphx-glr-timing **Total running time of the script:** ( 0 minutes 18.696 seconds) **Estimated memory usage:** 41 MB .. _sphx_glr_download_auto_examples_07_advanced_plot_neurovault_meta_analysis.py: .. only :: html .. container:: sphx-glr-footer :class: sphx-glr-footer-example .. container:: binder-badge .. image:: images/binder_badge_logo.svg :target: https://mybinder.org/v2/gh/nilearn/nilearn.github.io/main?filepath=examples/auto_examples/07_advanced/plot_neurovault_meta_analysis.ipynb :alt: Launch binder :width: 150 px .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_neurovault_meta_analysis.py ` .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_neurovault_meta_analysis.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_