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<li class="toctree-l3"><a class="reference internal" href="../auto_examples/02_decoding/plot_haxby_stimuli.html">Show stimuli of Haxby et al. dataset</a></li>
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<li class="toctree-l3"><a class="reference internal" href="../auto_examples/02_decoding/plot_haxby_multiclass.html">The haxby dataset: different multi-class strategies</a></li>
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<li class="toctree-l3"><a class="reference internal" href="../auto_examples/02_decoding/plot_haxby_full_analysis.html">ROI-based decoding analysis in Haxby et al. dataset</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/02_decoding/plot_haxby_grid_search.html">Setting a parameter by cross-validation</a></li>
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<li class="toctree-l3"><a class="reference internal" href="../auto_examples/02_decoding/plot_haxby_different_estimators.html">Different classifiers in decoding the Haxby dataset</a></li>
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<li class="toctree-l3"><a class="reference internal" href="../auto_examples/02_decoding/plot_miyawaki_reconstruction.html">Reconstruction of visual stimuli from Miyawaki et al. 2008</a></li>
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<li class="toctree-l3"><a class="reference internal" href="../auto_examples/03_connectivity/plot_inverse_covariance_connectome.html">Computing a connectome with sparse inverse covariance</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/03_connectivity/plot_probabilistic_atlas_extraction.html">Extracting signals of a probabilistic atlas of functional regions</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/03_connectivity/plot_simulated_connectome.html">Connectivity structure estimation on simulated data</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/03_connectivity/plot_multi_subject_connectome.html">Group Sparse inverse covariance for multi-subject connectome</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/03_connectivity/plot_seed_to_voxel_correlation.html">Producing single subject maps of seed-to-voxel correlation</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/03_connectivity/plot_compare_decomposition.html">Deriving spatial maps from group fMRI data using ICA and Dictionary Learning</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/03_connectivity/plot_extract_regions_dictlearning_maps.html">Regions extraction using dictionary learning and functional connectomes</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/03_connectivity/plot_atlas_comparison.html">Comparing connectomes on different reference atlases</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/03_connectivity/plot_group_level_connectivity.html">Classification of age groups using functional connectivity</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/03_connectivity/plot_signal_extraction.html">Extracting signals from a brain parcellation</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/03_connectivity/plot_sphere_based_connectome.html">Extract signals on spheres and plot a connectome</a></li>
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<li class="toctree-l3"><a class="reference internal" href="../auto_examples/04_glm_first_level/plot_design_matrix.html">Examples of design matrices</a></li>
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<li class="toctree-l3"><a class="reference internal" href="../auto_examples/04_glm_first_level/plot_adhd_dmn.html">Default Mode Network extraction of ADHD dataset</a></li>
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<li class="toctree-l3"><a class="reference internal" href="../auto_examples/04_glm_first_level/plot_spm_multimodal_faces.html">Single-subject data (two runs) in native space</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/04_glm_first_level/plot_hrf.html">Example of MRI response functions</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/04_glm_first_level/plot_predictions_residuals.html">Predicted time series and residuals</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/04_glm_first_level/plot_bids_features.html">First level analysis of a complete BIDS dataset from openneuro</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/04_glm_first_level/plot_localizer_surface_analysis.html">Example of surface-based first-level analysis</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/04_glm_first_level/plot_two_runs_model.html">Simple example of two-runs fMRI model fitting</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/04_glm_first_level/plot_first_level_details.html">Understanding parameters of the first-level model</a></li>
