Note
Go to the end to download the full example code. or to run this example in your browser via Binder
NeuroVault cross-study ICA maps¶
This example shows how to download statistical maps from NeuroVault, label them with NeuroSynth terms, and compute ICA components across all the maps.
See fetch_neurovault
documentation for more details.
import numpy as np
from scipy import stats
from sklearn.decomposition import FastICA
from nilearn.datasets import fetch_neurovault, load_mni152_brain_mask
from nilearn.image import smooth_img
from nilearn.maskers import NiftiMasker
from nilearn.plotting import plot_stat_map, show
Get image and term data¶
# Download images
# Here by default we only download 80 images to save time,
# but for better results I recommend using at least 200.
print(
"Fetching Neurovault images; "
"if you haven't downloaded any Neurovault data before "
"this will take several minutes."
)
nv_data = fetch_neurovault(
max_images=30, fetch_neurosynth_words=True, timeout=30.0
)
images = nv_data["images"]
term_weights = nv_data["word_frequencies"]
vocabulary = nv_data["vocabulary"]
if term_weights is None:
term_weights = np.ones((len(images), 2))
vocabulary = np.asarray(["Neurosynth is down", "Please try again later"])
# Clean and report term scores
term_weights[term_weights < 0] = 0
total_scores = np.mean(term_weights, axis=0)
print("\nTop 10 neurosynth terms from downloaded images:\n")
for term_idx in np.argsort(total_scores)[-10:][::-1]:
print(vocabulary[term_idx])
Fetching Neurovault images; if you haven't downloaded any Neurovault data before this will take several minutes.
[fetch_neurovault] Dataset directory found:
/home/runner/work/nilearn/nilearn/nilearn_data/neurovault
[fetch_neurovault] Reading local neurovault data.
[fetch_neurovault] Downloading file:
https://neurosynth.org/api/decode/?neurovault=32980
[fetch_neurovault] Download succeeded, downloaded to: /home/runner/work/nilearn/
nilearn/nilearn_data/neurovault/collection_1952/neurosynth_words_for_image_32980
.json
[fetch_neurovault] Already fetched 1 image
[fetch_neurovault] Already fetched 2 images
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[fetch_neurovault] Already fetched 30 images
[fetch_neurovault] 30 images found on local disk.
[fetch_neurovault] Computing word features.
[fetch_neurovault] Computing word features done; vocabulary size: 1315
Top 10 neurosynth terms from downloaded images:
task
superior temporal
parietal
anterior insula
tasks
working memory
posterior superior
auditory
working
superior
Reshape and mask images¶
import warnings
print("\nReshaping and masking images.\n")
mask_img = load_mni152_brain_mask(resolution=2)
masker = NiftiMasker(
mask_img=mask_img, memory="nilearn_cache", memory_level=1, verbose=1
)
masker = masker.fit()
# Images may fail to be transformed, and are of different shapes,
# so we need to transform one-by-one and keep track of failures.
X = []
is_usable = np.ones((len(images),), dtype=bool)
for index, image_path in enumerate(images):
# load image and remove nan and inf values.
# applying smooth_img to an image with fwhm=None simply cleans up
# non-finite values but otherwise doesn't modify the image.
image = smooth_img(image_path, fwhm=None)
try:
with warnings.catch_warnings():
warnings.simplefilter("ignore")
X.append(masker.transform(image))
except Exception as e:
meta = nv_data["images_meta"][index]
print(
f"Failed to mask/reshape image: id: {meta.get('id')}; "
f"name: '{meta.get('name')}'; "
f"collection: {meta.get('collection_id')}; error: {e}"
)
is_usable[index] = False
# Now reshape list into 2D matrix, and remove failed images from terms
X = np.vstack(X)
term_weights = term_weights[is_usable, :]
Reshaping and masking images.
\[NiftiMasker.fit] Loading mask from <nibabel.nifti1.Nifti1Image object at
0x7f80fd9e5bd0>
\[NiftiMasker.fit] Resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>, target_affine=None, target_shape=None, copy=False, interpolation='nearest')
_____________________________________________________resample_img - 0.0s, 0.0min
\[NiftiMasker.fit] Finished fit
________________________________________________________________________________
[Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask...
filter_and_mask(<nibabel.nifti1.Nifti1Image object at 0x7f80fd9e4700>, <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>, { 'clean_args': None,
'clean_kwargs': {},
'cmap': 'gray',
'detrend': False,
'dtype': None,
'high_pass': None,
'high_variance_confounds': False,
'low_pass': None,
'reports': True,
'runs': None,
'smoothing_fwhm': None,
'standardize': False,
'standardize_confounds': True,
't_r': None,
'target_affine': None,
'target_shape': None}, memory_level=1, memory=Memory(location=nilearn_cache/joblib), verbose=1, confounds=None, sample_mask=None, copy=True, sklearn_output_config=None)
\[NiftiMasker.wrapped] Loading data from <nibabel.nifti1.Nifti1Image object at
0x7f810e4d5870>
\[NiftiMasker.wrapped] Resampling images
\[NiftiMasker.wrapped] Extracting region signals
\[NiftiMasker.wrapped] Cleaning extracted signals
__________________________________________________filter_and_mask - 0.3s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask...
