Advertisement

The Effect of tDCS on EEG-Based Functional Connectivity in Gait Motor Imagery

  • J. A. Gaxiola-TiradoEmail author
  • M. Rodríguez-Ugarte
  • E. Iáñez
  • M. Ortiz
  • D. Gutiérrez
  • J. M. Azorín
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11486)

Abstract

Transcranial direct current stimulation (tDCS) is a non-invasive technique for brain stimulation capable of modulating brain excitability. Although beneficial effects of tDCS have been shown, the underlying brain mechanisms have not been described. In the present study, we aim to investigate the effects of tDCS on EEG-based functional connectivity, through a partial directed coherence (PDC) analysis, which is a frequency-domain metric that provides information about directionality in the interaction between signals recorded at different channels. The tDCS montage used in our study, was focused on the lower limbs and it was composed of two anodes and one cathode. A single-blind study was carried out, where eight healthy subjects were randomly separated into two groups: sham and active tDCS. Results showed that, for the active tDCS group, the central EEG electrodes Cz, C3 and C4 turned out to be highly connected within alpha and beta frequency bands. On the contrary, the sham group presented a tendency to be more random at its functional connections.

Keywords

PDC Functional connectivity Motor imagery BCI EEG Gait tDCS 

Notes

Acknowledgments

This research has been carried out in the framework of the project Associate - Decoding and stimulation of motor and sensory brain activity to support long term potentiation through Hebbian and paired associative stimulation during rehabilitation of gait (DPI2014-58431-C4-2-R), funded by the Spanish Ministry of Economy and Competitiveness and by the European Union through the European Regional Development Fund (ERDF) “A way to build Europe”. Also, the Mexican Council of Science and Technology (CONACyT) provided J. A. Gaxiola-Tirado his scholarship, under Grant 220145.

