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Single Trial Estimation of Peak Latency and Amplitude of Multiple Correlated ERP Components

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Abstract

Event related potentials (ERPs) are conventionally extracted by averaging EEG signals over many trials but some characteristics of these signals are lost as a result. Recently single-trial ERP extraction has become one of the main research areas in neuroscience. Spatiotemporal filtering method which uses more than one channel is one of these extraction methods. A modified spatiotemporal filtering method is proposed here for single-trial estimation of correlated ERP component parameters (peak latency and peak amplitude). The error of this method in extracting the peak amplitude and peak latency of ERP components is less than 10% and changing the temporal correlation coefficient of the main ERP components, does not change the results notably. Our proposed method for peak amplitude and peak latency estimation is proved to be better than other reported methods (especially for peak amplitude estimation) and has less computational cost in comparison with other spatiotemporal methods. The ability of our method to generalize to any number of correlated ERP components is one of the key points in our work.

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References

  1. Luck, S. (2005). An introduction to the event-related potential technique. Cambridge: The MIT Press.

    Google Scholar 

  2. Donchin, E., Ritter, W., & McCallum, C. (1978). Cognitive psychophysiology: The endogenous components of the ERP. In E. Callaway, P. Tueting, & S. Koslow (Eds.), Brain event-related potentials in man (pp. 349–441). New York, NY: Academic Press.

    Chapter  Google Scholar 

  3. Brazier, M. A. B. (1964). Evoked responses recorded from the depths of the human brain. Annals of New York Academy of Sciences, 112, 33–59.

    Article  Google Scholar 

  4. Al-Nashi, H. (1986). A maximum likelihood method for estimating EEG evoked potentials. IEEE Transactions on Biomedical Engineering, 33, 1087–1095.

    Article  Google Scholar 

  5. Cerutti, S., Bersani, V., Carrara, A., & Liberati, D. (1987). Analysis of visual evoked potentials through Wiener filtering applied to a small number of sweeps. Journal on Biomedical Engineering, 9, 3–12.

    Article  Google Scholar 

  6. Ouyang, G., Herzmann, G., Zhou, C., & Sommer, W. (2011). Residue iteration decomposition (RIDE): A new method to separate ERP components on the basis of latency variability in single trials. Psychophysiology, 48, 1631–1647.

    Article  Google Scholar 

  7. Aniyan, A. K., Philip, N. S., Samar, V. J., Desjardins, J. A., & Segalowitz, S. J. (2014). A wavelet based algorithm for the identification of oscillatory event-related potential components. Journal of Neuroscience Methods, 233, 63–72.

    Article  Google Scholar 

  8. Makeig, S., Delorme, A., Westerfield, M., Jung, T. P., Townsend, J., Courchesne, E., et al. (2004). Electroencephalographic brain dynamics following visual targets requiring manual responses. PLoS Biology, 2(6), 747–762.

    Article  Google Scholar 

  9. Glaser, E. M., & Ruchkin, D. S. (1976). Principles of neurobiological signal analysis. New York, NY: Academic Press.

    Google Scholar 

  10. Li, R., Principe, J. C., Bradley, M., & Ferrari, V. (2009). A spatiotemporal filtering methodology for single-trial ERP component estimation. IEEE Transactions on Biomedical Engineering, 56(1), 83–92.

    Article  Google Scholar 

  11. Li, R., Keil, A., & Principe, J. C. (2009). Single-trial P300 estimation with a spatiotemporal filtering method. Journal of Neuroscience Methods, 177, 488–496.

    Article  Google Scholar 

  12. Jarchi, D., Sanei, S., Principe, J. C., & Makkiabadi, B. (2011). A new spatiotemporal filtering method for single-trial estimation of correlated ERP subcomponents. IEEE Transactions on Biomedical Engineering, 58(1), 132–143.

    Article  Google Scholar 

  13. BrainStorm, MATLAB Toolbox, 2004. [Online]. Available: http://neuroimage.usc.edu/brainstorm.

  14. Freeman, W. (1975). Mass activation in the nervous system. New York, NY: Academic.

    Google Scholar 

  15. Richman, M. B. (1986). Rotation of principal components. Journal of Climatology, 6, 293–335.

    Article  Google Scholar 

  16. Dien, J. (2010). The ERP PCA toolkit: An open source program for advanced statistical analysis of event-related potential data. Journal of Neuroscience Methods, 187(1), 138–145.

    Article  MathSciNet  Google Scholar 

  17. Jin, J., Sellers, E. W., Zhou, S., Zhang, Y., Wang, X., & Cichocki, A. (2015). A P300 brain–computer interface based on a modification of the mismatch negativity paradigm. International Journal of Neural Systems, 25(3), 1550011-1–1550011-12.

    Article  Google Scholar 

  18. Belitski, A., Farquhar, J., & Desain, P. (2011). P300 audio-visual speller. Journal of Neural Engineering, 8, 025022.

    Article  Google Scholar 

  19. Yin, E., Zeyl, T., Saab, R., Hu, D., & Chau, T. (2016). An auditory-tactile visual saccade-independent P300 brain–computer interface. International Journal of Neural Systems, 26(1), 1650001-1–1650001-16.

    Article  Google Scholar 

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Correspondence to Mohammad Mikaeili.

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Ranjbar, M., Mikaeili, M. & Khorrami Banaraki, A. Single Trial Estimation of Peak Latency and Amplitude of Multiple Correlated ERP Components. J. Med. Biol. Eng. 38, 161–172 (2018). https://doi.org/10.1007/s40846-017-0309-2

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  • DOI: https://doi.org/10.1007/s40846-017-0309-2

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