MultiView ICA

Code accompanying the paper MultiViewICA https://arxiv.org/pdf/2006.06635.pdf

Documentation: https://hugorichard.github.io/multiviewica/

Install

Clone the repository

git clone https://github.com/hugorichard/multiviewica.git

Move into the multiviewica directory

cd multiviewica

Install MultiView ICA

pip install -e .

Requirements

For the core algorithms:

• numpy >= 1.16
• scipy >= 1.12
• scikit-learn >= 0.20
• python-picard >= 0.4 (pip install python-picard)

For the Experiments:

• nibabel (>=2.3.3)
• mne (>=0.20)
• nilearn (>=0.5)
• fastsrm (pip install fastsrm)

Experiments

Synthetic experiment

Move into the multiviewica directory

cd multiviewica

Run the experiment on synthetic data

python examples/synthetic_experiment.py

In order to reproduce the figure in the paper, use (might take a long time):

# sigmas: data noise
# m: number of subjects
# k: number of components
# n: number of samples
sigmas = np.logspace(-2, 1, 21)
n_seeds = 100
m, k, n = 10, 15, 1000

Experiments on fMRI data

Download and mask Sherlock data

Move into the data directory

cd multiviewica/data

Launch the download script (Runtime 34m6.751s)

bash download_data.sh

Mask the data (Runtime 15m27.104s)

python mask_data.py

Reconstructing BOLD signal of missing subjects

Move into the real_data_experiments directory

cd multiviewica/real_data_experiments

Run the experiment on masked data (Runtime 30m55.347s)

python reconstruction_experiment.py

This runs the experiment with n_components = 5 and benchmark PCA + GroupICA, PermICA and MultiView ICA with subject specific PCA for dimension reduction in PCA + GroupICA and SRM for PermICA and MultiView ICA.

Timesegment matching

Move into the real_data_experiment directory

cd multiviewica/real_data_experiments

Run the experiment on masked data (Runtime 17m39.520s)

python timesegment_matching.py

This runs the experiment with n_components = 5 and benchmark PCA + GroupICA, PermICA and MultiView ICA with subject specific PCA for dimension reduction in PCA + GroupICA and SRM for PermICA and MultiView ICA.

Cite

If you use this code in your project, please cite:

@inproceedings{NEURIPS2020_de03beff,
 author = {Richard, Hugo and Gresele, Luigi and Hyvarinen, Aapo and Thirion, Bertrand and Gramfort, Alexandre and Ablin, Pierre},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {H. Larochelle and M. Ranzato and R. Hadsell and M. F. Balcan and H. Lin},
 pages = {19149--19162},
 publisher = {Curran Associates, Inc.},
 title = {Modeling Shared responses in Neuroimaging Studies through MultiView ICA},
 url = {https://proceedings.neurips.cc/paper/2020/file/de03beffeed9da5f3639a621bcab5dd4-Paper.pdf},
 volume = {33},
 year = {2020}
}