Abstract
In this paper, we tested the efficiency of a two-step blind source separation (BSS) approach for the extraction of independent sources of α-activity from ongoing electroencephalograms (EEG). The method starts with a denoising source separation (DSS) of the recordings, and is followed by either an independent component analysis (ICA) or a temporal decorrelation algorithm (FastICA and TDSEP, respectively). This two-step method was compared with DSS, ICA and TDSEP alone. The tests were performed with simulated data based on real EEG signal, to guarantee the existence of a “ground truth”. The most efficient algorithm, for proper component extraction (regardless of the amount of α-activity in their spectra) is a combination of DSS and ICA. It provided also more stable results than ICA alone. TDSEP, in combination with DSS, was efficient only for the extraction of the components with prominent α-activity.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Borisov, S., Ilin, A., Vigário, R., Kaplan, A.: Source localization of low- and high-amplitude alpha activity: A segmental and DSS analysis. In: 11th Annual Meeting of Organization for Human Brain Mapping (OHBM) (June 2005); Neuroimage 26(suppl. 1), 38 (2005)
Delorme, A., Makeig, S.: EEG changes accompanying learned regulation of 12-Hz EEG activity. IEEE Trans. Neural. Syst. Rehabil. Eng. 11, 133–137 (2003)
Hyvarinen, A., Karhunen, J., Oja, E.: Independent Component Analysis. J. Wiley, Chichester (2001)
Jung, T.-P., Makeig, S., McKeown, M.J., Bell, A.J., Lee, T.-W., Sejnowski, T.J.: Imaging Brain Dynamics Using Independent Component Analysis. Proceedings of the IEEE 89, 1107–1122 (2001)
Kaplan, A.Y., Fingelkurts, A.A., Fingelkurts, A.A., Borisov, S.V., Darkhovsky, B.S.: Nonstationary nature of the brain activity as revealed by EEG/MEG: methodological, practical and conceptual challenges. Signal Processing 85, 2190–2212 (2005)
Makeig, S., Enghoff, S., Jung, T.P., Sejnowski, T.J.: A natural basis for efficient brainactuated control. IEEE Trans. Rehabil. Eng. 8, 208–211 (2000)
Särelä, J., Valpola, H.: Denoising Source Separation. Journal of machine learning research 6, 233–272 (2005)
Särelä, J., Vigário, R.: Overlearning in marginal distribution-based ICA: analysis and solutions. Journal of machine learning research 4, 1447–1469 (2003)
Tang, A., Pearlmutter, B., Malaszenko, N., Phung, D., Reeb, B.: Independent Components of Magnetoencephalography: Localization. Neural Computation 14, 1827–1858 (2002)
Vigário, R., Särelä, J., Jousmäki, V., Hämäläinen, M., Oja, E.: Independent component approach to the analysis of EEG and MEG recordings. IEEE transactions on biomedical engineering 47, 589–593 (2000)
Ylipaavalniemi, J., Vigário, R.: Analysis of Auditory fMRI Recordings via ICA: A Study on Consistency. In: Proceedings of the 2004 International Joint Conference on Neural Networks (IJCNN 2004), July 2004, vol. 1, pp. 249–254 (2004)
Ziehe, A., Müller, K.-R.: TDSEP - An Effective Algorithm for Blind Separation Using Time Structure. In: Proceedings of the 8th International Conference on Artificial Neural Networks (ICANN 1998), vol. 8, pp. 675–680 (1998)
FastICA Package online at, http://www.cis.hut.fi/research/ica/fastica
TDSEP Package online at, http://wwwold.first.fhg.de/~ziehe/download.html
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Borisov, S., Ilin, A., Vigário, R., Oja, E. (2006). Comparison of BSS Methods for the Detection of α-Activity Components in EEG. In: Rosca, J., Erdogmus, D., Príncipe, J.C., Haykin, S. (eds) Independent Component Analysis and Blind Signal Separation. ICA 2006. Lecture Notes in Computer Science, vol 3889. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11679363_54
Download citation
DOI: https://doi.org/10.1007/11679363_54
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-32630-4
Online ISBN: 978-3-540-32631-1
eBook Packages: Computer ScienceComputer Science (R0)