Applied Psychophysiology and Biofeedback

, Volume 43, Issue 1, pp 37–47 | Cite as

No Effects of Successful Bidirectional SMR Feedback Training on Objective and Subjective Sleep in Healthy Subjects

  • Olaf Binsch
  • Ellen S. Wilschut
  • Martijn Arns
  • Charelle Bottenheft
  • Pierre J. L. Valk
  • Eric H. G. J. M. Vermetten
Article

Abstract

There is a growing interest in the application of psychophysiological signals in more applied settings. Unidirectional sensory motor rhythm-training (SMR) has demonstrated consistent effects on sleep. In this study the main aim was to analyze to what extent participants could gain voluntary control over sleep-related parameters and secondarily to assess possible influences of this training on sleep metrics. Bidirectional training of SMR as well as heart rate variability (HRV) was used to assess the feasibility of training these parameters as possible brain computer interfaces (BCI) signals, and assess effects normally associated with unidirectional SMR training such as the influence on objective and subjective sleep parameters. Participants (n = 26) received between 11 and 21 training sessions during 7 weeks in which they received feedback on their personalized threshold for either SMR or HRV activity, for both up- and down regulation. During a pre- and post-test a sleep log was kept and participants used a wrist actigraph. Participants were asked to take an afternoon nap on the first day at the testing facility. During napping, sleep spindles were assessed as well as self-reported sleep measures of the nap. Although the training demonstrated successful learning to increase and decrease SMR and HRV activity, no effects were found of bidirectional training on sleep spindles, actigraphy, sleep diaries, and self-reported sleep quality. As such it is concluded that bidirectional SMR and HRV training can be safely used as a BCI and participants were able to improve their control over physiological signals with bidirectional training, whereas the application of bidirectional SMR and HRV training did not lead to significant changes of sleep quality in this healthy population.

Keywords

Sleep Military BCI Biofeedback Neurofeedback Training Heart rate variability 

Notes

Compliance with Ethical Standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical Approval