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<li class="toctree-l3"><a class="reference internal" href="../auto_examples/05_glm_second_level/plot_proportion_activated_voxels.html">Second-level fMRI model: true positive proportion in clusters</a></li>
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<li class="toctree-l3"><a class="reference internal" href="../auto_examples/05_glm_second_level/plot_second_level_one_sample_test.html">Second-level fMRI model: one sample test</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/05_glm_second_level/plot_second_level_association_test.html">Example of generic design in second-level models</a></li>
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<li class="toctree-l2 has-children"><a class="reference internal" href="../auto_examples/06_manipulating_images/index.html">Manipulating brain image volumes</a><input class="toctree-checkbox" id="toctree-checkbox-8" name="toctree-checkbox-8" role="switch" type="checkbox"/><label for="toctree-checkbox-8"><div class="visually-hidden">Toggle navigation of Manipulating brain image volumes</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/06_manipulating_images/plot_negate_image.html">Negating an image with math_img</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/06_manipulating_images/plot_compare_mean_image.html">Comparing the means of 2 images</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/06_manipulating_images/plot_smooth_mean_image.html">Smoothing an image</a></li>
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<li class="toctree-l3"><a class="reference internal" href="../auto_examples/06_manipulating_images/plot_resample_to_template.html">Resample an image to a template</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/06_manipulating_images/plot_extract_rois_smith_atlas.html">Regions Extraction of Default Mode Networks using Smith Atlas</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/06_manipulating_images/plot_nifti_simple.html">Simple example of NiftiMasker use</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/06_manipulating_images/plot_extract_rois_statistical_maps.html">Region Extraction using a t-statistical map (3D)</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/06_manipulating_images/plot_nifti_labels_simple.html">Extracting signals from brain regions using the NiftiLabelsMasker</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/06_manipulating_images/plot_mask_computation.html">Understanding NiftiMasker and mask computation</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/06_manipulating_images/plot_affine_transformation.html">Visualization of affine resamplings</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/06_manipulating_images/plot_roi_extraction.html">Computing a Region of Interest (ROI) mask manually</a></li>
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<li class="toctree-l2 has-children"><a class="reference internal" href="../auto_examples/07_advanced/index.html">Advanced statistical analysis of brain images</a><input class="toctree-checkbox" id="toctree-checkbox-9" name="toctree-checkbox-9" role="switch" type="checkbox"/><label for="toctree-checkbox-9"><div class="visually-hidden">Toggle navigation of Advanced statistical analysis of brain images</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/07_advanced/plot_ica_resting_state.html">Multivariate decompositions: Independent component analysis of fMRI</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/07_advanced/plot_localizer_simple_analysis.html">Massively univariate analysis of a calculation task from the Localizer dataset</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/07_advanced/plot_bids_analysis.html">BIDS dataset first and second level analysis</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/07_advanced/plot_neurovault_meta_analysis.html">NeuroVault meta-analysis of stop-go paradigm studies</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/07_advanced/plot_age_group_prediction_cross_val.html">Functional connectivity predicts age group</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/07_advanced/plot_surface_bids_analysis.html">Surface-based dataset first and second level analysis of a dataset</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/07_advanced/plot_localizer_mass_univariate_methods.html">Massively univariate analysis of a motor task from the Localizer dataset</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/07_advanced/plot_ica_neurovault.html">NeuroVault cross-study ICA maps</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/07_advanced/plot_haxby_mass_univariate.html">Massively univariate analysis of face vs house recognition</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/07_advanced/plot_advanced_decoding_scikit.html">Advanced decoding using scikit learn</a></li>
