The The Effect of Infraslow Frequency Neurofeedback on Autonomic Nervous System Function in Adults with Anxiety and Related Diseases

Authors

  • Karlien Balt, Msc Physiology Department of Human Physiology, Faculty of Health Sciences, University of Pretoria
  • Preet Du Toit, PhD Department of Human Physiology, Faculty of Health Sciences, University of Pretoria
  • Mark Llewellyn Smith, LCSW, BCN, QEEGD Neurofeedback Services
  • Charl Janse van Rensburg, MSc Mathematical Statistics Biostatics Unit, Medica Research Council Pretoria

DOI:

https://doi.org/10.15540/nr.7.2.64

Keywords:

neurofeedback, infraslow frequency, electroencephalogram, blood pressure, electromyogram, autonomic function

Abstract

Peripheral body monitoring of autonomic nervous system (ANS) response has been routinely applied during infraslow fluctuation (ISF) neurofeedback training.  This study hypothesized that ISF training has a distinct physiological effect on an individual that can be revealed by measuring autonomic function with peripheral biofeedback metrics that included heart rate variability (HRV), muscle tension, skin temperature, skin conductance, heart rate, respiration rate, and blood pressure.  Methods.  Thirty adults between the ages of 18 and 55, primarily with anxiety, were randomized into two groups: 20 in the experimental group and 9 in the control group.  The experimental group completed 10 ISF neurofeedback training sessions while continuous monitoring of ANS changes was applied.  The same process was completed for a control group that received one-channel sensorimotor rhythm (SMR) neurofeedback training.  Results.  Significant changes were seen in the skin conductance (p < .0001), electromyography (p = .01), very low frequency (p = .004), low frequency of HRV (p = .05) and blood pressure (systolic change p = .049) in the experimental group.  No significant changes were seen in the control group.  Conclusion.  The study demonstrated that ISF neurofeedback training impacts the ANS as measured by peripheral biofeedback indicators.

References

Akselrod, S., Gordon, D., Ubel, F. A., Shannon, D. C., Berger, A. C., & Cohen, R. J. (1981). Power spectrum analysis of heart rate fluctuation: A quantitative probe of beat-to-beat cardiovascular control. Science, 213(4504), 220–222. https://doi.org/10.1126/science.6166045

Aladjalova, N. A. (1957). Infra-slow rhythmic oscillations of the steady potential of the cerebral cortex. Nature, 179(4567), 957–959. http://dx.doi.org/10.1038/179957a0

Alshelh, Z., Di Pietro, F., Youssef, A. M., Reeves, J. M., Macey, P. M., Vickers, E. R., … Henderson, L. A. (2016). Chronic neuropathic pain: It's about the rhythm. The Journal of Neuroscience, 36(3), 1008–1018. https://doi.org/10.1523/jneurosci.2768-15.2016

Barrett, K. E., Barman, S. M., Boitano, S., & Brooks, H. L. (2012). Ganong's review of medical physiology. New York, NY: McGraw Hill. https://www.amazon.com/Ganongs-Review-Medical-Physiology-Science/dp/0071780033

Beissner, F., Meissner, K., Bär, K.-J., & Napadow, V. (2013). The autonomic brain: An activation likelihood estimation meta-analysis for central processing of autonomic function. The Journal of Neuroscience, 33(25), 10503–10511. https://doi.org/10.1523/jneurosci.1103-13.2013

Broyd, S. J., Helps, S. K., & Sonuga-Barke, E. J. S. (2011). Attention-induced deactivations in very low frequency EEG oscillations: Differential localisation according to ADHD symptom status. PLoS ONE, 6(3), e17325. http://dx.doi.org/10.1371/journal.pone.0017325

Camp, R. M., Remus, J. L., Kalburgi, S. N., Porterfield, V. M., & Johnson, J. D. (2012). Fear conditioning can contribute to behavioral changes observed in a repeated stress model. Behavioural Brain Research, 233(2), 536–544. https://doi.org/10.1016/j.bbr.2012.05.040

Collet, C., Vernet-Maury, E., Delhomme, G., & Dittmar, A. (1997). Autonomic nervous system response patterns specificity to basic emotions. Journal of the Autonomic Nervous System, 62(1–2), 45–57. https://doi.org/10.1016/S0165-1838(96)00108-7

Collura, T. F. (2013). Technical foundations of neurofeedback. New York, NY: Routledge/Taylor & Francis Group.

