Efficacy of Live Z-Score Neurofeedback Training for Chronic Insomnia: A Single-Case Study

Authors

  • Ruben Perez-Elvira NEPSA Rehabilitacion Neurologica
  • José A. Carrobles Universidad Autónoma de Madrid
  • Diego J López Bote NEPSA Rehabilitación Neurológica
  • Javier Oltra-Cucarella University of Alicante

DOI:

https://doi.org/10.15540/nr.6.2.93

Keywords:

insomnia, neurofeedback, z-score, QEEG, z-score neurofeedback

Abstract

Objective/Background: Insomnia is the most common sleep disorder in the general population.  Pharmacological treatments have shown efficacy in the short term, yet the symptoms return once the treatment has been withdrawn.  In the search for treatment options with long-lasting effects, neurofeedback (NF) has arisen as a therapeutic option.  Neurofeedback is the application of operant conditioning to brain activity.  The aim of this work is to show the effectiveness of Live Z-Score NF training (LZT), a paradigm within the field of NF, in a case of insomnia.  Participants: A 32-year-old male with chronic insomnia since his adolescence.  Methods: Thirty 35-min sessions of qEEG-guided LZT using patient’s highly preferred feedback.  The main outcomes of this study were the patient’s qEEG metrics and a visual analog scale of sleep quality throughout the intervention.  Results: qEEG-guided LZT showed an improvement of 90.63% of the patient’s qEEG metrics and an 82.55% relief of the clinical symptoms after 30 NF sessions.  Conclusions: Although more research is needed to establish that NF based on Live Z-Score is effective for insomnia, our results suggest that NF might be a therapeutic alternative for the treatment of insomnia.

 

Author Biography

Ruben Perez-Elvira, NEPSA Rehabilitacion Neurologica

Clinical Chief

NEPSA Rehabilitación Neurológica

References

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. https://doi.org/10.3389/fnhum.2014.01019

Arns, M., & Kenemans, J. L. (2014). Neurofeedback in ADHD and insomnia: Vigilance stabilization through sleep spindles and circadian networks. Neuroscience & Biobehavioral Reviews, 44, 183–194. https://doi.org/10.1016/j.neubiorev.2012.10.006

Arroyo, S., Lesser, R. P., Gordon, B., Uematsu, S., Jackson, D., & Webber, R. (1993). Functional significance of the mu rhythm of human cortex: an electrophysiologic study with subdural electrodes. Electroencephalography and Clinical Neurophysiology, 87(3), 76–87. https://doi.org/10.1016/0013-4694(93)90114-B

BrainAvatar (Version 4.6.4) [Computer software]. (n.d.). Bedford, OH: BrainMaster Technologies, Inc.

BrainMaster Discovery 20 [Apparatus]. Bedford, OH: BrainMaster Technologies, Inc.

Carrobles, J. A. (2016). Bio/neurofeedback. Clínica y Salud, 27(3), 125–131. https://doi.org/10.1016/j.clysa.2016.09.003

Chapin, T., & Russell-Chapin, L. A. (2014). Neurotherapy and neurofeedback: Brain-based treatment for psychological and behavioral problems. New York NY: Routledge/Taylor & Francis Group.

Collura, T., Guan, J., Tarrant, J., Bailey, J., & Starr, F. (2010). EEG biofeedback case studies using live Z-score training and a normative database. Journal of Neurotherapy, 14(1), 22–46. https://doi.org/10.1080/10874200903543963

Cortoos, A., De Valck, E., Arns, M., Breteler, M. H. M., & 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(2), 125–134. https://doi.org/10.1007/s10484-009-9116-z

Daley, M., Morin, C. M., LeBlanc, M., Grégoire, J.-P., & Savard, J. (2009). The economic burden of insomnia: direct and indirect costs for individuals with insomnia syndrome, insomnia symptoms, and good sleepers. Sleep, 32(1), 55–64.

Demos, J. N. (2005). Getting started with neurofeedback (1st ed). New York: W.W. Norton & Company.

Electro-Cap system [Apparatus]. Eaton, OH: Electro-Cap International, Inc.

Fisher, W., Piazza, C. C., Bowman, L. G., Hagopian, L. P., Owens, J. C., & Slevin, I. (1992). A comparison of two approaches for identifying reinforcers for persons with severe and profound disabilities. Journal of Applied Behavior Analysis, 25(2), 491–498. https://doi.org/10.1901/jaba.1992.25-491

Gracefire, P. (2016). Introduction to the concepts and clinical applications of multivariate live Z-Score training, PZOK and sLORETA feedback. In T. F. Collura & J. A. Frederick (Eds.), Handbook of clinical QEEG and neuropathy (pp. 326–383). New York, NY: Routledge.

Guan, J. (2016). The efficacy of Z-score neurofeedback training. In T. F. Collura & J. A. Frederick (Eds.), Handbook of clinical QEEG and neuropathy (pp. 312–325). New York, NY: Routledge.