filter_and_mask(<nibabel.nifti1.Nifti1Image object at 0x7f810e4d6fb0>, <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>, { 'clean_args': None,
'clean_kwargs': {},
'cmap': 'gray',
'detrend': False,
'dtype': None,
'high_pass': None,
'high_variance_confounds': False,
'low_pass': None,
'reports': True,
'runs': None,
'smoothing_fwhm': None,
'standardize': False,
'standardize_confounds': True,
't_r': None,
'target_affine': None,
'target_shape': None}, memory_level=1, memory=Memory(location=nilearn_cache/joblib), verbose=1, confounds=None, sample_mask=None, copy=True, sklearn_output_config=None)
\[NiftiMasker.wrapped] Loading data from <nibabel.nifti1.Nifti1Image object at
0x7f810e4d7b80>
\[NiftiMasker.wrapped] Resampling images
\[NiftiMasker.wrapped] Extracting region signals
\[NiftiMasker.wrapped] Cleaning extracted signals
__________________________________________________filter_and_mask - 0.2s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask...
filter_and_mask(<nibabel.nifti1.Nifti1Image object at 0x7f80fd9e4340>, <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>, { 'clean_args': None,
'clean_kwargs': {},
'cmap': 'gray',
'detrend': False,
'dtype': None,
'high_pass': None,
'high_variance_confounds': False,
'low_pass': None,
'reports': True,
'runs': None,
'smoothing_fwhm': None,
'standardize': False,
'standardize_confounds': True,
't_r': None,
'target_affine': None,
'target_shape': None}, memory_level=1, memory=Memory(location=nilearn_cache/joblib), verbose=1, confounds=None, sample_mask=None, copy=True, sklearn_output_config=None)
\[NiftiMasker.wrapped] Loading data from <nibabel.nifti1.Nifti1Image object at
0x7f810e4d7d90>
\[NiftiMasker.wrapped] Resampling images
\[NiftiMasker.wrapped] Extracting region signals
\[NiftiMasker.wrapped] Cleaning extracted signals
__________________________________________________filter_and_mask - 0.2s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask...
filter_and_mask(<nibabel.nifti1.Nifti1Image object at 0x7f810e4d4a00>, <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>, { 'clean_args': None,
'clean_kwargs': {},
'cmap': 'gray',
'detrend': False,
'dtype': None,
'high_pass': None,
'high_variance_confounds': False,
'low_pass': None,
'reports': True,
'runs': None,
'smoothing_fwhm': None,
'standardize': False,
'standardize_confounds': True,
't_r': None,
'target_affine': None,
'target_shape': None}, memory_level=1, memory=Memory(location=nilearn_cache/joblib), verbose=1, confounds=None, sample_mask=None, copy=True, sklearn_output_config=None)
\[NiftiMasker.wrapped] Loading data from <nibabel.nifti1.Nifti1Image object at
0x7f810e4d6560>
\[NiftiMasker.wrapped] Resampling images
\[NiftiMasker.wrapped] Extracting region signals
\[NiftiMasker.wrapped] Cleaning extracted signals
__________________________________________________filter_and_mask - 0.2s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask...
filter_and_mask(<nibabel.nifti1.Nifti1Image object at 0x7f810e4d5ea0>, <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>, { 'clean_args': None,
'clean_kwargs': {},
'cmap': 'gray',
'detrend': False,
'dtype': None,
'high_pass': None,
'high_variance_confounds': False,
'low_pass': None,
'reports': True,
'runs': None,
'smoothing_fwhm': None,
'standardize': False,
'standardize_confounds': True,
't_r': None,
'target_affine': None,
'target_shape': None}, memory_level=1, memory=Memory(location=nilearn_cache/joblib), verbose=1, confounds=None, sample_mask=None, copy=True, sklearn_output_config=None)
\[NiftiMasker.wrapped] Loading data from <nibabel.nifti1.Nifti1Image object at
0x7f80fd9e4f70>
\[NiftiMasker.wrapped] Resampling images
\[NiftiMasker.wrapped] Extracting region signals
\[NiftiMasker.wrapped] Cleaning extracted signals
__________________________________________________filter_and_mask - 0.2s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask...
