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Holds the code use in the "Which fMRI clustering gives good brain parcellations?" frontiers 2014 paper.
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Forked from nipy/nibabel
Python package to access a cacophony of neuro-imaging file formats
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Forked from nilearn/nilearn
NeuroImaging with the Scikit-learn: fMRI inverse inference tutorial
Python 1
251 contributions in the last year
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February 2021
Created 5 commits in 2 repositories
Reviewed 25 pull requests in 4 repositories
nilearn/nilearn 20 pull requests
- [MRG] Mosaic mode of displaying brain images
- NiftiLabelsMasker Reporting
- Solving "NiftiMapsMasker and NiftiLabelsMasker cannot transform 3D images"
- Resampling functionality for NeuroVault
- Raise warning for FirstLevelModel fit when confounds and design_matrices are both specified
- [MRG] Allow asymmetric matrices in plot_connectome
- Fixes numpy runtime warning in masking.py when img has NaNs.
- fix sampling in generate_fake_fmri_data_and_design
- [MRG] High variance confounds in maskers
- Support atlases in plot_carpet
- [FIX] get_clusters_table: ensure input is 3D and accept filenames
- MAINT: Avoid NumPy deprecations
- Warn in nifti masker report when no image provided to fit
- [MRG] Handle nans in surf plotting
- [MRG] Update surface functions
- fix for FirstLevelModel compute_contrast for multiple runs with varying matrice size or columns
- [MRG] Glm duplicate events
- [MRG] Fix failures due to numpy 1.20
- Add fields/sections for issue information to templates
- Document design matrix baseline fix in What's New