350 rub
Journal Neurocomputers №12 for 2011 г.
Article in number:
Sources of brain activity relevant and not relevant for classifying of EEG patterns, corresponding to motor imagination
Authors:
P. D. Bobrov, D. Husek, A. V. Korshakov, A. A. Frolov
Abstract:
The paper examines the sources of brain activity, contributing to EEG patterns, corresponding to motor imagination. The accuracy of their classifying specifies the efficiency of brain-computer interface (BCI), allowing to control external technical devices directly by signals of brain activity instead of natural muscle forces. The sources of brain activity corresponding to motor imagination are revealed by Independent Component Analysis (ICA). EEG during motor imagination is shown to be a superposition of components dependent and not dependent of the type of imaginary movement. Components dependent on the type of imaginary movement are relevant for EEG pattern classifying. They are localized in central brain areas. Components not dependent of the type of imaginary movement are localized in occipital areas. They relate to the attention to task performance independently of the imaginary movement and not relevant for BCI efficiency. Excluding of these components from EEG patterns improves essentially the BCI performance.
Pages: 3-15
References
  1. Блум Ф., Лейзерсон А., Хофстедтер Л. Мозг, разум и поведение. М.: Мир. 1988.
  2. Галкина Н.С., Боравова А.И. Динамика формирования мю- и альфа-ритмов электроэнцефалограммы детей 2-3-го года жизни // Физиология человека. 1996. № 5. С. 30-36.
  3. Berg, P., Scherg, M., Dipole modelling of eye activity and its application to the removal of eye artefacts from the EEG and MEG. Clin // Phys. Physiol. Meas. 1991. 12 Suppl. A.49-54.
  4. Bobrov, P., Frolov, A., Cantor, C., Fedulova, I., Bakhnyan, M., Zhavoronkov, A.,Brain-Computer Interface Based on Generation of Visual Images.PLoS ONE. 2011. 6(6):e20674.doi:10.1371/journal.pone.0020674
  5. Daly, J.J. and Wolpaw, J.R., Brain-computer interfaces in neurological rehabilitation // The Lancet Neurilogy. 2008. 7. 11. Р. 1032-1043.
  6. Delorme, A., Makeig, S., EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics. Journal of Neuroscience Methods. 2004. 134. P. 9-21.
  7. Frolov, A., Husek, D., Bobrov, P., Comparison of four classification methods for brain computer interface. Neural Network World, 2011. 21(2). P. 101-192.
  8. Hyvarinen, A., Karhunen, J., Oje, E., Independent component analysis. Willey, New-York. 2002.
  9. Kachenoura, A., Albera, L., Senhadji, L., Comon, P., ICA: a potential tool for BCI systems // IEEE Signal Processing Magazine. 2008. 25(1). P. 57-68.
  10. Krusienski, D.J., Wolpaw, J.W., Brain-computer interface research at the Wadsworth center: Development in noninvasive communication and control // International Review of Neurobiology. 2009.86. P. 147-157.
  11. Neuper, С., Pfurtscheller, G., Motor imagery and ERD, in: Event-Related Desynchronization. Handbook of Electroenceph. And Clin // Neurophysiol, rev. ed, G. Pfurtscheller and F. H. L. da Silva, Eds. Amsterdam, The Netherlands: Elsevier. 1999.
  12. Pfurtscheller, G., EEG event-related desynchronization (ERD) and eventrelated synchronization (ERS) // Niedermeyer E, Lopes da Silva FH, editors. Electroencephalography: basic principles, clinical applications and related fields, 4th ed. Baltimore. MD: Williams and Wilkins. 1999.
  13. Pfurtscheller, G., Neuper, C., Event-related synchronization of mu rhythm in the EEG over the cortical hand area in man // Neurosci. Lett. 1994. 174. P. 93-96.
  14. Storm van Leeuwen, W., Arntz, A., Spoelstra, P., Wieneke, G.H., The use of computer analysis for diagnosis in routine electroencephalography // Rev. EEG Neurophysiol. 1976. 2. P. 318-327.
  15. Suffczynski, P., Kalitzin, S., Pfurtscsheller, G., Lopes da Silva, F.H.,Computantional model of thalamo-cortical networks: dynamical control of alpha rhythms in relation to focal attention // Inernational Journal of Psychophysiology. 2001. 43:25-40.
  16. Wolpaw, J.R., Birbaumer, N., McFarland, D.J., Pfurtscheller, G., Vaugan, T.M., Brain-computer interface for communication and control // Clinical Neurophysiology. 2002. 113. P. 767-791.