<li class="toctree-l3"><a class="reference internal" href="../auto_examples/07_advanced/plot_beta_series.html">Beta-Series Modeling for Task-Based Functional Connectivity and Decoding</a></li>
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<li class="toctree-l3"><a class="reference internal" href="../auto_examples/08_experimental/plot_surface_image_and_maskers.html">A short demo of the surface images & maskers</a></li>
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<li class="toctree-l1 has-children"><a class="reference internal" href="../user_guide.html">User guide</a><input class="toctree-checkbox" id="toctree-checkbox-11" name="toctree-checkbox-11" role="switch" type="checkbox"/><label for="toctree-checkbox-11"><div class="visually-hidden">Toggle navigation of User guide</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
<li class="toctree-l2"><a class="reference internal" href="../introduction.html">1. Introduction</a></li>
<li class="toctree-l2"><a class="reference internal" href="../introduction.html#what-is-nilearn">2. What is <code class="docutils literal notranslate"><span class="pre">nilearn</span></code>?</a></li>
<li class="toctree-l2"><a class="reference internal" href="../introduction.html#using-nilearn-for-the-first-time">3. Using <code class="docutils literal notranslate"><span class="pre">nilearn</span></code> for the first time</a></li>
<li class="toctree-l2"><a class="reference internal" href="../introduction.html#machine-learning-applications-to-neuroimaging">4. Machine learning applications to Neuroimaging</a></li>
<li class="toctree-l2 has-children"><a class="reference internal" href="../decoding/index.html">5. Decoding and MVPA: predicting from brain images</a><input class="toctree-checkbox" id="toctree-checkbox-12" name="toctree-checkbox-12" role="switch" type="checkbox"/><label for="toctree-checkbox-12"><div class="visually-hidden">Toggle navigation of 5. Decoding and MVPA: predicting from brain images</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
<li class="toctree-l3"><a class="reference internal" href="../decoding/decoding_intro.html">5.1. An introduction to decoding</a></li>
<li class="toctree-l3"><a class="reference internal" href="../decoding/estimator_choice.html">5.2. Choosing the right predictive model for neuroimaging</a></li>
<li class="toctree-l3"><a class="reference internal" href="../decoding/frem.html">5.3. FREM: fast ensembling of regularized models for robust decoding</a></li>
<li class="toctree-l3"><a class="reference internal" href="../decoding/space_net.html">5.4. SpaceNet: decoding with spatial structure for better maps</a></li>
<li class="toctree-l3"><a class="reference internal" href="../decoding/searchlight.html">5.5. Searchlight : finding voxels containing information</a></li>
<li class="toctree-l3"><a class="reference internal" href="../decoding/going_further.html">5.6. Running scikit-learn functions for more control on the analysis</a></li>
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<li class="toctree-l2 has-children"><a class="reference internal" href="../connectivity/index.html">6. Functional connectivity and resting state</a><input class="toctree-checkbox" id="toctree-checkbox-13" name="toctree-checkbox-13" role="switch" type="checkbox"/><label for="toctree-checkbox-13"><div class="visually-hidden">Toggle navigation of 6. Functional connectivity and resting state</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
<li class="toctree-l3"><a class="reference internal" href="../connectivity/functional_connectomes.html">6.1. Extracting times series to build a functional connectome</a></li>
<li class="toctree-l3 has-children"><a class="reference internal" href="../connectivity/connectome_extraction.html">6.2. Connectome extraction: inverse covariance for direct connections</a><input class="toctree-checkbox" id="toctree-checkbox-14" name="toctree-checkbox-14" role="switch" type="checkbox"/><label for="toctree-checkbox-14"><div class="visually-hidden">Toggle navigation of 6.2. Connectome extraction: inverse covariance for direct connections</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
