This repository has code to reproduce results in the paper Hierarchical Bayesian estimation of motor-evoked potential recruitment curves yields accurate and robust estimates.
It uses the hbmep v0.5.0. See pyproject.toml for dependencies.
Begin by creating a virtual environment.
python3.11 -m venv .venv
Note that the above command uses Python 3.11. If you have a different version of Python, you can use conda to create a new environment with the required version of Python.
conda create -n python-311 python=3.11.9 -y
conda activate python-311
python -m venv .venv
conda deactivate
We can then install in editable mode.
@source .venv/bin/activate && \
pip install --upgrade pip && \
pip install -e .
Now, the Python interpreter should be located at .venv/bin/python
. You can use this to run the scripts in the notebooks directory.
Please cite Tyagi et al., 2024 if you find this code useful in your research. The BibTeX entry for the paper is:
@article{tyagi_hierarchical_2024, title = {Hierarchical {Bayesian} estimation of motor-evoked potential recruitment curves yields accurate and robust estimates}, author = {Tyagi, Vishweshwar and Murray, Lynda M. and Asan, Ahmet S. and Mandigo, Christopher and Virk, Michael S. and Harel, Noam Y. and Carmel, Jason B. and McIntosh, James R.}, journal={arXiv preprint arXiv:2407.08709}, year = {2024}, doi = {http://doi.org/10.48550/arXiv.2407.08709} }