Decoding executed and imagined grasping movements from distributed non-motor brain areas using a Riemannian decoder

Code used in:

Ottenhoff MC, Verwoert M, Goulis S, Colon AJ, Wagner L, Tousseyn S, van Dijk JP, Kubben PL and Herff C (2023) - Decoding executed and imagined grasping movements from distributed non-motor brain areas using a Riemannian decoder. Front. Neurosci. 17:1283491. doi: 10.3389/fnins.2023.1283491

Read the paper
Access the data

Installation

Tested for python 3.9, but other versions will likely work as well.

git clone https://github.com/mottenhoff/distributed_motor_decoding.git
Download the data to the cloned repository folder. I used ./data to save the data, but you can change the the folder in decode.py:run() data_path.

conda create --name your_env_name python=3.9
conda activate your_env_name
pip install -r requirements.txt

Running code

Decoder:

run python main.py

To run all files in parallel, set PARALLEL in main.py to True.
main.py:main() also contains all the variables used (exps, bands and ppts).
To change the included components, change the n_components in decode.py:run().
To run the CSP analysis, set DECODE_CSP_LDA in decode.py:42 to True.

Plot results

run plot_figures.py
Set the path to the results in plot_figures.py():run() -> path_results