Nilearn

from nilearn.interfaces.fmriprep import load_confounds
from nilearn.glm.first_level import FirstLevelModel
from nilearn.glm import threshold_stats_img

confounds, sample_mask = load_confounds(
    fmri_img, strategy=('motion', 'high_pass', 'wm_csf', 'scrub'),
    motion='full', scrub=5,
)

flm = FirstLevelModel(t_r=2.0, hrf_model='glover', noise_model='ar1',
                      smoothing_fwhm=6, high_pass=0.01, mask_img=mask)
flm.fit(fmri_img, events=events_df, confounds=confounds, sample_masks=sample_mask)

z_map = flm.compute_contrast('active - rest', output_type='z_score')
thresholded, thresh = threshold_stats_img(
    z_map, alpha=0.05, height_control='fdr', cluster_threshold=10,
)

from nilearn.maskers import NiftiLabelsMasker
from nilearn.connectome import ConnectivityMeasure
from nilearn.datasets import fetch_atlas_schaefer_2018

atlas = fetch_atlas_schaefer_2018(n_rois=200)
masker = NiftiLabelsMasker(labels_img=atlas.maps, labels=atlas.labels,
                           standardize='zscore_sample', memory='nilearn_cache')

all_ts = [masker.fit_transform(img, confounds=conf) for img, conf in zip(imgs, confs)]

conn = ConnectivityMeasure(kind='tangent', vectorize=True)
features = conn.fit_transform(all_ts)  # (n_subjects, n_features) — ready for sklearn

from nilearn.decoding import Decoder

decoder = Decoder(
    estimator='svc', mask=mask_img, cv=5,
    screening_percentile=5, scoring='accuracy',
    smoothing_fwhm=4, standardize=True,
)
decoder.fit(fmri_imgs, y=labels)
print(decoder.cv_scores_)
weight_img = decoder.coef_img_['face']

from nilearn.surface import SurfaceImage
from nilearn.datasets import load_fsaverage
from nilearn.maskers import SurfaceMasker, SurfaceLabelsMasker

fsaverage5 = load_fsaverage('fsaverage5')                          # PolyMesh
surf_img   = SurfaceImage.from_volume(mesh=fsaverage5, volume_img=fmri_4d)

masker  = SurfaceMasker()
signals = masker.fit_transform(surf_img)

# Maskers
from nilearn.maskers import (
    NiftiMasker, NiftiLabelsMasker, NiftiMapsMasker, NiftiSpheresMasker,
    MultiNiftiMasker, SurfaceMasker, SurfaceLabelsMasker, SurfaceMapsMasker,
)

# GLM
from nilearn.glm.first_level import FirstLevelModel, make_first_level_design_matrix, first_level_from_bids
from nilearn.glm.second_level import SecondLevelModel, non_parametric_inference
from nilearn.glm import threshold_stats_img, fdr_threshold, expression_to_contrast_vector

# Image / signal / masking
from nilearn import image
from nilearn.signal import clean, butterworth, high_variance_confounds
from nilearn import masking

# Connectivity / decoding / decomposition
from nilearn.connectome import ConnectivityMeasure, sym_matrix_to_vec, vec_to_sym_matrix
from nilearn.decoding import Decoder, DecoderRegressor, SearchLight, FREMClassifier, SpaceNetClassifier
from nilearn.decomposition import CanICA, DictLearning

# Regions / surface
from nilearn.regions import RegionExtractor, Parcellations, connected_regions
from nilearn.surface import SurfaceImage, PolyMesh, vol_to_surf

# Plotting
from nilearn import plotting
from nilearn.plotting import plot_stat_map, plot_glass_brain, plot_img_on_surf, view_img

# Datasets / interfaces / mass-univariate / reporting
from nilearn.datasets import (
    load_mni152_template, load_mni152_brain_mask, load_fsaverage,
    fetch_atlas_schaefer_2018, fetch_atlas_harvard_oxford, fetch_atlas_difumo,
    fetch_haxby, fetch_adhd, fetch_development_fmri,
)
from nilearn.interfaces.fmriprep import load_confounds, load_confounds_strategy
from nilearn.interfaces.bids import get_bids_files, parse_bids_filename
from nilearn.mass_univariate import permuted_ols
from nilearn.reporting import get_clusters_table