文件列表:

.circleci/
.faq/
.vscode/
WIP/
binder/
demos/
docs/
lib/
src/
tests/
tools/
.all-contributorsrc
.dockerignore
.flake8
.hadolint.yaml
.pre-commit-config.yaml
.readthedocs.yml
CHANGELOG.md
CITATION.cff
CONTRIBUTING.md
Dockerfile
Dockerfile_matlab
LICENSE
Makefile
bidspm.m
faq.yml
miss_hit.cfg
pyproject.toml
test_api.m
version.txt

[](https://results.pre-commit.ci/latest/github/cpp-lln-lab/bidspm/main) [](https://misshit.org/) [](https://bidspm.readthedocs.io/en/stable/?badge=stable) [](https://mybinder.org/v2/gh/cpp-lln-lab/bidspm/main) [](https://github.com/cpp-lln-lab/bidspm/actions/workflows/tests.yml) [](https://github.com/cpp-lln-lab/bidspm/actions/workflows/tests_octave.yml) [](https://codecov.io/gh/cpp-lln-lab/bidspm) [](https://doi.org/10.5281/zenodo.3554331) [](https://github.com/cpp-lln-lab/bidspm.git) [](https://github.com/cpp-lln-lab/bidspm#contributors) # bidspm This is a Matlab / Octave toolbox to perform MRI data analysis on a [BIDS data set](https://bids.neuroimaging.io/) using SPM12. ## Installation ### From docker hub ```bash docker pull cpplab/bidspm:latest ``` ### From the source In a terminal or a git bash prompt, type: ```bash git clone --recurse-submodules https://github.com/cpp-lln-lab/bidspm.git ``` To get the latest version that is on the `dev` branch. ```bash git clone --recurse-submodules --branch dev https://github.com/cpp-lln-lab/bidspm.git ``` To start using bidspm, you just need to initialize it for this MATLAB / Octave session with: ```matlab bidspm() ``` Please see our [documentation](https://bidspm.readthedocs.io/en/latest/installation.html) for more info. ### Installing the Command line Interface (CLI) If you want to use the BIDS app python based CLI of bidspm. You need to - [python3](https://www.python.org/downloads/) - pip If you are using MATLAB, you need to edit the file `src/matlab.py`, so that it returns the fullpath to the MATLAB executable on your computer. You can then install the bidspm CLI from within the `bidspm` folder with: ```bash pip install . ``` You can then type the following to see which command you have access to: ```bash bidspm --help ``` ### BIDS validation After installing bidspm python package, you can get access to extra validation options. ### BIDS stats model validation Please see [the documentation](https://bidspm.readthedocs.io/en/latest/bids_stats_model.html#using-the-bids-stats-model-python-package) ### BIDS dataset validation To run the bids-validator when running bidspm, you will need: - [node.js and npm](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm) - the bidspm python CLI (see above) You can then install: - the bids validator by running from the command line in the root folder of the repository: ```bash make install ``` or ```bash npm install -g bids-validator ``` ## Usage For some of its functionality bidspm has a BIDS app like API. See [this page for more information](https://bidspm.readthedocs.io/en/latest/usage_notes.html). But in brief they are of the form: ```matlab bidspm(bids_dir, output_dir, ... 'analysis_level', ... 'action', 'what_to_do') ``` ### Creating a default BIDS statistical model Use a MATLAB / Octave script with: ```matlab % path to your raw BIDS dataset bids_dir = path_of_raw_bids_dataset; % where you want to save the model output_dir = path_where_the_output_should_go; tasks_to_include_in_model = {'task1', 'task2', 'task3'}; % for example 'MNI152NLin2009cAsym' space_to_include_in_model = {'spaceName'}; bidspm(bids_dir, output_dir, 'dataset', ... 'action', 'default_model', ... 'task', tasks_to_include_in_model, ... 'space', space_to_include_in_model) ``` ### GLM Use a MATLAB / Octave script with: ```matlab % path to your raw BIDS dataset bids_dir = path_of_raw_bids_dataset; % where you want to save the model output_dir = path_where_the_output_should_go; preproc_dir = path_to_preprocessed_dataset; % for example fmriprep output model_file = path_to_bids_stats_model_json_file; subject_label = '01'; bidspm(bids_dir, output_dir, 'subject', ... 'participant_label', {subject_label}, ... 'action', 'stats', ... 'preproc_dir', preproc_dir, ... 'model_file', model_file) ``` ### Preprocessing ```matlab bids_dir = path_to_raw_bids_dataset; output_dir = path_to_where_the_output_should_go; subject_label = '01'; bidspm(bids_dir, output_dir, 'subject', ... 'participant_label', {subject_label}, ... 'action', 'preprocess', ... 'task', {'yourTask'}) ``` ## Features ### Statistics The model specification are set up using the [BIDS stats model](https://bids-standard.github.io/stats-models/) and can be used to perform: - whole GLM at the subject level - whole brain GLM at the group level à la SPM (meaning using a summary statistics approach). - ROI based GLM (using marsbar) - model selection (with the MACS toolbox) ### Preprocessing If your data is fairly "typical" (for example whole brain coverage functional data with one associated anatomical scan for each subject), you might be better off running [fmriprep](https://fmriprep.org/en/stable/) on your data. If you have more exotic data that cannot be handled well by fmriprep then bidspm has some automated workflows to perform amongst other things: - remove dummies - slice timing correction - spatial preprocessing: - realignment OR realignm and unwarp - coregistration `func` to `anat`, - `anat` segmentation and skull stripping - (optional) normalization to SPM's MNI space - smoothing - fieldmaps processing and voxel displacement map creation (work in progress) All (well almost all) preprocessed outputs are saved as BIDS derivatives with BIDS compliant filenames. ### Quality control: - anatomical data (work in progress) - functional data (work in progress) - GLM auto-correlation check Please see our [documentation](https://bidspm.readthedocs.io/en/latest/index.html) for more info. ## Citation ```bibtex @software{bidspm, author = {Gau, Rémi and Barilari, Marco and Battal, Ceren and Rezk, Mohamed and Collignon, Olivier and Gurtubay, Ane and Falagiarda, Federica and MacLean, Michèle and Cerpelloni, Filippo and Shahzad, Iqra and Nunes, Márcia and Caron-Guyon, Jeanne and Chouinard-Leclaire, Christine and Yang, Ying and Mattioni, Stefania and Van Audenhaege, Alice and Matuszewski, Jacek}, license = {GPL-3.0}, title = {{bidspm}}, url = {https://github.com/cpp-lln-lab/bidspm}, version = {3.1.0} } ``` ### Posters - [OHBM 2023](https://doi.org/10.5281/zenodo.8099835) ## Contributors Thanks goes to these wonderful people ([emoji key](https://allcontributors.org/docs/en/emoji-key)):

Ane Gurtubay	Ceren Battal	Christine Chouinard-Leclaire	Federica Falagiarda	Filippo Cerpelloni	Iqra Shahzad	JacMatu
Jeanne Caron-Guyon	Manon Chateaux	Marco Barilari	Michèle MacLean	Mohamed Rezk	Márcia Nunes	Olivier Collignon
Remi Gau	Stefania Mattioni	Ying Yang	avanaudenhaege

This project follows the [all-contributors](https://github.com/all-contributors/all-contributors) specification. Contributions of any kind welcome!

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