filter_and_mask(<nibabel.nifti1.Nifti1Image object at 0x7f810e4d4eb0>, <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>, { 'clean_args': None,
'clean_kwargs': {},
'cmap': 'gray',
'detrend': False,
'dtype': None,
'high_pass': None,
'high_variance_confounds': False,
'low_pass': None,
'reports': True,
'runs': None,
'smoothing_fwhm': None,
'standardize': False,
'standardize_confounds': True,
't_r': None,
'target_affine': None,
'target_shape': None}, memory_level=1, memory=Memory(location=nilearn_cache/joblib), verbose=1, confounds=None, sample_mask=None, copy=True, sklearn_output_config=None)
\[NiftiMasker.wrapped] Loading data from <nibabel.nifti1.Nifti1Image object at
0x7f810e4d4760>
\[NiftiMasker.wrapped] Resampling images
\[NiftiMasker.wrapped] Extracting region signals
\[NiftiMasker.wrapped] Cleaning extracted signals
__________________________________________________filter_and_mask - 0.2s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask...
filter_and_mask(<nibabel.nifti1.Nifti1Image object at 0x7f810e4d5f60>, <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>, { 'clean_args': None,
'clean_kwargs': {},
'cmap': 'gray',
'detrend': False,
'dtype': None,
'high_pass': None,
'high_variance_confounds': False,
'low_pass': None,
'reports': True,
'runs': None,
'smoothing_fwhm': None,
'standardize': False,
'standardize_confounds': True,
't_r': None,
'target_affine': None,
'target_shape': None}, memory_level=1, memory=Memory(location=nilearn_cache/joblib), verbose=1, confounds=None, sample_mask=None, copy=True, sklearn_output_config=None)
\[NiftiMasker.wrapped] Loading data from <nibabel.nifti1.Nifti1Image object at
0x7f810e4d4be0>
\[NiftiMasker.wrapped] Resampling images
\[NiftiMasker.wrapped] Extracting region signals
\[NiftiMasker.wrapped] Cleaning extracted signals
__________________________________________________filter_and_mask - 0.2s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask...
filter_and_mask(<nibabel.nifti1.Nifti1Image object at 0x7f80fd9e4700>, <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>, { 'clean_args': None,
'clean_kwargs': {},
'cmap': 'gray',
'detrend': False,
'dtype': None,
'high_pass': None,
'high_variance_confounds': False,
'low_pass': None,
'reports': True,
'runs': None,
'smoothing_fwhm': None,
'standardize': False,
'standardize_confounds': True,
't_r': None,
'target_affine': None,
'target_shape': None}, memory_level=1, memory=Memory(location=nilearn_cache/joblib), verbose=1, confounds=None, sample_mask=None, copy=True, sklearn_output_config=None)
\[NiftiMasker.wrapped] Loading data from <nibabel.nifti1.Nifti1Image object at
0x7f810e4d44f0>
\[NiftiMasker.wrapped] Resampling images
\[NiftiMasker.wrapped] Extracting region signals
\[NiftiMasker.wrapped] Cleaning extracted signals
__________________________________________________filter_and_mask - 0.2s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask...
filter_and_mask(<nibabel.nifti1.Nifti1Image object at 0x7f810e4d7d00>, <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>, { 'clean_args': None,
'clean_kwargs': {},
'cmap': 'gray',
'detrend': False,
'dtype': None,
'high_pass': None,
'high_variance_confounds': False,
'low_pass': None,
'reports': True,
'runs': None,
'smoothing_fwhm': None,
'standardize': False,
'standardize_confounds': True,
't_r': None,
'target_affine': None,
'target_shape': None}, memory_level=1, memory=Memory(location=nilearn_cache/joblib), verbose=1, confounds=None, sample_mask=None, copy=True, sklearn_output_config=None)
\[NiftiMasker.wrapped] Loading data from <nibabel.nifti1.Nifti1Image object at
0x7f810e4d7f10>
\[NiftiMasker.wrapped] Resampling images
\[NiftiMasker.wrapped] Extracting region signals
\[NiftiMasker.wrapped] Cleaning extracted signals
__________________________________________________filter_and_mask - 0.2s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask...
filter_and_mask(<nibabel.nifti1.Nifti1Image object at 0x7f80fd9e4700>, <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>, { 'clean_args': None,
'clean_kwargs': {},
'cmap': 'gray',
'detrend': False,
'dtype': None,
'high_pass': None,
'high_variance_confounds': False,
'low_pass': None,
'reports': True,
'runs': None,
'smoothing_fwhm': None,
'standardize': False,
'standardize_confounds': True,
't_r': None,
'target_affine': None,
'target_shape': None}, memory_level=1, memory=Memory(location=nilearn_cache/joblib), verbose=1, confounds=None, sample_mask=None, copy=True, sklearn_output_config=None)
\[NiftiMasker.wrapped] Loading data from <nibabel.nifti1.Nifti1Image object at
0x7f810e4d63b0>
\[NiftiMasker.wrapped] Resampling images
\[NiftiMasker.wrapped] Extracting region signals
\[NiftiMasker.wrapped] Cleaning extracted signals
__________________________________________________filter_and_mask - 0.2s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask...