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

Informed Consent

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

References

  1. Ancoli, S., & Kamiya, J. (1978). Methodological issues in alpha biofeedback training. Biofeedback and Self-Regulation, 3, 155–183.CrossRefGoogle Scholar
  2. Ancoli-Israel, S., Cole, R., Alessi, C., Chambers, M., Moorcroft, M., & Pollak, C. P. (2003). The role of actigraphy in the study of sleep and circadian rhythms. Sleep, 26, 342–392.CrossRefPubMedGoogle Scholar
  3. Arns, M., de Ridder, S., Strehl, U., Breteler, M., & Coenen, A. (2009). Efficacy of neurofeedback treatment in ADHD: The effects on inattention, impulsivity and hyperactivity: A meta-analysis. Clinical EEG and Neuroscience, 40, 180–189.CrossRefPubMedGoogle Scholar
  4. Arns, M., Feddema, I., & Kenemans, J. L. (2014). Differential effects of theta/beta and SMR neurofeedback in ADHD on sleep onset latency. Frontiers in Human Neuroscience, 8, 1019.CrossRefPubMedPubMedCentralGoogle Scholar
  5. Arns, M., Heinrich, H., Ros, T., Rothenberger, A., & Strehl, U. (2015). Editorial: Neurofeedback in ADHD. Frontiers in Human Neuroscience.  https://doi.org/10.3389/fnhum.2015.00602.PubMedPubMedCentralGoogle Scholar
  6. Arns, M., & Kenemans, J. L. (2013). Neurofeedback in ADHD and insomnia: Vigilance stabilization through sleep spindles and circadian networks. Neuroscience and Biobehavioral Reviews, 44, 183–194.CrossRefGoogle Scholar
  7. Bianchi, G., & Sorrentino, R. (2007). Electronic filter simulation & design. New York: McGraw-Hill Professional, pp. 17–20.Google Scholar
  8. Binsch, O., Banko, K., Veenstra, B. J., & Valk, P. J. L. (2015). Examining the relationship between mental, physical and organizational factors associated with attrition during maritime forces training. Journal of Strength & Conditioning Research, 29, 187–191.CrossRefGoogle Scholar
  9. Birbaumer, N., & Cohen, L. (2007). Brain-computer-interfaces (BCI): Communication and restoration of movement in paralysis. Journal of Physiology, 579, 621–636.CrossRefPubMedPubMedCentralGoogle Scholar
  10. Birbaumer, N., Ghanayim, N., Hinterberger, T., Iversen, I., Kotchoubey, B., Kübler, A., et al. (1999). A spelling device for the paralysed. Nature, 398, 297–298.CrossRefPubMedGoogle Scholar
  11. Buysse, D. J., Reynolds, C. F. III, Monk, T. H., Berman, S. R., & Kupfer, D. J. (1989). The Pittsburgh Sleep Quality Index: A new instrument for psychiatric practice and research. Psychiatry Research, 28, 193–213.  https://doi.org/10.1016/0165-1781(89)90047-4.CrossRefPubMedGoogle Scholar
  12. Cortoos, A., De Valck, E., Arns, M., Breteler, M. H., & Cluydts, R. (2010). An exploratory study on the effects of tele-neurofeedback and tele-biofeedback on objective and subjective sleep in patients with primary insomnia. Applied Psychophysiology and Biofeedback, 35, 125–134.CrossRefPubMedGoogle Scholar
  13. Del Pozo, J. M., Gevirtz, R. N., Scher, B., & Guarneria, E. (2004). Biofeedback treatment increases heart rate variability in patients with known coronary artery disease. American Heart Journal, 147, G1-G6.Google Scholar
  14. Egner, T., & Gruzelier, J. H. (2001). Learned self-regulation of EEG frequency components affects attention and event-related brain potentials in humans. NeuroReport, 12, 4155–4159.  https://doi.org/10.1097/00001756-200112210-00058.CrossRefPubMedGoogle Scholar
  15. Gruzelier, J. H. (2014). EEG-neurofeedback for optimising performance. In: A review of cognitive and affective outcome in healthy participants. Neuroscience and Biobehavioral Reviews, 44, 124–141.CrossRefPubMedGoogle Scholar
  16. Gruzelier, J. H., Egner, T., & Vernon, D. (2006). Validating the efficacy of neurofeedback for optimising performance. Progress in Brain Research, 159, 421–431.CrossRefPubMedGoogle Scholar
  17. Hammond, D. C. (2007). Neurofeedback for the enhancement of athletic performance and physical balance. The Journal of the American Board of Sport Psychology, 1, 1–9.Google Scholar
  18. Hansen, A. L., Johnsen, B. H., & Thayer, J. F. (2009). Relationship between heart rate variability and cognitive function during threat of shock. Anxiety, Stress, & Coping, 22, 77–89.  https://doi.org/10.1080/10615800802272251.CrossRefGoogle Scholar
