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Changes in the N200 and P300 Components of Event-Related Potentials on Variations in the Conditions of Attention in a Brain–Computer Interface System

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We put forward the hypothesis that the amplitudes of the P300 and N200 components of visual potentials evoked by flashes of the columns and rows of symbols in a matrix depend on the nature of the task attracting the operator’s attention to target symbol stimuli: 1) simple observation of the flashes of the target symbol; 2) observation with counting the numbers of these flashes and monitoring the success of this operation; 3) observation of the flashes of the target symbol with display of the symbol on a screen when the subject’s attention to this symbol was detected using the EEG as a brain–computer interface. Studies using a group of 17 subjects showed that the maximum amplitudes of the P300 and N200 components of visual potentials were reached to a statistically significant level in the second operator attention regime, which did not require involvement in a brain–computer interface. The second condition showed the largest number of statistically significant differences between the amplitudes of the P300 and N200 components of visual potentials evoked by flashes of target and nontarget symbols. At the same time, the smallest amplitudes of these components and the smallest differences between reactions to the target and nontarget stimuli were seen in conditions of simple observation of the flashes of the target stimuli. These results lead to the conclusion that successful operator functioning in a brain–computer interface does not require the maximal expression of the P300 and N200 components of visual potentials, which probably start to be optimized in the brain–computer interface in the task of controlling external processes, such as display of the target symbol on the computer screen.

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References

  1. Brunner, P., Joshi, S., Briskin, S., et al., “Does the ‘P300’ speller depend on eye gaze?” J. Neural. Eng., 7, No. 5, 056013 (2010).

  2. Farwell, L. A. and Donchin, E., “Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials,” EEG Clin. Neurophysiol., 70, 510–523 (1988).

    Article  CAS  Google Scholar 

  3. Frenzel, S., Neubert, E., and Bandt, C., “Two communication lines in a 3 × 3 matrix speller,” J. Neural. Eng., 8, No. 3, 036021 (2011).

  4. Frolov, A. A., Biryukova, E. V., Bobrov, P. D., et al., “Principles of neurorehabilitation based on the use of a ‘brain–computer’ interface and a biologically appropriate exoskeleton control,” Fiziol. Cheloveka, 39, No. 2, 99–113 (2013).

    CAS  PubMed  Google Scholar 

  5. Ganin, I. P., Shishkin, S. L., Kochetova, A. G., and Kaplan, A. Ya., “A P300 wave brain–computer interface: studies of the effects of the position of the stimulus in the presentation sequence,” Fiziol. Cheloveka, 38, No. 2, 5–13 (2012).

  6. Kaplan, A. Ya, Kochetova, A. G., Shishkin, S. L., et al., “Experimental and theoretical grounds and practical realization of the brain–computer interfaces,” Byull. Sib. Med., 12, No. 2, 21–29 (2013).

  7. Krusienski, D. J., Sellers E. W., McFarland, D. J., et al., “Toward enhanced P300 speller performance,” J. Neurosci. Meth., 167, 15–21 (2008).

    Article  CAS  Google Scholar 

  8. Krusienski, D. J., Sellers, E. W., Cabestaing, F., et al., “A comparison of classification techniques for the P300 speller,” J. Neural Eng., 3, No. 4, 299–305 (2006).

    Article  PubMed  Google Scholar 

  9. Mikhailova, E. S., Chicherov, V. A., Ptushenko, I. A, and Shevelev, I. A., “Spatial gradient of the P300 wave of the visual evoked potential of the human brain in a model of a neurocomputer interface,” Zh. Vyssh. Nerv. Deyat., 58, No. 3, 302–308 (2008).

    CAS  Google Scholar 

  10. Ortner, R., Aloise, F., Prückl, R., et al., “Accuracy of a P300 speller for people with motor impairments: a comparison,” Clin. EEG Neurosci., 42, No. 4, 214–218 (2011).

    Article  PubMed  Google Scholar 

  11. Piccione, E, Giorgi, F., Tonin, P., et al., “P300-based brain–computer interface: reliability and performance in healthy and paralysed participants,” Clin. Neurophysiol., 117, No. 3, 531–537 (2006).

    Article  CAS  PubMed  Google Scholar 

  12. Shishkin, S. L., Ganin, L. P., Basyul, I. A., et al., “N1 wave in the P300 BCI is not sensitive to the physical characteristics of stimuli,” J. Integr. Neurosci., 8, No. 4, 471–485 (2009).

    Article  PubMed  Google Scholar 

  13. Treder, M. S. and Blankertz, B., “(C)overt attention and visual speller design in an ERP-based brain–computer interface,” Behav. Brain Funct. , 6, 28 (2010).

    Article  PubMed Central  PubMed  Google Scholar 

  14. Vidal, J. J., “Real-time detection of brain events in EEG,” IEEE Proc., 65, 633–641 (1977).

    Article  Google Scholar 

  15. Wolpaw, J. R., Birbaumer, N., McFarland, D. J., et al., “Brain–computer interfaces for communication and control,” Clin. Neurophysiol., 113, 767–791 (2002).

    Article  PubMed  Google Scholar 

  16. Wolpaw, J. R., McFarland, D. J., Neat, G. W., and Forneris, C. A., “An EEG-based brain–computer interface for cursor control,” EEG Clin. Neurophysiol., 78, No. 3, 252–259 (1991).

    Article  CAS  Google Scholar 

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Correspondence to A. Ya. Kaplan.

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Translated from Zhurnal Vysshei Nervnoi Deyatel’nosti imeni I. P. Pavlova, Vol. 64, No. 2, pp. 159–165, March–April, 2014.

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Basyul, I.A., Kaplan, A.Y. Changes in the N200 and P300 Components of Event-Related Potentials on Variations in the Conditions of Attention in a Brain–Computer Interface System. Neurosci Behav Physi 45, 1038–1042 (2015). https://doi.org/10.1007/s11055-015-0183-8

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  • DOI: https://doi.org/10.1007/s11055-015-0183-8

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