Post-hoc labeling of EEG for benchmarking of decoding methods

This is the source code for the post-hoc labelled dataset generation framework:

Castaño-Candamil, Sebastián, Andreas Meinel, and Michael Tangermann. "Post-hoc labeling of arbitrary M/EEG recordings for data-efficient evaluation of neural decoding methods." Frontiers in neuroinformatics 13 (2019).

Getting started

1. Run the download_dependecies.m script to download and configure the bbci_toolbox.
2. Download EEG data available at https://zenodo.org/record/1065107#.WhaCX3XyvCI and place the .mat files under ./data
3. Run the script test_postHocLabelling.m to see usage example.

Comments on the New York's head model -

The Original head model can be downloaded at https://www.parralab.org/nyhead/ The .mat available here was stripped to the strictly necessary data in order to run this toolbox. Head model is licensed under GPL v3:

The New York Head (ICBM-NY)

Copyright (C) 2015 Yu Huang (Andy), Lucas C. Parra and Stefan Haufe

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.

Contact: Yu (Andy) Huang
Dept. of Biomedical Engineering, City College of New York
Center for Discovery and Innovation, Rm. 13-320,
85 St Nicholas Terrace, New York, NY 10027
Email: [email protected]
[email protected]