filter_and_mask(<nibabel.nifti1.Nifti1Image object at 0x7f810e4d5300>, <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>, { 'clean_args': None,
'clean_kwargs': {},
'cmap': 'gray',
'detrend': False,
'dtype': None,
'high_pass': None,
'high_variance_confounds': False,
'low_pass': None,
'reports': True,
'runs': None,
'smoothing_fwhm': None,
'standardize': False,
'standardize_confounds': True,
't_r': None,
'target_affine': None,
'target_shape': None}, memory_level=1, memory=Memory(location=nilearn_cache/joblib), verbose=1, confounds=None, sample_mask=None, copy=True, sklearn_output_config=None)
\[NiftiMasker.wrapped] Loading data from <nibabel.nifti1.Nifti1Image object at
0x7f810e4d7df0>
\[NiftiMasker.wrapped] Resampling images
\[NiftiMasker.wrapped] Extracting region signals
\[NiftiMasker.wrapped] Cleaning extracted signals
__________________________________________________filter_and_mask - 0.2s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask...
filter_and_mask(<nibabel.nifti1.Nifti1Image object at 0x7f810e4d7c40>, <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>, { 'clean_args': None,
'clean_kwargs': {},
'cmap': 'gray',
'detrend': False,
'dtype': None,
'high_pass': None,
'high_variance_confounds': False,
'low_pass': None,
'reports': True,
'runs': None,
'smoothing_fwhm': None,
'standardize': False,
'standardize_confounds': True,
't_r': None,
'target_affine': None,
'target_shape': None}, memory_level=1, memory=Memory(location=nilearn_cache/joblib), verbose=1, confounds=None, sample_mask=None, copy=True, sklearn_output_config=None)
\[NiftiMasker.wrapped] Loading data from <nibabel.nifti1.Nifti1Image object at
0x7f810e4d5d50>
\[NiftiMasker.wrapped] Resampling images
\[NiftiMasker.wrapped] Extracting region signals
\[NiftiMasker.wrapped] Cleaning extracted signals
__________________________________________________filter_and_mask - 0.2s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask...
filter_and_mask(<nibabel.nifti1.Nifti1Image object at 0x7f810e4d5300>, <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>, { 'clean_args': None,
'clean_kwargs': {},
'cmap': 'gray',
'detrend': False,
'dtype': None,
'high_pass': None,
'high_variance_confounds': False,
'low_pass': None,
'reports': True,
'runs': None,
'smoothing_fwhm': None,
'standardize': False,
'standardize_confounds': True,
't_r': None,
'target_affine': None,
'target_shape': None}, memory_level=1, memory=Memory(location=nilearn_cache/joblib), verbose=1, confounds=None, sample_mask=None, copy=True, sklearn_output_config=None)
\[NiftiMasker.wrapped] Loading data from <nibabel.nifti1.Nifti1Image object at
0x7f810e4d4f10>
\[NiftiMasker.wrapped] Resampling images
\[NiftiMasker.wrapped] Extracting region signals
\[NiftiMasker.wrapped] Cleaning extracted signals
__________________________________________________filter_and_mask - 0.2s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask...
filter_and_mask(<nibabel.nifti1.Nifti1Image object at 0x7f810e4d7e80>, <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>, { 'clean_args': None,
'clean_kwargs': {},
'cmap': 'gray',
'detrend': False,
'dtype': None,
'high_pass': None,
'high_variance_confounds': False,
'low_pass': None,
'reports': True,
'runs': None,
'smoothing_fwhm': None,
'standardize': False,
'standardize_confounds': True,
't_r': None,
'target_affine': None,
'target_shape': None}, memory_level=1, memory=Memory(location=nilearn_cache/joblib), verbose=1, confounds=None, sample_mask=None, copy=True, sklearn_output_config=None)
\[NiftiMasker.wrapped] Loading data from <nibabel.nifti1.Nifti1Image object at
0x7f810e4d5480>
\[NiftiMasker.wrapped] Resampling images
\[NiftiMasker.wrapped] Extracting region signals
\[NiftiMasker.wrapped] Cleaning extracted signals
__________________________________________________filter_and_mask - 0.2s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask...
