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
[fetch_neurovault] Already fetched 13 images
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[fetch_neurovault] Already fetched 18 images
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[fetch_neurovault] Already fetched 21 images
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[fetch_neurovault] Already fetched 28 images
[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
anterior insula
superior
parietal
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
0x7fa1340400d0>
\[NiftiMasker.fit] Resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>, 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 0x7fa133ac1db0>, <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>, { '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
0x7fa133ac3c40>
\[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 0x7fa1340404c0>, <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>, { '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
0x7fa133ac2aa0>
\[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 0x7fa133ac29b0>, <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>, { '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
0x7fa133ac32b0>
\[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 0x7fa134041720>, <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>, { '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
0x7fa133ac0b20>
\[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 0x7fa133ac0790>, <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>, { '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
0x7fa133ac0a60>
\[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 0x7fa1340404c0>, <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>, { '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
0x7fa133ac39a0>
\[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 0x7fa133ac0580>, <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>, { '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
0x7fa133ac3a30>
\[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 0x7fa133ac3970>, <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>, { '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
0x7fa133ac0820>
\[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 0x7fa133ac0f40>, <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>, { '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
0x7fa133ac30d0>
\[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 0x7fa133ac1330>, <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>, { '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
0x7fa133ac2a10>
\[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 0x7fa134041720>, <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>, { '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
0x7fa133ac21d0>
\[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 0x7fa133ac1e70>, <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>, { '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
0x7fa133ac0c10>
\[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 0x7fa133ac11e0>, <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>, { '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
0x7fa133ac0e50>
\[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 0x7fa133ac3cd0>, <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>, { '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
0x7fa133ac3190>
\[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 0x7fa134043430>, <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>, { '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
0x7fa133ac01c0>
\[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 0x7fa133ac0e80>, <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>, { '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
0x7fa133ac0430>
\[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 0x7fa133ac1540>, <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>, { '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
0x7fa135c698a0>
\[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 0x7fa1082bbac0>, <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>, { '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
0x7fa10ff6a590>
\[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 0x7fa13401b910>, <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>, { '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
0x7fa1340401f0>
\[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 0x7fa10ff6a650>, <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>, { '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
0x7fa13401beb0>
\[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 0x7fa1082b8d30>, <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>, { '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
0x7fa134042aa0>
\[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 0x7fa13401ac50>, <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>, { '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
0x7fa1082bb1c0>
\[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 0x7fa134043010>, <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>, { '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
0x7fa134040160>
\[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 0x7fa134042b30>, <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>, { '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
0x7fa134040cd0>
\[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 0x7fa13401a6e0>, <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>, { '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
0x7fa10ff6a650>
\[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 0x7fa134043340>, <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>, { '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
0x7fa134042740>
\[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 0x7fa13401a6e0>, <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>, { '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
0x7fa1082bb7f0>
\[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 0x7fa134043370>, <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>, { '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
0x7fa134043490>
\[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 0x7fa10ff68d30>, <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>, { '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
0x7fa1082bb7f0>
\[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([-0.230333, ..., -0.355222]), <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>)
___________________________________________________________unmask - 0.1s, 0.0min
\[NiftiMasker.inverse_transform] Computing image from signals
________________________________________________________________________________
[Memory] Calling nilearn.masking.unmask...
unmask(array([ 0.174666, ..., -0.079971]), <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>)
___________________________________________________________unmask - 0.0s, 0.0min
\[NiftiMasker.inverse_transform] Computing image from signals
________________________________________________________________________________
[Memory] Calling nilearn.masking.unmask...
unmask(array([-0.105046, ..., -0.089722]), <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>)
___________________________________________________________unmask - 0.0s, 0.0min
\[NiftiMasker.inverse_transform] Computing image from signals
________________________________________________________________________________
[Memory] Calling nilearn.masking.unmask...
unmask(array([-0.022539, ..., -0.03561 ]), <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>)
___________________________________________________________unmask - 0.0s, 0.0min
\[NiftiMasker.inverse_transform] Computing image from signals
________________________________________________________________________________
[Memory] Calling nilearn.masking.unmask...
unmask(array([0.100142, ..., 0.124067]), <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>)
___________________________________________________________unmask - 0.0s, 0.0min
\[NiftiMasker.inverse_transform] Computing image from signals
________________________________________________________________________________
[Memory] Calling nilearn.masking.unmask...
unmask(array([-0.219892, ..., -0.21238 ]), <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>)
___________________________________________________________unmask - 0.0s, 0.0min
\[NiftiMasker.inverse_transform] Computing image from signals
________________________________________________________________________________
[Memory] Calling nilearn.masking.unmask...
unmask(array([-0.475248, ..., -0.487403]), <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>)
___________________________________________________________unmask - 0.0s, 0.0min
\[NiftiMasker.inverse_transform] Computing image from signals
________________________________________________________________________________
[Memory] Calling nilearn.masking.unmask...
unmask(array([0.082926, ..., 0.039885]), <nibabel.nifti1.Nifti1Image object at 0x7fa1340422c0>)
___________________________________________________________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 14.763 seconds)
Estimated memory usage: 347 MB
