References and Citations#

Key Publications#

EEG Preprocessing Methods#

The following papers describe key preprocessing methods implemented in EEGPrep:

Artifact Removal and Cleaning

  • Delorme, A., & Makeig, S. (2004). EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. Journal of Neuroscience Methods, 134(1), 9-21.

    • Foundational paper for EEGLAB and many preprocessing techniques

  • Kothe, C. A., & Makeig, S. (2013). BCILAB: a platform for brain–computer interface development. Journal of Neural Engineering, 10(5), 056014.

    • Describes ASR (Artifact Subspace Reconstruction) algorithm

  • Onton, J., Westerfield, M., Townsend, J., & Makeig, S. (2006). Imaging human EEG dynamics using independent component analysis. Neuroscience & Biobehavioral Reviews, 30(6), 808-822.

    • ICA for EEG analysis

Independent Component Analysis (ICA)

  • Hyvärinen, A., & Oja, E. (2000). Independent component analysis: algorithms and applications. Neural Networks, 13(4-5), 411-430.

    • Comprehensive ICA review

  • Bell, A. J., & Sejnowski, T. J. (1995). An information-maximization approach to blind separation and blind deconvolution. Neural Computation, 7(6), 1129-1159.

    • Infomax ICA algorithm

ICLabel Component Classification

  • Pion-Tonachini, L., Kreutz-Delgado, K., & Makeig, S. (2019). ICLabel: Automated electroencephalographic independent component classification, labeling and brain source estimation. NeuroImage, 198, 181-197.

    • Deep learning-based IC classification

BIDS Format

  • Gorgolewski, K. J., Auer, T., Calhoun, V. D., et al. (2016). The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments. Scientific Data, 3, 160044.

    • BIDS specification paper

  • Pernet, C. R., Appelhoff, S., Gorgolewski, K. J., et al. (2019). EEG-BIDS, an extension to the brain imaging data structure for electroencephalography. Scientific Data, 6, 103.

    • EEG-BIDS extension

Signal Processing

  • Widmann, A., Schröger, E., & Maess, B. (2015). Digital filter design for electrophysiological data–a practical approach. Journal of Neuroscience Methods, 250, 34-46.

    • Filter design for EEG

External Resources#

Tutorials and Documentation#

EEG Analysis Tutorials

Signal Processing

Machine Learning

Forums and Communities#

GitHub

NeuroTalk

  • NeuroTalk Forums - Neuroscience discussion forums

  • EEG and neuroimaging discussions

Stack Overflow

Reddit

Datasets#

Public EEG Datasets

Citation Information#

How to Cite EEGPrep#

If you use EEGPrep in your research, please cite it as:

BibTeX:

@software{eegprep2024,
  title={EEGPrep: A comprehensive Python EEG preprocessing pipeline},
  author={EEGPrep Contributors},
  year={2024},
  url={https://github.com/NeuroTechX/eegprep}
}

APA Format:

EEGPrep Contributors. (2024). EEGPrep: A comprehensive Python EEG preprocessing pipeline. Retrieved from NeuroTechX/eegprep

Chicago Format:

EEGPrep Contributors. “EEGPrep: A comprehensive Python EEG preprocessing pipeline.” Accessed 2024. NeuroTechX/eegprep.

Citing Dependencies#

If you use specific algorithms, please also cite the original papers:

For ASR (Artifact Subspace Reconstruction):

@article{kothe2013bcilab,
  title={BCILAB: a platform for brain--computer interface development},
  author={Kothe, Christian A and Makeig, Scott},
  journal={Journal of Neural Engineering},
  volume={10},
  number={5},
  pages={056014},
  year={2013},
  publisher={IOP Publishing}
}

For ICLabel:

@article{pion2019iclabel,
  title={ICLabel: Automated electroencephalographic independent component classification, labeling and brain source estimation},
  author={Pion-Tonachini, Luca and Kreutz-Delgado, Kenneth and Makeig, Scott},
  journal={NeuroImage},
  volume={198},
  pages={181--197},
  year={2019},
  publisher={Elsevier}
}

For EEGLAB:

@article{delorme2004eeglab,
  title={EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis},
  author={Delorme, Arnaud and Makeig, Scott},
  journal={Journal of Neuroscience Methods},
  volume={134},
  number={1},
  pages={9--21},
  year={2004},
  publisher={Elsevier}
}

Acknowledgments#

Contributors#

EEGPrep is developed and maintained by the NeuroTechX community. We thank all contributors who have helped improve the project through code contributions, bug reports, and feedback.

Funding#

EEGPrep development has been supported by:

  • NeuroTechX community

  • Open-source software initiatives

  • Academic institutions

Inspiration and Acknowledgments#

EEGPrep builds upon the excellent work of:

  • EEGLAB: For pioneering EEG preprocessing and analysis tools

  • MNE-Python: For comprehensive neuroimaging analysis

  • Fieldtrip: For robust signal processing methods

  • Brainstorm: For user-friendly neuroimaging software

We acknowledge the neuroscience and signal processing communities for their contributions to EEG analysis methods.

Getting Help with References#

  • Check the User Guide for implementation details

  • Review Examples for practical examples

  • Search GitHub Issues for related discussions

  • Contact the maintainers for citation questions

For more information about EEG analysis methods, see the Glossary for terminology definitions.