Eckberg, D. L. (1997). Sympathovagal balance. Circulation, 96(9), 3224–3232. https://doi.org/10.1161/01.CIR.96.9.3224

Fink, A. M., Bronas, U. G., & Calik, M. W. (2018). Autonomic regulation during sleep and wakefulness: A review with implications for defining the pathophysiology of neurological disorders. Clinical Autonomic Research, 28(6), 509–518. https://doi.org/10.1007/s10286-018-0560-9

Goldstein, D. S., Bentho, O., Park, M.-Y., & Sharabi, Y. (2011). Low-frequency power of heart rate variability is not a measure of cardiac sympathetic tone but may be a measure of modulation of cardiac autonomic outflows by baroreflexes. Experimental Physiology, 96(12), 1255–1261. https://doi.org/10.1113/expphysiol.2010.056259

Grossman, E., Nadler, M., Sharabi, Y., Thaler, M., Shachar, A., & Shamiss, A. (2005). Antianxiety treatment in patients with excessive hypertension. American Journal of Hypertension, 18(9), 1174–1177. https://doi.org/10.1016/j.amjhyper.2005.03.728

Helfrich, R. F., Mander, B. A., Jagust, W. J., Knight, R. T., & Walker, M. P. (2018). Old brains come uncoupled in sleep: Slow wave-spindle synchrony, brain atrophy, and forgetting. Neuron, 97(1), 221–230.e4. https://doi.org/10.1016/j.neuron.2017.11.020

Hiltunen, T., Kantola, J., Abou Elseoud, A., Lepola, P., Suominen, K., Starck, T., … Palva, J. M. (2014). Infra-slow EEG fluctuations are correlated with resting-state network dynamics in fMRI. The Journal of Neuroscience, 34(2), 356–362. https://doi.org/10.1523/jneurosci.0276-13.2014

Huster, R. J., Mokom, Z. N., Enriquez-Geppert, S., & Herrmann, C. S. (2014). Brain–computer interfaces for EEG neurofeedback: Peculiarities and solutions. International Journal of Psychophysiology, 91(1), 36–45. https://doi.org/10.1016/j.ijpsycho.2013.08.011

Joshi, R. B., Duckrow, R. B., Goncharova, I. I., Gerrard, J. L., Spencer, D. D., Hirsch, L. J., … Zaveri, H. P. (2018). Seizure susceptibility and infraslow modulatory activity in the intracranial electroencephalogram. Epilepsia, 59(11), 2075–2085. https://doi.org/10.1111/epi.14559

Lecci, S., Fernandez, L. M. J., Weber, F. D., Cardis, R., Chatton, J.-Y., Born, J., & Lüthi, A. (2017). Coordinated infraslow neural and cardiac oscillations mark fragility and offline periods in mammalian sleep. Science Advances, 3(2), e1602026. https://doi.org/10.1126/sciadv.1602026

Leong, S. L., Vanneste, S., Lim, J., Smith, M., Manning, P., & De Ridder, D. (2018). A randomised, double-blind, placebo-controlled parallel trial of closed-loop infraslow brain training in food addiction. Scientific Reports, 8(1), 11659. https://doi.org/10.1038/s41598-018-30181-7

Levenson, R. W. (1992). Autonomic nervous system differences among emotions. Psychological Science, 3(1), 23–27. https://doi.org/10.1111/j.1467-9280.1992.tb00251.x

Li, K., Rüdiger, H., & Ziemssen, T. (2019). Spectral analysis of heart rate variability: Time window matters. Frontiers in Neurology, 10(545). https://doi.org/10.3389/fneur.2019.00545

Lin, H.-P., Lin, H.-Y., Lin, W.-L., & Huang, A. C.-W. (2011). Effects of stress, depression, and their interaction on heart rate, skin conductance, finger temperature, and respiratory rate: Sympathetic-parasympathetic hypothesis of stress and depression. Journal of Clinical Psychology, 67(10), 1080–1091. https://doi.org/10.1002/jclp.20833

Malik, M. (1998). Sympathovagal balance: A critical appraisal. Circulation, 98(23), 2643–2644. https://doi.org/10.1161/01.CIR.98.23.2643

Marshall, L., Mölle, M., Fehm, H. L., & Born, J. (2008). Changes in direct current (DC) potentials and infra-slow EEG oscillations at the onset of the luteinizing hormone (LH) pulse. European Journal of Neuroscience, 12(11), 3935–3943. https://doi.org/10.1046/j.1460-9568.2000.00304.x

Mathew, J., Adhia, D. B., Smith, M. L., De Ridder, D., & Mani, R. (2020). Protocol for a pilot randomized sham-controlled clinical trial evaluating the feasibility, safety, and acceptability of infraslow electroencephalography neurofeedback training on experimental and clinical pain outcomes in people with chronic painful knee osteoarthritis. NeuroRegulation, 7(1), 30–44. https://doi.org/10.15540/nr.7.1.30

McCorry, L. K. (2007). Physiology of the autonomic nervous system. American Journal of Pharmaceutical Education, 71(4), 78. https://doi.org/10.5688/aj710478

