Merry Christmas everyone 
Santa has brought you Nilearn 0.11.0… and 0.11.1 to fix the bugs 
of 0.11.0!
This version includes a new “surface” API that allows to represent surface meshes and data. 
Update from PyPi
pip install --upgrade nilearn
New features
- PolyMesh (and PolyData) can be used to instantiate mesh (and respectively data) objects with both hemispheres.
- SurfaceImage are objects that hold meshes and data for both hemispheres.
- SurfaceImage, PolyMesh, PolyData allow you to load and save mesh or data from one hemisphere from or to a Gifti file. SurfaceImage can also be instantiated directly with a nifti image and a mesh to project it on.
- Surface plotting functions have been adapted to work with SurfaceImage objects.
- To facilitate extracting data from those SurfaceImage objects, this new release also introduces SurfaceMasker and SurfaceLabelsMasker, SurfaceMapsMasker as counterparts to the volumetric NiftiMasker and NiftiLabelsMasker, NiftiMapsMasker.
- Several classes will already accept SurfaceImage and SurfaceMasker as inputs: Decoder, DecoderRegressor, FREMClassifier, FREMRegressor, FirstLevelModel, SecondLevelModel. Moreover first_level_from_bids will be able to build FirstLevelModel with the fsaverage5 files generated by fmriprep to directly analysis with surface data.
Code examples
To learn more about these new features see our new examples:
We have also updated several examples to make use of it:
- Loading and plotting of a cortical surface atlas
- Making a surface plot of a 3D statistical map
- Seed-based connectivity on the surface
- Cortical surface-based searchlight decoding
- Example of surface-based first-level analysis
- Surface-based dataset first and second level analysis of a dataset
Full changelog
You can see the full changelog of these releases here: What’s new - Nilearn
The full list of pull requests included in these versions:
The full “diff” since last version:
- https://github.com/nilearn/nilearn/compare/0.10.4…0.11.0
- https://github.com/nilearn/nilearn/compare/0.11.0…0.11.1
New contributors
Thanks to our 13 new contributors !!!
- alexsayal (Alexandre Sayal) · GitHub made their first contribution in add width input to view_img() by alexsayal · Pull Request #4416 · nilearn/nilearn · GitHub
- YCHuang0610 (YC H) · GitHub made their first contribution in [FIX] Refactor design matrix and contrast formula for the two-sample T-test example by YCHuang0610 · Pull Request #4407 · nilearn/nilearn · GitHub
- ajoshiusc (Anand A Joshi) · GitHub made their first contribution in [ENH] Add warning for future change of the default of `force_resample` to True by ajoshiusc · Pull Request #4412 · nilearn/nilearn · GitHub
- arovai · GitHub made their first contribution in Update second_level.py by arovai · Pull Request #4483 · nilearn/nilearn · GitHub
- muddi900 (Mudassir Chapra) · GitHub made their first contribution in [API] renamed `ax` parameter for consistency by muddi900 · Pull Request #4476 · nilearn/nilearn · GitHub
- victoris93 (Victoria Shevchenko) · GitHub made their first contribution in https://github.com/nilearn/nilearn/pull/4558
- kaitj (Jason Kai) · GitHub made their first contribution in [MAINT] Optimize `_resample_one_img` logic check for nearest interpolation by kaitj · Pull Request #4571 · nilearn/nilearn · GitHub
- tharun634 (Tharun K) · GitHub made their first contribution in [FIX] `first_level_from_bids` will now return subjects in order by tharun634 · Pull Request #4582 · nilearn/nilearn · GitHub
- hndgzkn (Hande Gözükan) · GitHub made their first contribution in [FIX] fix error PTH122 from by hndgzkn · Pull Request #4590 · nilearn/nilearn · GitHub
- PrakharJain1509 (Prakhar Jain) · GitHub made their first contribution in https://github.com/nilearn/nilearn/pull/4620
- anupriyakkumari (Anupriya) · GitHub made their first contribution in [DOC] Add missing default values to the docstrings in 'nilearn/glm' - part 1 by anupriyakkumari · Pull Request #4656 · nilearn/nilearn · GitHub
- mibur1 (Micha Burkhardt) · GitHub made their first contribution in [FIX] Make load_confounds return None for confounds if no cleaning strategy is provided by mibur1 · Pull Request #4636 · nilearn/nilearn · GitHub
- joycebrum (Joyce) · GitHub made their first contribution in [FIX] GitHub workflow script injection by joycebrum · Pull Request #4722 · nilearn/nilearn · GitHub
- tpremrud (Thiti Premrudeepreechacharn) · GitHub made their first contribution in [DOC] Add comparison of meaning differences of GLM between different libraries by tpremrud · Pull Request #4287 · nilearn/nilearn · GitHub
- badrinini · GitHub made their first contribution in [FIX] Add ClassVar type to mutable class defaults by badrinini · Pull Request #4954 · nilearn/nilearn · GitHub
Nilearn links
- Github: GitHub - nilearn/nilearn: Machine learning for NeuroImaging in Python
- Bluesky: @nilearn.bsky.social on Bluesky
- X: x.com
- Mastodon: Nilearn (@nilearn@fosstodon.org) - Fosstodon
- Pypi: nilearn · PyPI
- Documentation: https://nilearn.github.io
- Discord: Nilearn
- Zenodo DOI: nilearn
- Youtube: https://www.youtube.com/channel/UCU6BMAi2zOhNFnDkbdevmPw