<li class="toctree-l4"><a class="reference internal" href="../developers/group_sparse_covariance.html">6.2.3.1. Group-sparse covariance estimation</a></li>
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<li class="toctree-l3"><a class="reference internal" href="../connectivity/resting_state_networks.html">6.3. Extracting functional brain networks: ICA and related</a></li>
<li class="toctree-l3"><a class="reference internal" href="../connectivity/region_extraction.html">6.4. Region Extraction for better brain parcellations</a></li>
<li class="toctree-l3"><a class="reference internal" href="../connectivity/parcellating.html">6.5. Clustering to parcellate the brain in regions</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../plotting/index.html">7. Plotting brain images</a></li>
<li class="toctree-l2 has-children"><a class="reference internal" href="../glm/index.html">8. Analyzing fMRI using GLMs</a><input class="toctree-checkbox" id="toctree-checkbox-15" name="toctree-checkbox-15" role="switch" type="checkbox"/><label for="toctree-checkbox-15"><div class="visually-hidden">Toggle navigation of 8. Analyzing fMRI using GLMs</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
<li class="toctree-l3"><a class="reference internal" href="../glm/glm_intro.html">8.1. An introduction to GLMs in fMRI statistical analysis</a></li>
<li class="toctree-l3"><a class="reference internal" href="../glm/first_level_model.html">8.2. First level models</a></li>
<li class="toctree-l3"><a class="reference internal" href="../glm/second_level_model.html">8.3. Second level models</a></li>
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<li class="toctree-l2 has-children"><a class="reference internal" href="../manipulating_images/index.html">9. Manipulation brain volumes with nilearn</a><input class="toctree-checkbox" id="toctree-checkbox-16" name="toctree-checkbox-16" role="switch" type="checkbox"/><label for="toctree-checkbox-16"><div class="visually-hidden">Toggle navigation of 9. Manipulation brain volumes with nilearn</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
<li class="toctree-l3"><a class="reference internal" href="../manipulating_images/input_output.html">9.1. Input and output: neuroimaging data representation</a></li>
<li class="toctree-l3"><a class="reference internal" href="../manipulating_images/manipulating_images.html">9.2. Manipulating images: resampling, smoothing, masking, ROIs…</a></li>
<li class="toctree-l3"><a class="reference internal" href="../manipulating_images/masker_objects.html">9.3. From neuroimaging volumes to data matrices: the masker objects</a></li>
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<li class="toctree-l2 has-children"><a class="reference internal" href="../building_blocks/index.html">10. Advanced usage: manual pipelines and scaling up</a><input class="toctree-checkbox" id="toctree-checkbox-17" name="toctree-checkbox-17" role="switch" type="checkbox"/><label for="toctree-checkbox-17"><div class="visually-hidden">Toggle navigation of 10. Advanced usage: manual pipelines and scaling up</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
<li class="toctree-l3"><a class="reference internal" href="../building_blocks/manual_pipeline.html">10.1. Building your own neuroimaging machine-learning pipeline</a></li>
<li class="toctree-l3"><a class="reference internal" href="../building_blocks/neurovault.html">10.2. Downloading statistical maps from the Neurovault repository</a></li>
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<li class="toctree-l1 has-children"><a class="reference internal" href="../modules/index.html">API References</a><input class="toctree-checkbox" id="toctree-checkbox-18" name="toctree-checkbox-18" role="switch" type="checkbox"/><label for="toctree-checkbox-18"><div class="visually-hidden">Toggle navigation of API References</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
<li class="toctree-l2 has-children"><a class="reference internal" href="../modules/connectome.html"><code class="xref py py-mod docutils literal notranslate"><span class="pre">nilearn.connectome</span></code>: Functional Connectivity</a><input class="toctree-checkbox" id="toctree-checkbox-19" name="toctree-checkbox-19" role="switch" type="checkbox"/><label for="toctree-checkbox-19"><div class="visually-hidden">Toggle navigation of nilearn.connectome: Functional Connectivity</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
