A closed-loop EEG-based visual stimulation framework from controllable generation

Conceptualization.

The closed-loop Framework.

Environment setup

You can create a new conda environment and install the required dependencies by running

conda env create -f environment.yml
conda activate BCI

pip install wandb
pip install einops

Data availability

We provide you with the preprocessed EEG data used in our paper at Hugging Face, as well as the raw image data.

You can also download the relevant THINGS-EEG data set and THINGS-MEG data set at osf.io.

The raw and preprocessed EEG dataset, the training and test images are available on osf.

• Raw EEG data: ../project_directory/eeg_dataset/raw_data/.
• Preprocessed EEG data: ../project_directory/eeg_dataset/preprocessed_data/.
• Training and test images: ../project_directory/image_set/.

Code description

• EEG-preprocessing: preprocess the raw EEG data.
• EEG-encoding: synthesize the EEG responses to images through end-to-end encoding models.
• EEG-feature: Maximize the elicitation of neural activities such as image retrieval and stimulus generation