References

  1. 1.
    Gandiga, P.C., Hummel, F.C., Cohen, L.G.: Transcranial DC stimulation (tDCS): a tool for double-blind sham-controlled clinical studies in brain stimulation. Clin. Neurophysiol. 117(4), 845–850 (2006)CrossRefGoogle Scholar
  2. 2.
    Brunoni, A.R., et al.: Clinical research with transcranial direct current stimulation (tDCS): challenges and future directions. Brain Stimul. 5(3), 175–195 (2012)CrossRefGoogle Scholar
  3. 3.
    Nitsche, M.A., Paulus, W.: Excitability changes induced in the human motor cortex by weak transcranial direct current stimulation. J. Physiol. 527(3), 633–639 (2000)CrossRefGoogle Scholar
  4. 4.
    Angulo-Sherman, I.N., Rodríguez-Ugarte, M., Sciacca, N., Iáñez, E., Azorín, J.M.: Effect of tDCS stimulation of motor cortex and cerebellum on EEG classification of motor imagery and sensorimotor band power. J. Neuroeng. Rehabil. 14(1), 31 (2017)CrossRefGoogle Scholar
  5. 5.
    Matsumoto, J., Fujiwara, T., Takahashi, O., Liu, M., Kimura, A., Ushiba, J.: Modulation of mu rhythm desynchronization during motor imagery by transcranial direct current stimulation. J. Neuroeng. Rehabil. 7(1), 27 (2010)CrossRefGoogle Scholar
  6. 6.
    Reis, J., Fritsch, B.: Modulation of motor performance and motor learning by transcranial direct current stimulation. Curr. Opin. Neurol. 24(6), 590–596 (2011)CrossRefGoogle Scholar
  7. 7.
    Lee, S.J., Chun, M.H.: Combination transcranial direct current stimulation and virtual reality therapy for upper extremity training in patients with subacute stroke. Arch. Phys. Med. Rehabil. 95(3), 431–438 (2014)CrossRefGoogle Scholar
  8. 8.
    Butler, A.J., Shuster, M., O’hara, E., Hurley, K., Middlebrooks, D., Guilkey, K.: A meta-analysis of the efficacy of anodal transcranial direct current stimulation for upper limb motor recovery in stroke survivors. JJ. Hand Ther. 26(2), 162–171 (2013)CrossRefGoogle Scholar
  9. 9.
    Kim, D.Y., et al.: Effect of transcranial direct current stimulation on motor recovery in patients with subacute stroke. Am. J. Phys. Med. Rehabil. 89(11), 879–886 (2010)CrossRefGoogle Scholar
  10. 10.
    Foerster, Á., Dutta, A., Kuo, M.F., Paulus, W., Nitsche, M.A.: Effects of anodal transcranial direct current stimulation over lower limb primary motor cortex on motor learning in healthy individuals. Eur. J. Neurosci. 47(7), 779–789 (2018)CrossRefGoogle Scholar
  11. 11.
    Fernandez, L., et al.: Cathodal transcranial direct current stimulation (tDCS) to the right cerebellar hemisphere affects motor adaptation during gait. Cerebellum 16(1), 168–177 (2017)CrossRefGoogle Scholar
  12. 12.
    Rodriguez-Ugarte, M., Iáñez, E., Ortiz-Garcia, M., Azorín, J.M.: Effects of tDCS on real-time BCI detection of pedaling motor imagery. Sensors 18(4), 1136 (2018)CrossRefGoogle Scholar
  13. 13.
    Bakker, M., De Lange, F., Stevens, J., Toni, I., Bloem, B.: Motor imagery of gait: a quantitative approach. Exp. Brain Res. 179(3), 497–504 (2007)CrossRefGoogle Scholar
  14. 14.
    Parsons, L.M., et al.: Use of implicit motor imagery for visual shape discrimination as revealed by PET. Nature 375(6526), 54 (1995)CrossRefGoogle Scholar
  15. 15.
    Hamedi, M., Salleh, S.H., Noor, A.M.: Electroencephalographic motor imagery brain connectivity analysis for BCI: a review. Neural Comput. 28(6), 999–1041 (2016)MathSciNetCrossRefGoogle Scholar
  16. 16.
    Baccalá, L.A., Sameshima, K.: Partial directed coherence: a new concept in neural structure determination. Biol. Cybern. 84(6), 463–474 (2001)CrossRefGoogle Scholar
  17. 17.
    Neumaier, A., Schneider, T.: Estimation of parameters and eigenmodes of multivariate autoregressive models. ACM Trans. Math. Softw. (TOMS) 27(1), 27–57 (2001)CrossRefGoogle Scholar
  18. 18.
    Delorme, A., Makeig, S.: EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J. Neurosci. Methods 134(1), 9–21 (2004)CrossRefGoogle Scholar
  19. 19.
    Gaxiola-Tirado, J.A., Salazar-Varas, R., Gutiérrez, D.: Using the partial directed coherence to assess functional connectivity in electroencephalography data for brain-computer interfaces. IEEE Trans. Cogn. Dev. Syst. 10(3), 776–783 (2018)CrossRefGoogle Scholar
  20. 20.
    Schelter, B., et al.: Testing for directed influences among neural signals using partial directed coherence. J. Neurosci. Methods 152(1–2), 210–219 (2006)CrossRefGoogle Scholar
  21. 21.
    Akaike, H.: A new look at the statistical model identification. IEEE Trans. Autom. Control. 19(6), 716–723 (1974)MathSciNetCrossRefGoogle Scholar
  22. 22.
    van Dun, K., Bodranghien, F.C., Mariën, P., Manto, M.U.: tDCS of the cerebellum: where do we stand in 2016? Technical issues and critical review of the literature. Front. Hum. Neurosci. 10, 199 (2016)Google Scholar
  23. 23.
    Galea, J.M., Jayaram, G., Ajagbe, L., Celnik, P.: Modulation of cerebellar excitability by polarity-specific noninvasive direct current stimulation. J. Neurosci. 29(28), 9115–9122 (2009)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.CINVESTAV, Monterrey’s UnitApodacaMexico
  2. 2.Brain-Machine Interface Systems LabSystems Engineering and Automation Department at Miguel Hernández University of ElcheElche (Alicante)Spain

Personalised recommendations