filter_and_mask(<nibabel.nifti1.Nifti1Image object at 0x7f80fd9e4f70>, <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>, { 'clean_args': None,
'clean_kwargs': {},
'cmap': 'gray',
'detrend': False,
'dtype': None,
'high_pass': None,
'high_variance_confounds': False,
'low_pass': None,
'reports': True,
'runs': None,
'smoothing_fwhm': None,
'standardize': False,
'standardize_confounds': True,
't_r': None,
'target_affine': None,
'target_shape': None}, memory_level=1, memory=Memory(location=nilearn_cache/joblib), verbose=1, confounds=None, sample_mask=None, copy=True, sklearn_output_config=None)
\[NiftiMasker.wrapped] Loading data from <nibabel.nifti1.Nifti1Image object at
0x7f810e4d41f0>
\[NiftiMasker.wrapped] Resampling images
\[NiftiMasker.wrapped] Extracting region signals
\[NiftiMasker.wrapped] Cleaning extracted signals
__________________________________________________filter_and_mask - 0.2s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask...
filter_and_mask(<nibabel.nifti1.Nifti1Image object at 0x7f810e4d5ea0>, <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>, { 'clean_args': None,
'clean_kwargs': {},
'cmap': 'gray',
'detrend': False,
'dtype': None,
'high_pass': None,
'high_variance_confounds': False,
'low_pass': None,
'reports': True,
'runs': None,
'smoothing_fwhm': None,
'standardize': False,
'standardize_confounds': True,
't_r': None,
'target_affine': None,
'target_shape': None}, memory_level=1, memory=Memory(location=nilearn_cache/joblib), verbose=1, confounds=None, sample_mask=None, copy=True, sklearn_output_config=None)
\[NiftiMasker.wrapped] Loading data from <nibabel.nifti1.Nifti1Image object at
0x7f810e4d60b0>
\[NiftiMasker.wrapped] Resampling images
\[NiftiMasker.wrapped] Extracting region signals
\[NiftiMasker.wrapped] Cleaning extracted signals
__________________________________________________filter_and_mask - 0.2s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask...
filter_and_mask(<nibabel.nifti1.Nifti1Image object at 0x7f810e4d42b0>, <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>, { 'clean_args': None,
'clean_kwargs': {},
'cmap': 'gray',
'detrend': False,
'dtype': None,
'high_pass': None,
'high_variance_confounds': False,
'low_pass': None,
'reports': True,
'runs': None,
'smoothing_fwhm': None,
'standardize': False,
'standardize_confounds': True,
't_r': None,
'target_affine': None,
'target_shape': None}, memory_level=1, memory=Memory(location=nilearn_cache/joblib), verbose=1, confounds=None, sample_mask=None, copy=True, sklearn_output_config=None)
\[NiftiMasker.wrapped] Loading data from <nibabel.nifti1.Nifti1Image object at
0x7f810e4d6d70>
\[NiftiMasker.wrapped] Resampling images
\[NiftiMasker.wrapped] Extracting region signals
\[NiftiMasker.wrapped] Cleaning extracted signals
__________________________________________________filter_and_mask - 0.2s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask...
filter_and_mask(<nibabel.nifti1.Nifti1Image object at 0x7f810e4d7040>, <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>, { 'clean_args': None,
'clean_kwargs': {},
'cmap': 'gray',
'detrend': False,
'dtype': None,
'high_pass': None,
'high_variance_confounds': False,
'low_pass': None,
'reports': True,
'runs': None,
'smoothing_fwhm': None,
'standardize': False,
'standardize_confounds': True,
't_r': None,
'target_affine': None,
'target_shape': None}, memory_level=1, memory=Memory(location=nilearn_cache/joblib), verbose=1, confounds=None, sample_mask=None, copy=True, sklearn_output_config=None)
\[NiftiMasker.wrapped] Loading data from <nibabel.nifti1.Nifti1Image object at
0x7f810e4d6020>
\[NiftiMasker.wrapped] Resampling images
\[NiftiMasker.wrapped] Extracting region signals
\[NiftiMasker.wrapped] Cleaning extracted signals
__________________________________________________filter_and_mask - 0.2s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask...
filter_and_mask(<nibabel.nifti1.Nifti1Image object at 0x7f810e4d7ac0>, <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>, { 'clean_args': None,
'clean_kwargs': {},
'cmap': 'gray',
'detrend': False,
'dtype': None,
'high_pass': None,
'high_variance_confounds': False,
'low_pass': None,
'reports': True,
'runs': None,
'smoothing_fwhm': None,
'standardize': False,
'standardize_confounds': True,
't_r': None,
'target_affine': None,
'target_shape': None}, memory_level=1, memory=Memory(location=nilearn_cache/joblib), verbose=1, confounds=None, sample_mask=None, copy=True, sklearn_output_config=None)
\[NiftiMasker.wrapped] Loading data from <nibabel.nifti1.Nifti1Image object at
0x7f810e4d5180>
\[NiftiMasker.wrapped] Resampling images
\[NiftiMasker.wrapped] Extracting region signals
\[NiftiMasker.wrapped] Cleaning extracted signals
__________________________________________________filter_and_mask - 0.2s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask...
