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The impact of goal-oriented task design on neurofeedback learning for brain–computer interface control

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Abstract

Neurofeedback training teaches individuals to modulate brain activity by providing real-time feedback and can be used for brain–computer interface control. The present study aimed to optimize training by maximizing engagement through goal-oriented task design. Participants were shown either a visual display or a robot, where each was manipulated using motor imagery (MI)-related electroencephalography signals. Those with the robot were instructed to quickly navigate grid spaces, as the potential for goal-oriented design to strengthen learning was central to our investigation. Both groups were hypothesized to show increased magnitude of these signals across 10 sessions, with the greatest gains being seen in those navigating the robot due to increased engagement. Participants demonstrated the predicted increase in magnitude, with no differentiation between hemispheres. Participants navigating the robot showed stronger left-hand MI increases than those with the computer display. This is likely due to success being reliant on maintaining strong MI-related signals. While older participants showed stronger signals in early sessions, this trend later reversed, suggesting greater natural proficiency but reduced flexibility. These results demonstrate capacity for modulating neurofeedback using MI over a series of training sessions, using tasks of varied design. Importantly, the more goal-oriented robot control task resulted in greater improvements.

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References

  1. Akaike H (1974) A new look at the statistical model identification. IEEE Trans Automat Contr 19:716–723. doi:10.1109/TAC.1974.1100705

    Article  Google Scholar 

  2. Bardouille T, Picton TW, Ross B (2010) Attention modulates beta oscillations during prolonged tactile stimulation. Eur J Neurosci 31:761–769. doi:10.1111/j.1460-9568.2010.07094.x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Boe S, Gionfriddo A, Kraeutner S et al (2014) Laterality of brain activity during motor imagery is modulated by the provision of source level neurofeedback. Neuroimage 101:159–167. doi:10.1016/j.neuroimage.2014.06.066

    Article  PubMed  Google Scholar 

  4. Braun S, Kleynen M, Schols J et al (2008) Using mental practice in stroke rehabilitation: a framework. Clin Rehabil 22:579–591. doi:10.1177/0269215508090066

    Article  PubMed  Google Scholar 

  5. Burianová H, Marstaller L, Sowman P et al (2013) Multimodal functional imaging of motor imagery using a novel paradigm. Neuroimage 71:50–58. doi:10.1016/j.neuroimage.2013.01.001

    Article  PubMed  Google Scholar 

  6. Deilami M, Jahandideh A, Kazemnejad Y et al (2016) The effect of neurofeedback therapy on reducing symptoms associated with attention deficit hyperactivity disorder: a case series study. Basic Clin Neurosci J. doi:10.15412/J.BCN.03070211

    Google Scholar 

  7. Donati ARC, Shokur S, Morya E et al (2016) Long-term training with a brain-machine interface-based gait protocol induces partial neurological recovery in paraplegic patients. Sci Rep 6:30383. doi:10.1038/srep30383

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Farah MJ (1989) The neural basis of mental imagery. Trends Neurosci 12:395–399. doi:10.1016/0166-2236(89)90079-9

    Article  CAS  PubMed  Google Scholar 

  9. Gomez-Pilar J, Corralejo R, Nicolas-Alonso LF et al (2016) Neurofeedback training with a motor imagery-based BCI: neurocognitive improvements and EEG changes in the elderly. Med Biol Eng Comput. doi:10.1007/s11517-016-1454-4

    PubMed  Google Scholar 

  10. Hamilton JP, Glover GH, Bagarinao E et al (2016) Effects of salience-network-node neurofeedback training on affective biases in major depressive disorder. Psychiatry Res 249:91–96. doi:10.1016/j.pscychresns.2016.01.016

    Article  PubMed  PubMed Central  Google Scholar 

  11. Ietswaart M, Johnston M, Dijkerman HC et al (2011) Mental practice with motor imagery in stroke recovery: randomized controlled trial of efficacy. Brain 134:1373–1386. doi:10.1093/brain/awr077

    Article  PubMed  PubMed Central  Google Scholar 

  12. Jeannerod M, Frak V (1999) Mental imaging of motor activity in humans. Curr Opin Neurobiol 9:735–739. doi:10.1016/S0959-4388(99)00038-0