Palva, J. M., & Palva, S. (2012). Infra-slow fluctuations in electrophysiological recordings, blood-oxygenation-level-dependent signals, and psychophysical time series. NeuroImage, 62(4), 2201–2211. https://doi.org/10.1016/j.neuroimage.2012.02.060

Peper, E., Harvey, R., Lin, I.-M., Tylova, H., & Moss, D. W. (2015). Is there more to blood volume pulse than heart rate variability, respiratory sinus arrhythmia, and cardiorespiratory synchrony? Biofeedback, 35(2), 54–61. https://api.semanticscholar.org/CorpusID:15486681

Pluess, M., Conrad, A., & Wilhelm, F. H. (2009). Muscle tension in generalized anxiety disorder: A critical review of the literature. Journal of Anxiety Disorders, 23(1), 1–11. https://doi.org/10.1016/j.janxdis.2008.03.016

Prinsloo, G. E., Rauch, H. G. L., Lambert, M. I., Muench, F., Noakes, T. D., & Derman, W. E. (2011). The effect of short duration heart rate variability (HRV) biofeedback on cognitive performance during laboratory induced cognitive stress. Applied Cognitive Psychology, 25(5), 792–801. https://doi.org/10.1002/acp.1750

Rodin, E., Bornfleth, H., & Johnson, M. (2017). DC-EEG recordings of mindfulness. Clinical Neurophysiology, 128(4), 512–519. https://doi.org/10.1016/j.clinph.2016.12.031

Sainsbury, P., & Gibson, J. G. (1954). Symptoms of anxiety and tension and the accompanying physiological changes in the muscular system. Journal of Neurology, Neurosurgery, & Psychiatry, 17(3), 216–224. https://doi.org/10.1136/jnnp.17.3.216

Silverman, D. (1963). The rationale and history of the 10-20 system of the International Federation. American Journal of EEG Technology, 3(1), 17–22. https://doi.org/10.1080/00029238.1963.11080602

Smith, M. L. (2013). Infra-slow fluctuation training; On the down-low in neuromodulation. NeuroConnections, Fall, 38 & 42.

Smith, M. L., Collura, T. F., Ferrara, J., & de Vries, J. (2014). Infra-slow fluctuation training in clinical practice: A technical history. NeuroRegulation, 1(2), 187–207. https://doi.org/10.15540/nr.1.2.187

Smith, M. L., Leiderman, L., & de Vries, J. (2017). Infra-slow fluctuation (ISF) for autism spectrum disorders. In T. F. Collura & J. A. Frederick (Eds.), Handbook of clinical QEEG and neurotherapy. New York, NY: Routledge/Taylor & Francis Group. https://www.taylorfrancis.com/books/e/9781315754093/chapters/10.4324%2F9781315754093-42

Stein, P. K., Bosner, M. S., Kleiger, R. E., & Conger, B. M. (1994). Heart rate variability: A measure of cardiac autonomic tone. American Heart Journal, 127(5), 1376–1381. https://doi.org/10.1016/0002-8703(94)90059-0

Sztajzel, J. (2004). Heart rate variability: A noninvasive electrodardiographic method to measure the autonomic nervous system. Swiss Medical Weekly, 135(35–36), 514–522. https://www.ncbi.nlm.nih.gov/pubmed/15517504

Thayer, J. F., & Lane, R. D. (2000). A model of neurovisceral integration in emotion regulation and dysregulation. Journal of Affective Disorders, 61(3), 201–216. https://doi.org/10.1016/S0165-0327(00)00338-4

Thought Technology. (2014). BioGraph 6.0 Software User Manual. Montreal, Canada: Thought Technology Ltd.

van der Kruijs, S. J. M., Vonck, K. E. J., Langereis, G. R., Feijs, L. M. G., Bodde, N. M. G., Lazeron, R. H. C., … Cluitmans, P. J. M. (2016). Autonomic nervous system functioning associated with psychogenic nonepileptic seizures: Analysis of heart rate variability. Epilepsy & Behavior, 54, 14–19. https://doi.org/10.1016/j.yebeh.2015.10.014

Warren, S. M., Chou, Y.-H., & Steklis, H. D. (2020). Potential for resting-state fMRI of the amygdala in elucidating neurological mechanisms of adaptive self-regulatory strategies: A systematic review. Brain Connectivity, 10(1), 3–17. https://doi.org/10.1089/brain.2019.0700

Wei, Y., Wu, Y., & Tudor, J. (2017). A real-time wearable emotion detection headband based on EEG measurement. Sensors and Actuators A: Physical, 263, 614–621. https://doi.org/10.1016/j.sna.2017.07.012

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Published

2020-06-26

Issue

Vol. 7 No. 2 (2020): .

Section

Research Papers

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