filter_and_mask(<nibabel.nifti1.Nifti1Image object at 0x7f810e4d5780>, <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>, { 'clean_args': None,
'clean_kwargs': {},
'cmap': 'gray',
'detrend': False,
'dtype': None,
'high_pass': None,
'high_variance_confounds': False,
'low_pass': None,
'reports': True,
'runs': None,
'smoothing_fwhm': None,
'standardize': False,
'standardize_confounds': True,
't_r': None,
'target_affine': None,
'target_shape': None}, memory_level=1, memory=Memory(location=nilearn_cache/joblib), verbose=1, confounds=None, sample_mask=None, copy=True, sklearn_output_config=None)
\[NiftiMasker.wrapped] Loading data from <nibabel.nifti1.Nifti1Image object at
0x7f810e4d5ba0>
\[NiftiMasker.wrapped] Resampling images
\[NiftiMasker.wrapped] Extracting region signals
\[NiftiMasker.wrapped] Cleaning extracted signals
__________________________________________________filter_and_mask - 0.2s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask...
filter_and_mask(<nibabel.nifti1.Nifti1Image object at 0x7f810e4d6e00>, <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>, { 'clean_args': None,
'clean_kwargs': {},
'cmap': 'gray',
'detrend': False,
'dtype': None,
'high_pass': None,
'high_variance_confounds': False,
'low_pass': None,
'reports': True,
'runs': None,
'smoothing_fwhm': None,
'standardize': False,
'standardize_confounds': True,
't_r': None,
'target_affine': None,
'target_shape': None}, memory_level=1, memory=Memory(location=nilearn_cache/joblib), verbose=1, confounds=None, sample_mask=None, copy=True, sklearn_output_config=None)
\[NiftiMasker.wrapped] Loading data from <nibabel.nifti1.Nifti1Image object at
0x7f810e4d5ba0>
\[NiftiMasker.wrapped] Resampling images
\[NiftiMasker.wrapped] Extracting region signals
\[NiftiMasker.wrapped] Cleaning extracted signals
__________________________________________________filter_and_mask - 0.2s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask...
filter_and_mask(<nibabel.nifti1.Nifti1Image object at 0x7f810e4d5ae0>, <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>, { 'clean_args': None,
'clean_kwargs': {},
'cmap': 'gray',
'detrend': False,
'dtype': None,
'high_pass': None,
'high_variance_confounds': False,
'low_pass': None,
'reports': True,
'runs': None,
'smoothing_fwhm': None,
'standardize': False,
'standardize_confounds': True,
't_r': None,
'target_affine': None,
'target_shape': None}, memory_level=1, memory=Memory(location=nilearn_cache/joblib), verbose=1, confounds=None, sample_mask=None, copy=True, sklearn_output_config=None)
\[NiftiMasker.wrapped] Loading data from <nibabel.nifti1.Nifti1Image object at
0x7f810e4d7be0>
\[NiftiMasker.wrapped] Resampling images
\[NiftiMasker.wrapped] Extracting region signals
\[NiftiMasker.wrapped] Cleaning extracted signals
__________________________________________________filter_and_mask - 0.3s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask...
filter_and_mask(<nibabel.nifti1.Nifti1Image object at 0x7f8102145300>, <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>, { 'clean_args': None,
'clean_kwargs': {},
'cmap': 'gray',
'detrend': False,
'dtype': None,
'high_pass': None,
'high_variance_confounds': False,
'low_pass': None,
'reports': True,
'runs': None,
'smoothing_fwhm': None,
'standardize': False,
'standardize_confounds': True,
't_r': None,
'target_affine': None,
'target_shape': None}, memory_level=1, memory=Memory(location=nilearn_cache/joblib), verbose=1, confounds=None, sample_mask=None, copy=True, sklearn_output_config=None)
\[NiftiMasker.wrapped] Loading data from <nibabel.nifti1.Nifti1Image object at
0x7f8102147790>
\[NiftiMasker.wrapped] Resampling images
\[NiftiMasker.wrapped] Extracting region signals
\[NiftiMasker.wrapped] Cleaning extracted signals
__________________________________________________filter_and_mask - 0.3s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask...
