.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "auto_examples/07_advanced/plot_ica_neurovault.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code or to run this example in your browser via Binder. .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_examples_07_advanced_plot_ica_neurovault.py: NeuroVault cross-study ICA maps =============================== This example shows how to download statistical maps from NeuroVault, label them with NeuroSynth terms, and compute :term:`ICA` components across all the maps. See :func:`~nilearn.datasets.fetch_neurovault` documentation for more details. .. include:: ../../../examples/masker_note.rst .. Ported from code authored by Chris Filo Gorgolewski, Gael Varoquaux https://github.com/NeuroVault/neurovault_analysis .. GENERATED FROM PYTHON SOURCE LINES 18-28 .. code-block:: Python 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 .. GENERATED FROM PYTHON SOURCE LINES 29-31 Get image and term data ----------------------- .. GENERATED FROM PYTHON SOURCE LINES 31-60 .. code-block:: Python # 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]) .. rst-class:: sphx-glr-script-out .. code-block:: none Fetching Neurovault images; if you haven't downloaded any Neurovault data before this will take several minutes. [fetch_neurovault] Dataset found in /home/remi-gau/nilearn_data/neurovault [fetch_neurovault] Reading local neurovault data. 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[fetch_neurovault] Computing word features. [fetch_neurovault] Computing word features done; vocabulary size: 1314 Top 10 neurosynth terms from downloaded images: amygdala vi resting state resting hippocampus cerebellar emotional hippocampal lobules cerebellum .. GENERATED FROM PYTHON SOURCE LINES 61-63 Reshape and mask images ----------------------- .. GENERATED FROM PYTHON SOURCE LINES 63-100 .. code-block:: Python 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, :] .. rst-class:: sphx-glr-script-out .. code-block:: none Reshaping and masking images. [NiftiMasker.fit] Loading mask from [NiftiMasker.fit] Resampling mask ________________________________________________________________________________ [Memory] Calling nilearn.image.resampling.resample_img... resample_img(, 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(, , { '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, dtype=None, sklearn_output_config=None) [NiftiMasker.wrapped] Loading data from [NiftiMasker.wrapped] Resampling images [NiftiMasker.wrapped] Extracting region signals [NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 0.4s, 0.0min ________________________________________________________________________________ [Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask... filter_and_mask(, , { '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, dtype=None, sklearn_output_config=None) [NiftiMasker.wrapped] Loading data from [NiftiMasker.wrapped] Resampling images [NiftiMasker.wrapped] Extracting region signals [NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 0.4s, 0.0min ________________________________________________________________________________ [Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask... filter_and_mask(, , { '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, dtype=None, sklearn_output_config=None) [NiftiMasker.wrapped] Loading data from [NiftiMasker.wrapped] Resampling images [NiftiMasker.wrapped] Extracting region signals [NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 0.4s, 0.0min ________________________________________________________________________________ [Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask... filter_and_mask(, , { '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, dtype=None, sklearn_output_config=None) [NiftiMasker.wrapped] Loading data from [NiftiMasker.wrapped] Resampling images [NiftiMasker.wrapped] Extracting region signals [NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 0.4s, 0.0min ________________________________________________________________________________ [Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask... filter_and_mask(, , { '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, dtype=None, sklearn_output_config=None) [NiftiMasker.wrapped] Loading data from [NiftiMasker.wrapped] Resampling images [NiftiMasker.wrapped] Extracting region signals [NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 0.4s, 0.0min ________________________________________________________________________________ [Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask... filter_and_mask(, , { '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, dtype=None, sklearn_output_config=None) [NiftiMasker.wrapped] Loading data from [NiftiMasker.wrapped] Resampling images [NiftiMasker.wrapped] Extracting region signals [NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 0.4s, 0.0min ________________________________________________________________________________ [Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask... filter_and_mask(, , { '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, dtype=None, sklearn_output_config=None) [NiftiMasker.wrapped] Loading data from [NiftiMasker.wrapped] Resampling images [NiftiMasker.wrapped] Extracting region signals [NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 0.4s, 0.0min ________________________________________________________________________________ [Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask... filter_and_mask(, , { '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, dtype=None, sklearn_output_config=None) [NiftiMasker.wrapped] Loading data from [NiftiMasker.wrapped] Resampling images [NiftiMasker.wrapped] Extracting region signals [NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 0.4s, 0.0min ________________________________________________________________________________ [Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask... filter_and_mask(, , { '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, dtype=None, sklearn_output_config=None) [NiftiMasker.wrapped] Loading data from [NiftiMasker.wrapped] Resampling images [NiftiMasker.wrapped] Extracting region signals [NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 0.4s, 0.0min ________________________________________________________________________________ [Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask... filter_and_mask(, , { '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, dtype=None, sklearn_output_config=None) [NiftiMasker.wrapped] Loading data from [NiftiMasker.wrapped] Resampling images [NiftiMasker.wrapped] Extracting region signals [NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 0.4s, 0.0min ________________________________________________________________________________ [Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask... filter_and_mask(, , { '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, dtype=None, sklearn_output_config=None) [NiftiMasker.wrapped] Loading data from [NiftiMasker.wrapped] Resampling images [NiftiMasker.wrapped] Extracting region signals [NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 0.4s, 0.0min ________________________________________________________________________________ [Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask... filter_and_mask(, , { '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, dtype=None, sklearn_output_config=None) [NiftiMasker.wrapped] Loading data from [NiftiMasker.wrapped] Resampling images [NiftiMasker.wrapped] Extracting region signals [NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 0.4s, 0.0min ________________________________________________________________________________ [Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask... filter_and_mask(, , { '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, dtype=None, sklearn_output_config=None) [NiftiMasker.wrapped] Loading data from [NiftiMasker.wrapped] Resampling images [NiftiMasker.wrapped] Extracting region signals [NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 0.4s, 0.0min ________________________________________________________________________________ [Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask... filter_and_mask(, , { '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, dtype=None, sklearn_output_config=None) [NiftiMasker.wrapped] Loading data from [NiftiMasker.wrapped] Resampling images [NiftiMasker.wrapped] Extracting region signals [NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 0.4s, 0.0min ________________________________________________________________________________ [Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask... filter_and_mask(, , { '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, dtype=None, sklearn_output_config=None) [NiftiMasker.wrapped] Loading data from [NiftiMasker.wrapped] Resampling images [NiftiMasker.wrapped] Extracting region signals [NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 0.4s, 0.0min ________________________________________________________________________________ [Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask... filter_and_mask(, , { '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, dtype=None, sklearn_output_config=None) [NiftiMasker.wrapped] Loading data from [NiftiMasker.wrapped] Resampling images [NiftiMasker.wrapped] Extracting region signals [NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 0.4s, 0.0min ________________________________________________________________________________ [Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask... filter_and_mask(, , { '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, dtype=None, sklearn_output_config=None) [NiftiMasker.wrapped] Loading data from [NiftiMasker.wrapped] Resampling images [NiftiMasker.wrapped] Extracting region signals [NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 0.4s, 0.0min ________________________________________________________________________________ [Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask... filter_and_mask(, , { '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, dtype=None, sklearn_output_config=None) [NiftiMasker.wrapped] Loading data from [NiftiMasker.wrapped] Resampling images [NiftiMasker.wrapped] Extracting region signals [NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 0.4s, 0.0min ________________________________________________________________________________ [Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask... filter_and_mask(, , { '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, dtype=None, sklearn_output_config=None) [NiftiMasker.wrapped] Loading data from [NiftiMasker.wrapped] Resampling images [NiftiMasker.wrapped] Extracting region signals [NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 0.4s, 0.0min ________________________________________________________________________________ [Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask... filter_and_mask(, , { '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, dtype=None, sklearn_output_config=None) [NiftiMasker.wrapped] Loading data from [NiftiMasker.wrapped] Resampling images [NiftiMasker.wrapped] Extracting region signals [NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 0.4s, 0.0min ________________________________________________________________________________ [Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask... filter_and_mask(, , { '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, dtype=None, sklearn_output_config=None) [NiftiMasker.wrapped] Loading data from [NiftiMasker.wrapped] Resampling images [NiftiMasker.wrapped] Extracting region signals [NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 0.5s, 0.0min ________________________________________________________________________________ [Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask... filter_and_mask(, , { '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, dtype=None, sklearn_output_config=None) [NiftiMasker.wrapped] Loading data from [NiftiMasker.wrapped] Resampling images [NiftiMasker.wrapped] Extracting region signals [NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 0.4s, 0.0min ________________________________________________________________________________ [Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask... filter_and_mask(, , { '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, dtype=None, sklearn_output_config=None) [NiftiMasker.wrapped] Loading data from [NiftiMasker.wrapped] Resampling images [NiftiMasker.wrapped] Extracting region signals [NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 0.4s, 0.0min ________________________________________________________________________________ [Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask... filter_and_mask(, , { '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, dtype=None, sklearn_output_config=None) [NiftiMasker.wrapped] Loading data from [NiftiMasker.wrapped] Resampling images [NiftiMasker.wrapped] Extracting region signals [NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 0.5s, 0.0min ________________________________________________________________________________ [Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask... filter_and_mask(, , { '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, dtype=None, sklearn_output_config=None) [NiftiMasker.wrapped] Loading data from [NiftiMasker.wrapped] Resampling images [NiftiMasker.wrapped] Extracting region signals [NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 0.4s, 0.0min ________________________________________________________________________________ [Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask... filter_and_mask(, , { '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, dtype=None, sklearn_output_config=None) [NiftiMasker.wrapped] Loading data from [NiftiMasker.wrapped] Resampling images [NiftiMasker.wrapped] Extracting region signals [NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 0.4s, 0.0min ________________________________________________________________________________ [Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask... filter_and_mask(, , { '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, dtype=None, sklearn_output_config=None) [NiftiMasker.wrapped] Loading data from [NiftiMasker.wrapped] Resampling images [NiftiMasker.wrapped] Extracting region signals [NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 0.4s, 0.0min ________________________________________________________________________________ [Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask... filter_and_mask(, , { '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, dtype=None, sklearn_output_config=None) [NiftiMasker.wrapped] Loading data from [NiftiMasker.wrapped] Resampling images [NiftiMasker.wrapped] Extracting region signals [NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 0.4s, 0.0min ________________________________________________________________________________ [Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask... filter_and_mask(, , { '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, dtype=None, sklearn_output_config=None) [NiftiMasker.wrapped] Loading data from [NiftiMasker.wrapped] Resampling images [NiftiMasker.wrapped] Extracting region signals [NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 0.4s, 0.0min ________________________________________________________________________________ [Memory] Calling nilearn.maskers.nifti_masker.filter_and_mask... filter_and_mask(, , { '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, dtype=None, sklearn_output_config=None) [NiftiMasker.wrapped] Loading data from [NiftiMasker.wrapped] Resampling images [NiftiMasker.wrapped] Extracting region signals [NiftiMasker.wrapped] Cleaning extracted signals __________________________________________________filter_and_mask - 0.4s, 0.0min .. GENERATED FROM PYTHON SOURCE LINES 101-103 Run :term:`ICA` and map components to terms ------------------------------------------- .. GENERATED FROM PYTHON SOURCE LINES 103-115 .. code-block:: Python 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.") .. rst-class:: sphx-glr-script-out .. code-block:: none Running ICA; may take time... Done, plotting results. .. GENERATED FROM PYTHON SOURCE LINES 116-118 Generate figures ---------------- .. GENERATED FROM PYTHON SOURCE LINES 118-134 .. code-block:: Python 