Halson, S. L. (2017). Neurofeedback as a Potential Nonpharmacological Treatment for Insomnia. Biofeedback, 45(1), 19–20. https://doi.org/10.5298/1081-5937-45.1.08

Hammer, B. U., Colbert, A. P., Brown, K. A., & Ilioi, E. C. (2011). Neurofeedback for insomnia: A pilot study of Z-Score SMR and individualized protocols. Applied Psychophysiology and Biofeedback, 36(4), 251–264. https://doi.org/10.1007/s10484-011-9165-y

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(10), 1401–1408. http://doi.org/10.5665/sleep/31.10.1401

Krigbaum, G., & Wigton, N. L. (2015). A methodology of analysis for monitoring treatment progression with 19-channel Z-score neurofeedback (19ZNF) in a single-subject design. Applied Psychophysiology and Biofeedback, 40(3), 139–149. https://doi.org/10.1007/s10484-015-9274-0

Lubar, J. F. (2015). Optimal procedures in Z-score neurofeedback. In R. W. Thatcher & D. S. Foster (Eds.), Z score neurofeedback: Clinical applications (pp. 41–58). San Diego, CA: Academic Press. https://doi.org/10.1016/B978-0-12-801291-8.00003-0

Mangum, A., Fredrick, L., Pabico, R., & Roane, H. (2012). The role of context in the evaluation of reinforcer efficacy: Implications for the preference assessment outcomes. Research in Autism Spectrum Disorders, 6(1), 158–167. https://doi.org/10.1016/j.rasd.2011.04.001

Martínez Hernández, J., Lozano Olivares, J., & Álamo González, C. (2016). Insomnio. Madrid, Spain: FFOMC IM&C.

NeuroGuide (Version 2.9.1) [Computer software]. (n.d.). Largo, FL: Applied Neuroscience, Inc.

NIH. (2005). NIH State-of-the-Science Conference Statement on manifestations and management of chronic insomnia in adults. NIH Consensus and State-of-the-Science Statements, 22(2), 1–30.

Ohayon, M. M., & Sagales, T. (2010). Prevalence of insomnia and sleep characteristics in the general population of Spain. Sleep Medicine, 11(10), 1010–1018. https://doi.org/10.1016/j.sleep.2010.02.018

Pérez-Elvira, R., López Bote, D. J., Guarino, S., Agudo Juan, M., De León, R. J., Feiner, T., & Perez, B. (2018). Neurometric results of a case series using live Z-scores neurofeedback. International Journal of Psychophysiology, 131, S139–S140. https://doi.org/10.1016/j.ijpsycho.2018.07.375

Piazza, C. C., Fisher, W. W., Hagopian, L. P., Bowman, L. G., & Toole, L. (1996). Using a choice assessment to predict reinforcer effectiveness. Journal of Applied Behavior Analysis, 29(1), 1–9. https://doi.org/10.1901/jaba.1996.29-1

Schabus, M., Griessenberger, H., Gnjezda, M.-T., Heib, D. P. J., Wislowska, M., & Hoedlmoser, K. (2017). Better than sham? A double-blind placebo-controlled neurofeedback study in primary insomnia. Brain, 140(4), 1041–1052. https://doi.org/10.1093/brain/awx011

Schabus, M., Heib, D. P. J., Lechinger, J., Griessenberger, H., Klimesch, W., Pawlizki, A., … Hoedlmoser, K. (2014). Enhancing sleep quality and memory in insomnia using instrumental sensorimotor rhythm conditioning. Biological Psychology, 95, 126–134. https://doi.org/10.1016/j.biopsycho.2013.02.020

Skinner, B. F. (1938). The behavior of organisms: An experimental analysis. New York, NY: Appleton-Century-Crofts, Inc.

Soutar, R. G., & Longo, R. E. (2011). Doing neurofeedback: An introduction (pp. 121–140). ISNR Research Foundation.

Thatcher, R. W., & Lubar, J. F. (Eds.). (2014). Z score neurofeedback: Clinical applications. San Diego, CA: Academic Press.

Walker, J. E. (2016). qEEG-guided neurofeedback to normalize brain function in various disorders. In T. F. Collura & J. A. Frederick (Eds.), Handbook of clinical QEEG and neuropathy (pp. 149–157). New York, NY: Routledge.

Wigton, N. L., & Krigbaum, G. (2015). Attention, executive function, behavior, and electrocortical function, significantly improved with 19-channel z-score neurofeedback in a clinical setting: A pilot study. Journal of Attention Disorders, 23(4), 398–408. https://doi.org/10.1177/1087054715577135

Zisapel, N., & Nir, T. (2003). Determination of the minimal clinically significant difference on a patient visual analog sleep quality scale. Journal of Sleep Research, 12(4), 291–298. https://doi.org/10.1046/j.0962-1105.2003.00365.x

Downloads

Published

2019-06-26

Issue

Section

Research Papers