filter_and_mask(<nibabel.nifti1.Nifti1Image object at 0x7f810e4d6650>, <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>, { 'clean_args': None,
'clean_kwargs': {},
'cmap': 'gray',
'detrend': False,
'dtype': None,
'high_pass': None,
'high_variance_confounds': False,
'low_pass': None,
'reports': True,
'runs': None,
'smoothing_fwhm': None,
'standardize': False,
'standardize_confounds': True,
't_r': None,
'target_affine': None,
'target_shape': None}, memory_level=1, memory=Memory(location=nilearn_cache/joblib), verbose=1, confounds=None, sample_mask=None, copy=True, sklearn_output_config=None)
\[NiftiMasker.wrapped] Loading data from <nibabel.nifti1.Nifti1Image object at
0x7f810e4d6620>
\[NiftiMasker.wrapped] Resampling images
\[NiftiMasker.wrapped] Extracting region signals
\[NiftiMasker.wrapped] Cleaning extracted signals
__________________________________________________filter_and_mask - 0.3s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask...
filter_and_mask(<nibabel.nifti1.Nifti1Image object at 0x7f810e4d7580>, <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>, { 'clean_args': None,
'clean_kwargs': {},
'cmap': 'gray',
'detrend': False,
'dtype': None,
'high_pass': None,
'high_variance_confounds': False,
'low_pass': None,
'reports': True,
'runs': None,
'smoothing_fwhm': None,
'standardize': False,
'standardize_confounds': True,
't_r': None,
'target_affine': None,
'target_shape': None}, memory_level=1, memory=Memory(location=nilearn_cache/joblib), verbose=1, confounds=None, sample_mask=None, copy=True, sklearn_output_config=None)
\[NiftiMasker.wrapped] Loading data from <nibabel.nifti1.Nifti1Image object at
0x7f810e4d78e0>
\[NiftiMasker.wrapped] Resampling images
\[NiftiMasker.wrapped] Extracting region signals
\[NiftiMasker.wrapped] Cleaning extracted signals
__________________________________________________filter_and_mask - 0.3s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask...
filter_and_mask(<nibabel.nifti1.Nifti1Image object at 0x7f810e4d5360>, <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>, { 'clean_args': None,
'clean_kwargs': {},
'cmap': 'gray',
'detrend': False,
'dtype': None,
'high_pass': None,
'high_variance_confounds': False,
'low_pass': None,
'reports': True,
'runs': None,
'smoothing_fwhm': None,
'standardize': False,
'standardize_confounds': True,
't_r': None,
'target_affine': None,
'target_shape': None}, memory_level=1, memory=Memory(location=nilearn_cache/joblib), verbose=1, confounds=None, sample_mask=None, copy=True, sklearn_output_config=None)
\[NiftiMasker.wrapped] Loading data from <nibabel.nifti1.Nifti1Image object at
0x7f810e4d4280>
\[NiftiMasker.wrapped] Resampling images
\[NiftiMasker.wrapped] Extracting region signals
\[NiftiMasker.wrapped] Cleaning extracted signals
__________________________________________________filter_and_mask - 0.3s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask...
filter_and_mask(<nibabel.nifti1.Nifti1Image object at 0x7f80fc8bfeb0>, <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>, { 'clean_args': None,
'clean_kwargs': {},
'cmap': 'gray',
'detrend': False,
'dtype': None,
'high_pass': None,
'high_variance_confounds': False,
'low_pass': None,
'reports': True,
'runs': None,
'smoothing_fwhm': None,
'standardize': False,
'standardize_confounds': True,
't_r': None,
'target_affine': None,
'target_shape': None}, memory_level=1, memory=Memory(location=nilearn_cache/joblib), verbose=1, confounds=None, sample_mask=None, copy=True, sklearn_output_config=None)
\[NiftiMasker.wrapped] Loading data from <nibabel.nifti1.Nifti1Image object at
0x7f8126de2aa0>
\[NiftiMasker.wrapped] Resampling images
\[NiftiMasker.wrapped] Extracting region signals
\[NiftiMasker.wrapped] Cleaning extracted signals
__________________________________________________filter_and_mask - 0.3s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask...
filter_and_mask(<nibabel.nifti1.Nifti1Image object at 0x7f81260c9ff0>, <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>, { 'clean_args': None,
'clean_kwargs': {},
'cmap': 'gray',
'detrend': False,
'dtype': None,
'high_pass': None,
'high_variance_confounds': False,
'low_pass': None,
'reports': True,
'runs': None,
'smoothing_fwhm': None,
'standardize': False,
'standardize_confounds': True,
't_r': None,
'target_affine': None,
'target_shape': None}, memory_level=1, memory=Memory(location=nilearn_cache/joblib), verbose=1, confounds=None, sample_mask=None, copy=True, sklearn_output_config=None)
\[NiftiMasker.wrapped] Loading data from <nibabel.nifti1.Nifti1Image object at
0x7f8126de3130>
\[NiftiMasker.wrapped] Resampling images
\[NiftiMasker.wrapped] Extracting region signals
\[NiftiMasker.wrapped] Cleaning extracted signals
__________________________________________________filter_and_mask - 0.3s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask...