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) .. rst-class:: sphx-glr-horizontal * .. image-sg:: /auto_examples/07_advanced/images/sphx_glr_plot_ica_neurovault_001.png :alt: plot ica neurovault :srcset: /auto_examples/07_advanced/images/sphx_glr_plot_ica_neurovault_001.png :class: sphx-glr-multi-img * .. image-sg:: /auto_examples/07_advanced/images/sphx_glr_plot_ica_neurovault_002.png :alt: plot ica neurovault :srcset: /auto_examples/07_advanced/images/sphx_glr_plot_ica_neurovault_002.png :class: sphx-glr-multi-img * .. image-sg:: /auto_examples/07_advanced/images/sphx_glr_plot_ica_neurovault_003.png :alt: plot ica neurovault :srcset: /auto_examples/07_advanced/images/sphx_glr_plot_ica_neurovault_003.png :class: sphx-glr-multi-img * .. image-sg:: /auto_examples/07_advanced/images/sphx_glr_plot_ica_neurovault_004.png :alt: plot ica neurovault :srcset: /auto_examples/07_advanced/images/sphx_glr_plot_ica_neurovault_004.png :class: sphx-glr-multi-img * .. image-sg:: /auto_examples/07_advanced/images/sphx_glr_plot_ica_neurovault_005.png :alt: plot ica neurovault :srcset: /auto_examples/07_advanced/images/sphx_glr_plot_ica_neurovault_005.png :class: sphx-glr-multi-img * .. image-sg:: /auto_examples/07_advanced/images/sphx_glr_plot_ica_neurovault_006.png :alt: plot ica neurovault :srcset: /auto_examples/07_advanced/images/sphx_glr_plot_ica_neurovault_006.png :class: sphx-glr-multi-img * .. image-sg:: /auto_examples/07_advanced/images/sphx_glr_plot_ica_neurovault_007.png :alt: plot ica neurovault :srcset: /auto_examples/07_advanced/images/sphx_glr_plot_ica_neurovault_007.png :class: sphx-glr-multi-img * .. image-sg:: /auto_examples/07_advanced/images/sphx_glr_plot_ica_neurovault_008.png :alt: plot ica neurovault :srcset: /auto_examples/07_advanced/images/sphx_glr_plot_ica_neurovault_008.png :class: sphx-glr-multi-img .. rst-class:: sphx-glr-script-out .. code-block:: none [NiftiMasker.inverse_transform] Computing image from signals ________________________________________________________________________________ [Memory] Calling nilearn.masking.unmask... unmask(array([0.166983, ..., 0.22512 ], shape=(235375,)), ) ___________________________________________________________unmask - 0.2s, 0.0min [NiftiMasker.inverse_transform] Computing image from signals ________________________________________________________________________________ [Memory] Calling nilearn.masking.unmask... unmask(array([0.006767, ..., 0.16057 ], shape=(235375,)), ) ___________________________________________________________unmask - 0.2s, 0.0min [NiftiMasker.inverse_transform] Computing image from signals ________________________________________________________________________________ [Memory] Calling nilearn.masking.unmask... unmask(array([-0.669131, ..., -1.246227], shape=(235375,)), ) ___________________________________________________________unmask - 0.2s, 0.0min [NiftiMasker.inverse_transform] Computing image from signals ________________________________________________________________________________ [Memory] Calling nilearn.masking.unmask... unmask(array([ 0.031285, ..., -0.242347], shape=(235375,)), ) ___________________________________________________________unmask - 0.2s, 0.0min [NiftiMasker.inverse_transform] Computing image from signals ________________________________________________________________________________ [Memory] Calling nilearn.masking.unmask... unmask(array([-0.307528, ..., -0.346196], shape=(235375,)), ) ___________________________________________________________unmask - 0.2s, 0.0min [NiftiMasker.inverse_transform] Computing image from signals ________________________________________________________________________________ [Memory] Calling nilearn.masking.unmask... unmask(array([0.88318 , ..., 0.359842], shape=(235375,)), ) ___________________________________________________________unmask - 0.2s, 0.0min [NiftiMasker.inverse_transform] Computing image from signals ________________________________________________________________________________ [Memory] Calling nilearn.masking.unmask... unmask(array([-0.020097, ..., 0.512281], shape=(235375,)), ) ___________________________________________________________unmask - 0.2s, 0.0min [NiftiMasker.inverse_transform] Computing image from signals ________________________________________________________________________________ [Memory] Calling nilearn.masking.unmask... unmask(array([-0.122086, ..., -0.073002], shape=(235375,)), ) ___________________________________________________________unmask - 0.2s, 0.0min .. GENERATED FROM PYTHON SOURCE LINES 135-138 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 .. GENERATED FROM PYTHON SOURCE LINES 138-141 .. code-block:: Python # Done. show() .. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 30.581 seconds) **Estimated memory usage:** 206 MB .. _sphx_glr_download_auto_examples_07_advanced_plot_ica_neurovault.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: binder-badge .. image:: images/binder_badge_logo.svg :target: https://mybinder.org/v2/gh/nilearn/nilearn/0.13.0?urlpath=lab/tree/notebooks/auto_examples/07_advanced/plot_ica_neurovault.ipynb :alt: Launch binder :width: 150 px .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_ica_neurovault.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_ica_neurovault.py ` .. container:: sphx-glr-download sphx-glr-download-zip :download:`Download zipped: plot_ica_neurovault.zip ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_