This repository contains notebooks for running xCEBRA-based analyses and figure generation for schizophrenia time-series experiments. See our manuscript: “An explainable AI latent space of brain dynamics reveals a cerebello-prefrontal signature of schizophrenia symptoms” Moritz Bonhoeffer, Paolo Muratore, Mackenzie Weygandt Mathis & Indrit Bègue.
xCEBRA_combined.ipynb — main xCEBRA workflow.Ensemble_xCEBRA_models.ipynb — ensemble modeling workflow.Decode_clinical_variables_different_decoders.ipynb — decoder comparison for clinical variables.Data_Pipeline_for_publishing/ — preprocessing and atlas/time-course preparation notebooks.Plotting_for_figures/ — plotting notebooks and generated figures.python -m venv .venvsource .venv/bin/activate (Linux/macOS) or .venv\\Scripts\\activate (Windows)pip install -r requirements.txtjupyter notebookData_Pipeline_for_publishing/*.ipynbxCEBRA_combined.ipynbEnsemble_xCEBRA_models.ipynbDecode_clinical_variables_different_decoders.ipynbPlotting_for_figures/*.ipynbdocker build -t xcebra-schizophrenia .docker run --rm -p 8888:8888 -v "$PWD":/workspace xcebra-schizophreniaInstall all dependencies:
pip install -r requirements.txt
Primary runtime stack:
torch)cebra)numpy, pandas, scipy, scikit-learnnibabel, nilearn, SUITPymatplotlib, seabornjoblib, pingouin, openpyxlnotebook, ipykernelflowchart TD
NB[Notebooks in this repo] --> CORE[torch + cebra]
NB --> SCI[numpy + pandas + scipy + scikit-learn]
NB --> NEURO[nibabel + nilearn + SUITPy]
NB --> PLOT[matplotlib + seaborn]
NB --> UTIL[joblib + pingouin + openpyxl]
This repo includes Jupyter Book configuration files:
_config.yml_toc.ymlTo build and serve the book locally:
pip install jupyter-bookjupyter-book build ._build/html/index.html