filter_and_mask(<nibabel.nifti1.Nifti1Image object at 0x7f81260ca7a0>, <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>, { 'clean_args': None,
'clean_kwargs': {},
'cmap': 'gray',
'detrend': False,
'dtype': None,
'high_pass': None,
'high_variance_confounds': False,
'low_pass': None,
'reports': True,
'runs': None,
'smoothing_fwhm': None,
'standardize': False,
'standardize_confounds': True,
't_r': None,
'target_affine': None,
'target_shape': None}, memory_level=1, memory=Memory(location=nilearn_cache/joblib), verbose=1, confounds=None, sample_mask=None, copy=True, sklearn_output_config=None)
\[NiftiMasker.wrapped] Loading data from <nibabel.nifti1.Nifti1Image object at
0x7f8126dfb610>
\[NiftiMasker.wrapped] Resampling images
\[NiftiMasker.wrapped] Extracting region signals
\[NiftiMasker.wrapped] Cleaning extracted signals
__________________________________________________filter_and_mask - 0.3s, 0.0min
Run ICA and map components to terms¶
print("Running ICA; may take time...")
# We use a very small number of components as we have downloaded only 80
# images. For better results, increase the number of images downloaded
# and the number of components
n_components = 8
fast_ica = FastICA(n_components=n_components, random_state=0)
ica_maps = fast_ica.fit_transform(X.T).T
term_weights_for_components = np.dot(fast_ica.components_, term_weights)
print("Done, plotting results.")
Running ICA; may take time...
Done, plotting results.
Generate figures¶
for index, (ic_map, ic_terms) in enumerate(
zip(ica_maps, term_weights_for_components, strict=False)
):
if -ic_map.min() > ic_map.max():
# Flip the map's sign for prettiness
ic_map = -ic_map
ic_terms = -ic_terms
ic_threshold = stats.scoreatpercentile(np.abs(ic_map), 90)
ic_img = masker.inverse_transform(ic_map)
important_terms = vocabulary[np.argsort(ic_terms)[-3:]]
title = f"IC{int(index)} {', '.join(important_terms[::-1])}"
plot_stat_map(ic_img, threshold=ic_threshold, colorbar=False, title=title)
\[NiftiMasker.inverse_transform] Computing image from signals
________________________________________________________________________________
[Memory] Calling nilearn.masking.unmask...
unmask(array([-0.470759, ..., -0.468364]), <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>)
___________________________________________________________unmask - 0.1s, 0.0min
\[NiftiMasker.inverse_transform] Computing image from signals
________________________________________________________________________________
[Memory] Calling nilearn.masking.unmask...
unmask(array([0.060853, ..., 0.062147]), <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>)
___________________________________________________________unmask - 0.0s, 0.0min
\[NiftiMasker.inverse_transform] Computing image from signals
________________________________________________________________________________
[Memory] Calling nilearn.masking.unmask...
unmask(array([-0.258327, ..., -0.257222]), <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>)
___________________________________________________________unmask - 0.0s, 0.0min
\[NiftiMasker.inverse_transform] Computing image from signals
________________________________________________________________________________
[Memory] Calling nilearn.masking.unmask...
unmask(array([-0.025708, ..., -0.025104]), <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>)
___________________________________________________________unmask - 0.0s, 0.0min
\[NiftiMasker.inverse_transform] Computing image from signals
________________________________________________________________________________
[Memory] Calling nilearn.masking.unmask...
unmask(array([-0.213691, ..., -0.213687]), <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>)
___________________________________________________________unmask - 0.0s, 0.0min
\[NiftiMasker.inverse_transform] Computing image from signals
________________________________________________________________________________
[Memory] Calling nilearn.masking.unmask...
unmask(array([0.042412, ..., 0.046539]), <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>)
___________________________________________________________unmask - 0.0s, 0.0min
\[NiftiMasker.inverse_transform] Computing image from signals
________________________________________________________________________________
[Memory] Calling nilearn.masking.unmask...
unmask(array([0.143693, ..., 0.140491]), <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>)
___________________________________________________________unmask - 0.0s, 0.0min
\[NiftiMasker.inverse_transform] Computing image from signals
________________________________________________________________________________
[Memory] Calling nilearn.masking.unmask...
unmask(array([-0.108373, ..., -0.116693]), <nibabel.nifti1.Nifti1Image object at 0x7f80fd9e55d0>)
___________________________________________________________unmask - 0.0s, 0.0min
As we can see, some of the components capture cognitive or neurological maps, while other capture noise in the database. More data, better filtering, and better cognitive labels would give better maps
# Done.
show()
Total running time of the script: (0 minutes 15.091 seconds)
Estimated memory usage: 347 MB
