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International Work-Conference on the Interplay Between Natural and Artificial Computation

IWINAC 2019: Understanding the Brain Function and Emotions pp 138–145Cite as

Group Differences in Time-Frequency Relevant Patterns for User-Independent BCI Applications

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11486))

Abstract

We present a comparison of two known methodologies for group analysis in EEG signals, which are the analysis by Group ICA on synchronization and desynchronization ERS/ERD, and brain connectivity analysis by measuring wPLI, both analyzes based on the brain synchronization information. For comparison, we have taken into account different frequency bands related to sensorimotor stimuli and time segmentation in order to overcome the nonstationarity of the EEG signal. In addition, we have used a threshold algorithm to reduce the dimension of the connectivity matrix, conserving the connections that are most important for both methodologies. The results obtained from the BCI competition IV-2a database show that the variable can be measured between two different measurement spaces, using the Euclidean distance, conserving spatial zones with more meaningful physiological interpretation.

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Notes

  1. 1.

    www.bbci.de/competition/iv/.

References

  1. Hardmeier, M., Hatz, F., Bousleiman, H., Schindler, C., Stam, C.J., Fuhr, P.: Reproducibility of functional connectivity and graph measures based on the phase lag index (PLI) and weighted phase lag index (wPLI) derived from high resolution EEG. PloS One 9(10), e108648 (2014)

    Article  Google Scholar 

  2. Allison, B.Z., Wolpaw, E.W., Wolpaw, J.R.: Brain-computer interface systems: progress and prospects. Expert Rev. Med. Dev. 4(4), 463–474 (2007)

    Article  Google Scholar 

  3. Huster, R., Plis, S.M., Calhoun, V.D.: Group-level component analyses of EEG: validation and evaluation. Front. Neurosci. 9, 254 (2015)

    Article  Google Scholar 

  4. Allen, E., Damaraju, E., Eichele, T., Wu, L., Calhoun, V.D.: EEG signatures of dynamic functional network connectivity states. Brain Topogr. 31(1), 101–116 (2018)

    Article  Google Scholar 

  5. Labounek, R., et al.: Stable scalp EEG spatiospectral patterns across paradigms estimated by group ICA. Brain Topogr. 31(1), 76–89 (2018)

    Article  Google Scholar 

  6. Zhang, Y., Zhou, G., Jin, J., Wang, X., Cichocki, A.: Optimizing spatial patterns with sparse filter bands for motor-imagery based brain-computer interface. J. Neurosci. Methods 255, 85–91 (2015)

    Article  Google Scholar 

  7. Dai, S., Wei, Q.: Electrode channel selection based on backtracking search optimization in motor imagery brain-computer interfaces. J. Integr. Neurosci. 16(3), 241–254 (2017)

    Article  MathSciNet  Google Scholar 

  8. Aviyente, S., Tootell, A., Bernat, E.M.: Time-frequency phase-synchrony approaches with ERPs. Int. J. Psychophysiol. 111, 88–97 (2017)

    Article  Google Scholar 

  9. Terrien, J., Germain, G., Marque, C., Karlsson, B.: Bivariate piecewise stationary segmentation; improved pre-treatment for synchronization measures used on non-stationary biological signals. Med. Eng. Phys. 35(8), 1188–1196 (2013)

    Article  Google Scholar 

  10. Reinhold Scherer, C.V.: Motor imagery based brain-computer interfaces, chap. 8, pp. 171 – 195 (2018)

    Google Scholar 

  11. Wolpaw, J.R., Birbaumer, N., McFarland, D.J., Pfurtscheller, G., Vaughan, T.M.: Brain-computer interfaces for communication and control. Clin. Neurophysiol. 113(6), 767–791 (2002)

    Article  Google Scholar 

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Acknowledgements

This work is supported by the project Programa de reconstrucción del tejido social en zonas de pos-conflicto en Colombia del proyecto Fortalecimiento docente desde la alfabetización mediática Informacional y la CTel, como estrategia didáctico-pedagógica y soporte para la recuperación de la confianza del tejido social afectado por el conflicto. Código SIGP 58950 Financiado por Fondo Nacional de Financiamiento para la Ciencia, la Tecnología y la Innovación, Fondo Francisco José de Caldas con contrato No 213-2018 con Código 58960.

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Authors and Affiliations

  1. Signal Processing and Recognition Group, Universidad Nacional de Colombia, Manizales, Colombia

    L. F. Velasquez-Martinez, F. Y. Zapata-Castaño, J. I. Padilla-Buritica & G. Castellanos-Dominguez

  2. Universidad Politécnica de Cartagena, Cartagena, Spain

    J. I. Padilla-Buritica & José Manuel Ferrández Vicente

Authors
  1. L. F. Velasquez-Martinez
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  2. F. Y. Zapata-Castaño
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  3. J. I. Padilla-Buritica
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  4. José Manuel Ferrández Vicente
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  5. G. Castellanos-Dominguez
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Corresponding author

Correspondence to L. F. Velasquez-Martinez .

Editor information

Editors and Affiliations

  1. Universidad Politécnica de Cartagena, Cartagena, Spain

    José Manuel Ferrández Vicente

  2. Universidad Nacional de Educación a Distancia, Madrid, Spain

    José Ramón Álvarez-Sánchez

  3. Universidad Nacional de Educación a Distancia, Madrid, Madrid, Spain

    Félix de la Paz López

  4. Universidad Politécnica de Cartagena, Cartagena, Spain

    Javier Toledo Moreo

  5. The Ohio State University, Columbus, OH, USA

    Hojjat Adeli

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Velasquez-Martinez, L.F., Zapata-Castaño, F.Y., Padilla-Buritica, J.I., Ferrández Vicente, J.M., Castellanos-Dominguez, G. (2019). Group Differences in Time-Frequency Relevant Patterns for User-Independent BCI Applications. In: Ferrández Vicente, J., Álvarez-Sánchez, J., de la Paz López, F., Toledo Moreo, J., Adeli, H. (eds) Understanding the Brain Function and Emotions. IWINAC 2019. Lecture Notes in Computer Science(), vol 11486. Springer, Cham. https://doi.org/10.1007/978-3-030-19591-5_15

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  • DOI: https://doi.org/10.1007/978-3-030-19591-5_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-19590-8

  • Online ISBN: 978-3-030-19591-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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