py_neuromodulation
The py_neuromodulation toolbox allows for real time capable processing of multimodal electrophysiological data. The primary use is movement prediction for adaptive deep brain stimulation.
Find the documentation here https://neuromodulation.github.io/py_neuromodulation/ for example usage and parametrization.
Setup
For running this toolbox first create a new virtual conda environment:
conda env create --file=env.yml --user
The main modules include running real time enabled feature preprocessing based on iEEG BIDS data.
Different features can be enabled/disabled and parametrized in the `https://github.com/neuromodulation/py_neuromodulation/blob/main/pyneuromodulation/nm_settings.json>`_.
The current implementation mainly focuses band power and sharpwave feature estimation.
An example folder with a mock subject and derivate feature set was estimated.
To run feature estimation given the example BIDS data run in root directory.
python main.py
This will write write a feature_arr.csv file in the 'examples/data/derivatives' folder.
For further documentatin view ParametrizationDefinition for description of necessary parametrization files. FeatureEstimationDemo walks through an example feature estimation and explains sharpwave estimation.
GitHub
neuromodulation
