Note
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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] Already fetched 1 image
[fetch_neurovault] Already fetched 2 images
[fetch_neurovault] Already fetched 3 images
[fetch_neurovault] Already fetched 4 images
[fetch_neurovault] Already fetched 5 images
[fetch_neurovault] Already fetched 6 images
[fetch_neurovault] Already fetched 7 images
[fetch_neurovault] Already fetched 8 images
[fetch_neurovault] Already fetched 9 images
[fetch_neurovault] Already fetched 10 images
[fetch_neurovault] Already fetched 11 images
[fetch_neurovault] Already fetched 12 images
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[fetch_neurovault] Already fetched 21 images
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[fetch_neurovault] Already fetched 29 images
[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:
superior temporal
task
auditory
posterior superior
temporal sulcus
anterior insula
superior
temporale
planum temporale
planum
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
0x7efed8c73100>
\[NiftiMasker.fit] Resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, 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 0x7efed8c73ca0>, <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, { '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
0x7efed8c73f10>
\[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 0x7efed8c71060>, <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, { '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
0x7eff081ba530>
\[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 0x7eff081bb9a0>, <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, { '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
0x7eff081bb370>
\[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 0x7efed8c71ab0>, <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, { '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
0x7eff081ba200>
\[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 0x7eff081ba740>, <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, { '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
0x7eff081b8c70>
\[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 0x7efed8c73c40>, <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, { '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
0x7eff081bba30>
\[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 0x7eff081b86a0>, <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, { '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
0x7eff081ba170>
\[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 0x7eff2cfe1e70>, <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, { '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
0x7eff2cfe3af0>
\[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 0x7eff2cfe1c60>, <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, { '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
0x7eff081ba3b0>
\[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 0x7eff081b9f60>, <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, { '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
0x7eff081b9660>
\[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 0x7eff081b92d0>, <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, { '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
0x7eff2cfe3af0>
\[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 0x7eff2cfe05e0>, <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, { '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
0x7eff081bbe20>
\[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 0x7efef8dc7790>, <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, { '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
0x7eff2cfe0dc0>
\[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 0x7eff081b92d0>, <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, { '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
0x7eff2cfe1e70>
\[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 0x7eff2cfe3370>, <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, { '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
0x7eff081bbe20>
\[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 0x7eff2cfe2230>, <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, { '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
0x7efef8dc5090>
\[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 0x7efef13d3970>, <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, { '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
0x7eff2cfe0880>
\[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 0x7efef8dc5240>, <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, { '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
0x7efed8c71ab0>
\[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 0x7efed8c72020>, <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, { '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
0x7efed8c71510>
\[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 0x7efed8c70730>, <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, { '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
0x7eff2cfe0250>
\[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 0x7eff2cfe05e0>, <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, { '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
0x7efef8dc70a0>
\[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 0x7eff080b0430>, <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, { '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
0x7eff2cfe3af0>
\[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 0x7eff2cfe1e70>, <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, { '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
0x7eff08732170>
\[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 0x7eff08732170>, <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, { '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
0x7efed8c70ac0>
\[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 0x7eff2cfe3af0>, <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, { '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
0x7eff2cfe1e70>
\[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 0x7eff081b9210>, <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, { '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
0x7eff081ba650>
\[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 0x7efef8dc4460>, <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, { '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
0x7efed8c720e0>
\[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 0x7eff08731fc0>, <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, { '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
0x7eff081b88b0>
\[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 0x7eff2cfe0250>, <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, { '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
0x7eff08730e20>
\[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 0x7eff081bbdf0>, <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>, { '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
0x7eff081b8c40>
\[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([-0.251969, ..., -0.21535 ]), <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>)
___________________________________________________________unmask - 0.1s, 0.0min
\[NiftiMasker.inverse_transform] Computing image from signals
________________________________________________________________________________
[Memory] Calling nilearn.masking.unmask...
unmask(array([0.044185, ..., 0.009038]), <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>)
___________________________________________________________unmask - 0.0s, 0.0min
\[NiftiMasker.inverse_transform] Computing image from signals
________________________________________________________________________________
[Memory] Calling nilearn.masking.unmask...
unmask(array([0.116209, ..., 0.113023]), <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>)
___________________________________________________________unmask - 0.0s, 0.0min
\[NiftiMasker.inverse_transform] Computing image from signals
________________________________________________________________________________
[Memory] Calling nilearn.masking.unmask...
unmask(array([-0.038463, ..., -0.04593 ]), <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>)
___________________________________________________________unmask - 0.0s, 0.0min
\[NiftiMasker.inverse_transform] Computing image from signals
________________________________________________________________________________
[Memory] Calling nilearn.masking.unmask...
unmask(array([ 0.146915, ..., -0.115344]), <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>)
___________________________________________________________unmask - 0.0s, 0.0min
\[NiftiMasker.inverse_transform] Computing image from signals
________________________________________________________________________________
[Memory] Calling nilearn.masking.unmask...
unmask(array([-0.232613, ..., -0.354522]), <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>)
___________________________________________________________unmask - 0.0s, 0.0min
\[NiftiMasker.inverse_transform] Computing image from signals
________________________________________________________________________________
[Memory] Calling nilearn.masking.unmask...
unmask(array([-0.404357, ..., -0.430212]), <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>)
___________________________________________________________unmask - 0.0s, 0.0min
\[NiftiMasker.inverse_transform] Computing image from signals
________________________________________________________________________________
[Memory] Calling nilearn.masking.unmask...
unmask(array([0.175771, ..., 0.153993]), <nibabel.nifti1.Nifti1Image object at 0x7efed8c717e0>)
___________________________________________________________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 15.180 seconds)
Estimated memory usage: 347 MB
