Self-Organizing Maps for Event-Related Potential Data Analysis

Lukáš Vařeka, Pavel Mautner


Event-Related Potentials (ERPs) and especially the P300 component have been gaining attention in braincomputer interface design and neurobiological research. The detection of the P300 component in electroencephalographic signal is challenging since its signal-to-noise ratio is very low. Instead of using traditional supervised pattern recognition, this paper discusses using unsupervised neural networks for the P300 classification purposes. To validate the proposed approach, a method for the P300 detection based on matching pursuit and self-organizing maps is proposed and evaluated. The results may be applied to the design of brain-computer interfaces.


  1. Cashero, Z. (2012). Comparison of Eeg Preprocessing Methods to Improve the Performance of the P300 Speller. Proquest, Umi Dissertation Publishing.
  2. Dudacek, K., Mautner, P., Moucek, R., and Novotny, J. (Sept.). Odd-ball protocol stimulator for neuroinformatics research. In Applied Electronics (AE), 2011 International Conference on, pages 1-4.
  3. Durka, P. and Blinowska, K. (1995). Analysis of EEG transients by means of matching pursuit. Annals of Biomedical Engineering, 23(5):608-611.
  4. Fausett, L., editor (1994). Fundamentals of neural networks: architectures, algorithms, and applications. Prentice-Hall, Inc., Upper Saddle River, NJ, USA.
  5. Joutsiniemi, S. L., Kaski, S., and Larsen, A. T. (1995). Selforganizing map in recognition of topographic patterns of EEG spectra. IEEE Transactions on Biomedical Engineering, 42:1062-1068.
  6. Kohonen, T. (1989). Self-organization and associative memory: 3rd edition. Springer-Verlag New York, Inc., New York, NY, USA.
  7. Liang, N. and Bougrain, L. (2008). Non-identity Learning Vector Quantization applied to evoked potential detection. In Deuxième conférence franc¸aise de Neurosciences Computationnelles, ”Neurocomp08”, Marseille, France. ISBN : 978-2-9532965-0-1.
  8. Lotte, F., Congedo, M., Lécuyer, A., Lamarche, F., and Arnaldi, B. (2007). A review of classification algorithms for EEG-based brain-computer interfaces. Journal of neural engineering, 4(2).
  9. Luck, S. (2005). An introduction to the event-related potential technique. Cognitive neuroscience. MIT Press.
  10. Mak, J. N., Arbel, Y., Minett, J. W., McCane, L. M., Yuksel, B., Ryan, D., Thompson, D., Bianchi, L., and Erdogmus, D. (2011). Optimizing the P300-based brain-computer interface: current status, limitations and future directions. Journal of Neural Engineering, 8(2):025003+.
  11. Mallat, S. and Zhang, Z. (1993). Matching pursuit with time-frequency dictionaries. IEEE Transactions on Signal Processing, 41:3397-3415.
  12. Picton, T. W., Lins, O. G., and Scherg, M. (1995). The recording and analysis of event-related potentials. In Boller, F. and Grafman, J., editors, Handbook of Neuropsychology, volume 10, pages 3-73. Elsevier, Amsterdam.
  13. Polich, J. (2007). Updating P300: an integrative theory of P3a and P3b. Clinical neurophysiology, 118(10):2128-2148.
  14. Tomas Rondik, Jindrich Ciniburk, R. M. and Mautner, P. (2011). Erp components detection using wavelet transform and matching pursuit algorithm. In Applied Electronics 2011, pages 1-4.
  15. Vesanto, J., Himberg, J., Alhoniemi, E., and Parhankangas, J. (2000). Self-organizing map in matlab: the som toolbox. In In Proceedings of the Matlab DSP Conference, pages 35-40.

Paper Citation

in Harvard Style

Vařeka L. and Mautner P. (2014). Self-Organizing Maps for Event-Related Potential Data Analysis . In Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2014) ISBN 978-989-758-010-9, pages 387-392. DOI: 10.5220/0004885103870392

in Bibtex Style

author={Lukáš Vařeka and Pavel Mautner},
title={Self-Organizing Maps for Event-Related Potential Data Analysis},
booktitle={Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2014)},

in EndNote Style

JO - Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2014)
TI - Self-Organizing Maps for Event-Related Potential Data Analysis
SN - 978-989-758-010-9
AU - Vařeka L.
AU - Mautner P.
PY - 2014
SP - 387
EP - 392
DO - 10.5220/0004885103870392