<li class="toctree-l3"><a class="reference internal" href="../modules/generated/nilearn.connectome.ConnectivityMeasure.html">nilearn.connectome.ConnectivityMeasure</a></li>
<li class="toctree-l3"><a class="reference internal" href="../modules/generated/nilearn.connectome.GroupSparseCovariance.html">nilearn.connectome.GroupSparseCovariance</a></li>
<li class="toctree-l3"><a class="reference internal" href="../modules/generated/nilearn.connectome.GroupSparseCovarianceCV.html">nilearn.connectome.GroupSparseCovarianceCV</a></li>
<li class="toctree-l3"><a class="reference internal" href="../modules/generated/nilearn.connectome.sym_matrix_to_vec.html">nilearn.connectome.sym_matrix_to_vec</a></li>
<li class="toctree-l3"><a class="reference internal" href="../modules/generated/nilearn.connectome.vec_to_sym_matrix.html">nilearn.connectome.vec_to_sym_matrix</a></li>
<li class="toctree-l3"><a class="reference internal" href="../modules/generated/nilearn.connectome.group_sparse_covariance.html">nilearn.connectome.group_sparse_covariance</a></li>
<li class="toctree-l3"><a class="reference internal" href="../modules/generated/nilearn.connectome.cov_to_corr.html">nilearn.connectome.cov_to_corr</a></li>
<li class="toctree-l3"><a class="reference internal" href="../modules/generated/nilearn.connectome.prec_to_partial.html">nilearn.connectome.prec_to_partial</a></li>
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<h1>0.1.0<a class="headerlink" href="#id1" title="Link to this heading">#</a></h1>
<p><strong>Released February 2015</strong></p>
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<h2>Changelog<a class="headerlink" href="#changelog" title="Link to this heading">#</a></h2>
<p>First release of nilearn.</p>
<p>Contributors (from <code class="docutils literal notranslate"><span class="pre">git</span> <span class="pre">shortlog</span> <span class="pre">-ns</span> <span class="pre">0.1</span></code>):</p>
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<li><p><a class="reference external" href="https://gael-varoquaux.info/">Gael Varoquaux</a> (600)</p></li>
<li><p><a class="reference external" href="https://twinee.fr/">Alexandre Abraham</a> (483)</p></li>
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<li><p><a class="reference external" href="https://github.com/eickenberg">Michael Eickenberg</a> (83)</p></li>
<li><p><a class="reference external" href="http://jeankossaifi.com/">Jean Kossaifi</a> (59)</p></li>
<li><p><a class="reference external" href="https://github.com/jaquesgrobler">Jaques Grobler</a> (57)</p></li>
<li><p><a class="reference external" href="https://github.com/banilo">Danilo Bzdok</a> (46)</p></li>
<li><p><a class="reference external" href="https://chrisgorgolewski.org/">Chris Gorgolewski</a> (35)</p></li>
<li><p><a class="reference external" href="https://github.com/rphlypo">Ronald Phlypo</a> (28)</p></li>
<li><p><a class="reference external" href="https://github.com/bcipolli">Ben Cipollini</a> (25)</p></li>
<li><p><a class="reference external" href="https://pages.saclay.inria.fr/bertrand.thirion/">Bertrand Thirion</a> (15)</p></li>
<li><p><a class="reference external" href="http://alexandre.gramfort.net/">Alexandre Gramfort</a> (13)</p></li>
<li><p><a class="reference external" href="https://github.com/fabianp">Fabian Pedregosa</a> (12)</p></li>
<li><p>Yannick Schwartz (11)</p></li>
<li><p><a class="reference external" href="https://github.com/mrahim">Mehdi Rahim</a> (9)</p></li>
<li><p><a class="reference external" href="https://github.com/Titan-C">Óscar Nájera</a> (7)</p></li>
<li><p><a class="reference external" href="https://dohmatob.github.io/">Elvis Dohmatob</a> (6)</p></li>
<li><p><a class="reference external" href="https://github.com/kshmelkov">Konstantin Shmelkov</a> (4)</p></li>
<li><p><a class="reference external" href="http://jgors.com/">Jason Gors</a> (3)</p></li>
<li><p><a class="reference external" href="https://github.com/salma1601">Salma Bougacha</a> (3)</p></li>
<li><p><a class="reference external" href="https://github.com/alex-savio">Alexandre Savio</a> (1)</p></li>
<li><p><a class="reference external" href="https://github.com/jmargeta">Jan Margeta</a> (1)</p></li>
<li><p><a class="reference external" href="https://github.com/mekman">Matthias Ekman</a> (1)</p></li>
<li><p><a class="reference external" href="https://mwaskom.github.io/">Michael Waskom</a> (1)</p></li>
<li><p><a class="reference external" href="https://github.com/vmichel">Vincent Michel</a> (1)</p></li>
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