    Article  CAS  PubMed  Google Scholar 

  13. Kober SE, Wood G, Kampl C et al (2014) Electrophysiological correlates of mental navigation in blind and sighted people. Behav Brain Res 273:106–115. doi:10.1016/j.bbr.2014.07.022

    Article  PubMed  Google Scholar 

  14. Kraeutner S, Gionfriddo A, Bardouille T, Boe S (2014) Motor imagery-based brain activity parallels that of motor execution: evidence from magnetic source imaging of cortical oscillations. Brain Res 1588:81–91. doi:10.1016/j.brainres.2014.09.001

    Article  CAS  PubMed  Google Scholar 

  15. Kraeutner S, Gionfriddo A, Bardouille T, Boe S (2014) Motor imagery-based brain activity parallels that of motor execution: evidence from magnetic source imaging of cortical oscillations. Brain Res 1588:81–91. doi:10.1016/j.brainres.2014.09.001

    Article  CAS  PubMed  Google Scholar 

  16. Ma L, Wang B, Narayana S et al (2010) Changes in regional activity are accompanied with changes in inter-regional connectivity during 4 weeks motor learning. Brain Res 1318:64–76. doi:10.1016/j.brainres.2009.12.073

    Article  CAS  PubMed  Google Scholar 

  17. Malouin F, Richards CL, Durand A, Doyon J (2009) Added value of mental practice combined with a small amount of physical practice on the relearning of rising and sitting post-stroke: a pilot study. J Neurol Phys Ther 33:195–202. doi:10.1097/NPT.0b013e3181c2112b

    Article  PubMed  Google Scholar 

  18. Masterpasqua F, Healey KN (2003) Neurofeedback in psychological practice. Prof Psychol Res Pract 34:652–656. doi:10.1037/0735-7028.34.6.652

    Article  Google Scholar 

  19. Nunez P, Srinivasan R (1981) Electric fields of the brain: the neurophysics of EEG. Oxford University Press, Oxford

    Google Scholar 

  20. Oldfield RC (1971) The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia 9:97–113

    Article  CAS  PubMed  Google Scholar 

  21. Peeters F, Oehlen M, Ronner J et al (2014) Neurofeedback as a treatment for major depressive disorder—a pilot study. PLoS ONE 9:e91837. doi:10.1371/journal.pone.0091837

    Article  PubMed  PubMed Central  Google Scholar 

  22. Penhune VB, Doyon J (2005) Cerebellum and M1 interaction during early learning of timed motor sequences. Neuroimage 26:801–812. doi:10.1016/j.neuroimage.2005.02.041

    Article  CAS  PubMed  Google Scholar 

  23. Pfurtscheller G, da Silva FH (1999) Event-related {EEG}/{MEG} synchronization and desynchronization: basic principles. Clin Neurophysiol 110:1842–1857. doi:10.1016/S1388-2457(99)00141-8

    Article  CAS  PubMed  Google Scholar 

  24. Pfurtscheller G, Solis-Escalante T (2009) Could the beta rebound in the EEG be suitable to realize a “brain switch”? Clin Neurophysiol 120:24–29. doi:10.1016/j.clinph.2008.09.027

    Article  CAS  PubMed  Google Scholar 

  25. Pfurtscheller G, Neuper C, Brunner C, da Silva FL (2005) Beta rebound after different types of motor imagery in man. Neurosci Lett 378:156–159. doi:10.1016/j.neulet.2004.12.034

    Article  CAS  PubMed  Google Scholar 

  26. Picard N, Matsuzaka Y, Strick PL (2013) Extended practice of a motor skill is associated with reduced metabolic activity in M1. Nat Neurosci 16:1340–1347. doi:10.1038/nn.3477

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Poldrack RA, Sabb FW, Foerde K et al (2005) The neural correlates of motor skill automaticity. J Neurosci 25:5356–5364. doi:10.1523/JNEUROSCI.3880-04.2005

    Article  CAS  PubMed  Google Scholar 

  28. Riccio I, Iolascon G, Barillari MR et al (2010) Mental practice is effective in upper limb recovery after stroke: a randomized single-blind cross-over study. Eur J Phys Rehabil Med 46:19–25

