.. 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.
.. 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
Fetch images for "successful stop minus go"-like protocols.
-----------------------------------------------------------
.. 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.
No image found on local disk.
getting new batch: http://neurovault.org/api/images/3041
getting new batch: http://neurovault.org/api/collections/42
Downloading file: https://neurovault.org/media/images/42/task002_cope10_succstop_minus_go.nii.gz
Download succeeded, downloaded to: /home/varoquau/nilearn_data/neurovault/collection_42/image_3041.nii.gz
Already fetched 1 image
getting new batch: http://neurovault.org/api/images/3042
getting new batch: http://neurovault.org/api/collections/98
Downloading file: https://neurovault.org/media/images/98/task002_cope06_succ_stop_vs_go.nii.gz
Download succeeded, downloaded to: /home/varoquau/nilearn_data/neurovault/collection_98/image_3042.nii.gz
Already fetched 2 images
getting new batch: http://neurovault.org/api/images/2818
getting new batch: http://neurovault.org/api/collections/423
Downloading file: https://neurovault.org/media/images/423/task002_cope007_tstat1.nii.gz
Download succeeded, downloaded to: /home/varoquau/nilearn_data/neurovault/collection_423/image_2818.nii.gz
Already fetched 3 images
getting new batch: http://neurovault.org/api/images/2834
Downloading file: https://neurovault.org/media/images/423/task003_cope007_tstat1.nii.gz
Download succeeded, downloaded to: /home/varoquau/nilearn_data/neurovault/collection_423/image_2834.nii.gz
Already fetched 4 images
getting new batch: http://neurovault.org/api/images/2675
getting new batch: http://neurovault.org/api/collections/413
Downloading file: https://neurovault.org/media/images/413/A_model001_task002_cope011_tstat1.nii.gz
Download succeeded, downloaded to: /home/varoquau/nilearn_data/neurovault/collection_413/image_2675.nii.gz
Already fetched 5 images
getting new batch: http://neurovault.org/api/images/2676
Downloading file: https://neurovault.org/media/images/413/B_model001_task002_cope011_tstat1.nii.gz
Download succeeded, downloaded to: /home/varoquau/nilearn_data/neurovault/collection_413/image_2676.nii.gz
Already fetched 6 images
getting new batch: http://neurovault.org/api/images/151
Downloading file: https://neurovault.org/media/images/42/task001_cope07_succstop_minus_go.nii.gz
Download succeeded, downloaded to: /home/varoquau/nilearn_data/neurovault/collection_42/image_151.nii.gz
Already fetched 7 images
Visualize the data
------------------
.. 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:: /auto_examples/07_advanced/images/sphx_glr_plot_neurovault_meta_analysis_001.png
:alt: plot neurovault meta analysis
:class: sphx-glr-multi-img
*
.. image:: /auto_examples/07_advanced/images/sphx_glr_plot_neurovault_meta_analysis_002.png
:alt: plot neurovault meta analysis
:class: sphx-glr-multi-img
*
.. image:: /auto_examples/07_advanced/images/sphx_glr_plot_neurovault_meta_analysis_003.png
:alt: plot neurovault meta analysis
:class: sphx-glr-multi-img
*
.. image:: /auto_examples/07_advanced/images/sphx_glr_plot_neurovault_meta_analysis_004.png
:alt: plot neurovault meta analysis
:class: sphx-glr-multi-img
*
.. image:: /auto_examples/07_advanced/images/sphx_glr_plot_neurovault_meta_analysis_005.png
:alt: plot neurovault meta analysis
:class: sphx-glr-multi-img
*
.. image:: /auto_examples/07_advanced/images/sphx_glr_plot_neurovault_meta_analysis_006.png
:alt: plot neurovault meta analysis
:class: sphx-glr-multi-img
*
.. image:: /auto_examples/07_advanced/images/sphx_glr_plot_neurovault_meta_analysis_007.png
:alt: plot neurovault meta analysis
:class: sphx-glr-multi-img
.. rst-class:: sphx-glr-script-out
Out:
.. code-block:: none
plotting glass brain for collected images
Compute statistics
------------------
.. 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 3041:
Image 3041: degrees of freedom: 13
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
Plot the combined z maps
------------------------
.. 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:: /auto_examples/07_advanced/images/sphx_glr_plot_neurovault_meta_analysis_008.png
:alt: plot neurovault meta analysis
:class: sphx-glr-single-img
.. rst-class:: sphx-glr-timing
**Total running time of the script:** ( 0 minutes 39.107 seconds)
.. _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:: https://mybinder.org/badge_logo.svg
:target: https://mybinder.org/v2/gh/nilearn/nilearn.github.io/master?filepath=examples/auto_examples/07_advanced/plot_neurovault_meta_analysis.ipynb
: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
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