  19. Hassett, A. L., Radvanski, D. C., Vaschillo, E. G., Vaschillo, B., Sigal, L. H., & Karavidas, M. K. (2007). A pilot study of heart rate variability (HRV) biofeedback in patients with fibromyalgia. Applied Psychophysiology and Biofeedback, 32, 1–10.  https://doi.org/10.1007/s10484-006-9028-0.CrossRefPubMedGoogle Scholar
  20. Hoddes, E., Zarcone, V., Smythe, H., Philips, R., & Dement, W. C. (1973). Quantification of sleepiness: A new approach. Psychophysiology, 10, 431–436.  https://doi.org/10.1111/j.1469-8986.1973.tb00801.x.CrossRefPubMedGoogle Scholar
  21. Hoedlmoser, K., Pecherstorfer, T., Gruber, G., Anderer, P., Doppelmayr, M., Klimesch, W., & Schabus, M. (2008). Instrumental conditioning of human sensorimotor rhythm (12–15 hz) and its impact on sleep as well as declarative learning. Sleep, 31, 1401–1408.PubMedPubMedCentralGoogle Scholar
  22. Kerkhof, G. A., Brouwer, A., Rijsman, R. M., Schimsheimer, R. J., & van Kasteel, V. (2013). Holland sleep disorders questionnaire: A new sleep disorders questionnaire based on the international classification of sleep disorders-2. Journal of Sleep Research, 22, 104–107.  https://doi.org/10.1111/j.1365-2869.2012.01041.x.CrossRefPubMedGoogle Scholar
  23. Kinnear, P. R., & Gray, C. D. (2000). SPSS for Windows made simple. Hove: Psychology Press.Google Scholar
  24. Kleinnijenhuis, M., Arns, M. W., Spronk, D. B., Breteler, M. H. M., & Duysens, J. E. J. (2008). Comparison of discrete-trial based SMR and SCP training and the interrelationship between SCP and SMR networks: Implications for brain-computer interfaces and neurofeedback. Journal of Neurotherapy, 11, 19–35.CrossRefGoogle Scholar
  25. Kober, S. E., Witte, M., Ninaus, M., Neuper, C., & Wood, G. (2013). Learning to modulate one’s own brain activity: The effect of spontaneous mental strategies. Frontiers in Human Neuroscience, 7, 695. doi: https://doi.org/10.3389/fnhum.2013.00695.CrossRefPubMedPubMedCentralGoogle Scholar
  26. Lehrer, P. M., Vaschillo, E., & Vaschillo, B. (2000). Resonant frequency biofeedback training to increase cardiac variability: Rationale and manual for training. Applied Psychophysiology and Biofeedback, 25, 177–191.  https://doi.org/10.1023/A:1009554825745.CrossRefPubMedGoogle Scholar
  27. Lehrer, P. M., Vaschillo, E., Vaschillo, B., Lu, S. E., Eckberg, D. L., Edelberg, R., Shih, W. J., Lin, Y., Kuusela, T. A., Tahvanainen, K. U., & Hamer, R. M. (2003). Heart rate variability biofeedback increases baroreflex gain and peak expiratory flow. Psychosomatic Medicine, 65, 796–805.CrossRefPubMedGoogle Scholar
  28. Lofthouse, N., Arnold, L. E., Hersch, S., Hurt, E., & DeBeus, R. (2012). A review of neu-rofeedback treatment for pediatric ADHD. Journal of Attention Disorders, 16, 351–372.CrossRefPubMedGoogle Scholar
  29. Meijman, T. F., Thunnissen, M. J., & De Vries-Griever, A. G. H. (1990). The after-effects of a prolonged period of day-sleep on subjective sleep quality. Work and Stress, 4, 65–70.CrossRefGoogle Scholar
  30. Monastra, V. J., Lynn, S., Linden, M., Lubar, J. F., Gruzelier, J., & LaVaque, T. J. (2005). Electroencephalograpic biofeedback in the treatment of attention-deficit/hyperactivity disorder. Applied Psychophysiology & Biofeedback, 30, 95–111.CrossRefGoogle Scholar
  31. Morin, C. M., LeBlance, M., Daley, M., Gregoire, J. P., & Merette, C. (2006). Epidemiology of insomnia: Prevalence, self-help treatments, consultations, and determinants of help-seeking behaviors. Sleep Medicine, 7, 123–130.  https://doi.org/10.1016/j.sleep.2005.08.008.CrossRefPubMedGoogle Scholar
  32. Mulder-Hajonides van der Meulen W. R. E. H., Wijnberg, J. R., Hollanders, J. J., DeDiana, I., & Hoofdakker, R. (1980). Measurement of subjective sleep quality. Fifth European Congress on Sleep Research, Amsterdam.Google Scholar
  33. Peterson, A. L., Goodie, M. J. L., Satterfield, W. A., & Brim, W. L. (2008). Sleep disturbance during military deployment. Military Medicine, 173, 230–235.CrossRefPubMedGoogle Scholar