    CAS  PubMed  Google Scholar 

  29. Schnitzler A, Salenius S, Salmelin R et al (1997) Involvement of primary motor cortex in motor imagery: a neuromagnetic study. Neuroimage 6:201–208. doi:10.1006/nimg.1997.0286

    Article  CAS  PubMed  Google Scholar 

  30. Schuster C, Butler J, Andrews B et al (2012) Comparison of embedded and added motor imagery training in patients after stroke: results of a randomised controlled pilot trial. Trials 13:11. doi:10.1186/1745-6215-13-11

    Article  PubMed  PubMed Central  Google Scholar 

  31. Sousa T, Direito B, Lima J et al (2016) Control of brain activity in hMT +/V5 at three response levels using fMRI-based neurofeedback/BCI. PLoS ONE 11:e0155961. doi:10.1371/journal.pone.0155961

    Article  PubMed  PubMed Central  Google Scholar 

  32. Toni I, Krams M, Turner R, Passingham RE (1998) The time course of changes during motor sequence learning: a whole-brain fMRI study. Neuroimage 8:50–61. doi:10.1006/nimg.1998.0349

    Article  CAS  PubMed  Google Scholar 

  33. Tremblay A, Tucker BV (2011) What can the production of four-word sequences tell us about the mental lexicon? Ment Lex 6:302–324

    Article  Google Scholar 

  34. Ungerleider L (2002) Imaging brain plasticity during motor skill learning. Neurobiol Learn Mem 78:553–564. doi:10.1006/nlme.2002.4091

    Article  PubMed  Google Scholar 

  35. Wan F, da Cruz JN, Nan W et al (2016) Alpha neurofeedback training improves SSVEP-based BCI performance. J Neural Eng 13:36019. doi:10.1088/1741-2560/13/3/036019

    Article  Google Scholar 

  36. Wiestler T, Diedrichsen J (2013) Skill learning strengthens cortical representations of motor sequences. Elife. doi:10.7554/eLife.00801

    PubMed  PubMed Central  Google Scholar 

  37. Xiong J, Ma L, Wang B et al (2009) Long-term motor training induced changes in regional cerebral blood flow in both task and resting states. Neuroimage 45:75–82. doi:10.1016/j.neuroimage.2008.11.016

    Article  PubMed  Google Scholar 

  38. Young KD, Zotev V, Phillips R et al (2014) Real-time FMRI neurofeedback training of amygdala activity in patients with major depressive disorder. PLoS ONE 9:e88785. doi:10.1371/journal.pone.0088785

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We are grateful to the following people for their assistance in this study: Jack P. Solomon, Christopher Friesen, Gloria Kamba, Jeremy Huard, and Derek Rodgers. This work was supported by the Brain Repair Centre.

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Authors and Affiliations

  1. Department of Psychology and Neuroscience, Dalhousie University, 1355 Oxford Street, P.O. Box 15000, Halifax, NS, B3H 4R2, Canada

    S. R. McWhinney, A. Tremblay, S. G. Boe & T. Bardouille

  2. Department of Linguistics, Saint Mary’s University, 923 Robie Street, Halifax, NS, B3H 3C3, Canada

    A. Tremblay

  3. NovaScape Data Analysis and Consulting, 18, Stonehaven Road, Halifax, NS, B3N 1G1, Canada

    A. Tremblay

  4. School of Physiotherapy, Dalhousie University, 5869 University Avenue, Halifax, NS, B3H 4R2, Canada

    S. G. Boe & T. Bardouille

  5. IWK Health Centre, Biomedical Translational Imaging Centre, 5850/5950 University Avenue, Halifax, NS, B3K 6R8, Canada

    T. Bardouille

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  1. S. R. McWhinney
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  2. A. Tremblay
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  3. S. G. Boe
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  4. T. Bardouille
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Correspondence to S. R. McWhinney.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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Informed consent was obtained from all individual participants included in the study.

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McWhinney, S.R., Tremblay, A., Boe, S.G. et al. The impact of goal-oriented task design on neurofeedback learning for brain–computer interface control. Med Biol Eng Comput 56, 201–210 (2018). https://doi.org/10.1007/s11517-017-1683-1

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  • DOI: https://doi.org/10.1007/s11517-017-1683-1

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