  34. Piantoni, G., Poil, S.-S., Linkenkaer-Hansen, K., Verweij, I. M., Ramautar, J. R., Van Someren, E. J. W., & Van Der Werf, Y. D. (2013). Individual differences in white matter diffusion affect sleep oscillations. Journal of Neuroscience, 33, 227–233.CrossRefPubMedGoogle Scholar
  35. Royer, A.,S., Doud, A.,J., Rose, M.,L., & He, B. (2010). EEG control of a virtual helicopter in 3-dimensional space using intelligent control strategies. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 18, 581–589.CrossRefPubMedPubMedCentralGoogle Scholar
  36. Ruehland, W. R., O’Donoghue, F. J., Pierce, R. J., Thornton, A. T., Singh, P., Copland, J. M., Stevens, B., & Rochford, P. D. (2011). The 2007 AASM recommendations for EEG electrode placement in polysomnography: Impact on sleep and cortical arousal scoring. Sleep, 1, 34, 73–81.CrossRefGoogle Scholar
  37. Schabus, M., Heib, D. P. J., Lechinger, J., Griessenberger, H., Klimesch, W., Pawlizki, A., Kunz, A. B., Sterman, B. M., & Hoedlmoser, K. (2014). Enhancing sleep quality and memory in insomnia using instrumental sensorimotor rhythm conditioning. Biological Psychology, 95, 126–134.CrossRefPubMedGoogle Scholar
  38. Spronk, D., Kleinnijenhuis, M., Luijtelaar, G., & Arns, M. (2010). Discrete-trial SCP and GSR training and the interrelationship between central and peripheral arousal. Journal of Neurotherapy, 14, 217–228.CrossRefGoogle Scholar
  39. Sterman, M. B. (2000). Basic concepts and clinical findings in the treatment of seizure disorders with EEG operant conditioning. Clinical EEG (Electroencephalography), 31, 45–55.CrossRefGoogle Scholar
  40. Sterman, M. B., & Egner, T. (2006). Foundation and practice of neurofeedback for the treatment of epilepsy. Applied Psychophysiology and Biofeedback, 31, 21–35.CrossRefPubMedGoogle Scholar
  41. Sterman, M. B., Wyrwicka, W., & Roth, S. R. (1969). Electrophysiological correlates andneural substrates of alimentary behaviour in the cat. Annals of the New York Academy of Science, 157, 723–739.CrossRefGoogle Scholar
  42. Tan, G., Thornby, J., Hammond, D. C., Strehl, U., Canady, B., Arnemann, K., & Kaiser, D. A. (2009). Meta-analysis of EEG biofeedback in treating epilepsy. Clinical EEG and Neuroscience, 40, 173–173.CrossRefPubMedGoogle Scholar
  43. Vernon, D., Dempster, T., Bazanova, O., Rutterford, N., Pasqualini, M., & Andersen, S. (2009). Alpha neurofeedback training for performance enhancement: Reviewing the methodology. Journal of Neurotherapy, 13, 214–227.CrossRefGoogle Scholar
  44. Vernon, D., Egner, T., Cooper, N., Compton, T., Neilands, C., Sheri, A., & Gruzelier, J. (2003). The effect of training distinct neurofeedback protocols onaspects of cognitive performance. International Journal of Psychophysiology, 47, 75–86.CrossRefPubMedGoogle Scholar
  45. Wolpaw, J. R., & McFarland, D. J. (2004). Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans. Proceedings of the National Academy of Sciences of the U. S. A. 101, 17849–17854.CrossRefGoogle Scholar
  46. Yuan, H., & He, B. (2014). Brain-computer interfaces using sensorimotor rhythms: Current state and future perspectives. IEEE Transactions on Biomedical Engineering, 61, 1425–1435.CrossRefPubMedPubMedCentralGoogle Scholar
  47. Zucker, T. L., Samuelson, K. W., Muench, F., Greenberg, M. A., & Gevirtz, R. N. (2009). The effects of respiratory sinus arrhythmia biofeedback on heart rate variability and posttraumatic stress disorder symptoms: A pilot study. Applied Psychophysiology & Biofeedback, 34, 135–143.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  • Olaf Binsch
    • 1
  • Ellen S. Wilschut
    • 1
  • Martijn Arns
    • 2
    • 5
  • Charelle Bottenheft
    • 1
  • Pierre J. L. Valk
    • 1
  • Eric H. G. J. M. Vermetten
    • 3
    • 4
  1. 1.Netherlands Organisation for Applied Scientific Research (TNO)SoesterbergThe Netherlands
  2. 2.Research Institute BrainclinicsNijmegenThe Netherlands
  3. 3.Ministry of DefenseCentral Military HospitalUtrechtThe Netherlands
  4. 4.University of LeidenLeidenThe Netherlands
  5. 5.Department of Experimental PsychologyUtrecht UniversityUtrechtThe Netherlands

Personalised recommendations