Published date: Nov 01 2018

Journal Title: KnE Life Sciences

Issue title: The Fifth International Luria Memorial Congress «Lurian Approach in International Psychological Science»

Pages: 868–877

DOI: 10.18502/kls.v4i8.3344

A Trofimovasandratrofimova@gmail.com

E Silina

O Dobrushina

S Isaychev

Background: Stroke patients develop the ability to perform higher levels of functional activity on basis of concentrated rehabilitative training which affects sensory, motor and cognitive functions. Objective: The main aim of our work was to show the usefullness of neurofeedback therapy in rehabilitation of stroke patients. Design: 27 stroke patients with severe disabilitis were included in the pilot study (men aged 32 to 68 years, mean age 52.4 ± 3.29 years, median 57 years). They all underwent complex study of brain bioelectrical activity EEG and 15 trainings of neurofeedback. Results: By the end of the rehabilitation (after 17 sessions) recollection of psychotrauma led to an increase in the power of the alpha rhythm in both left and right hemispheres. At
the endpoint of the study differences in the power of the alpha rhythm in the left hemisphere were 1.47 times greater, and in the right hemisphere, 1.95 times greater than at the first visit. The regress of theta rhythm (1.25 times in the left, 1.11 times in the right hemisphere) decreased considerable, which affected the alpha / theta
ratio - decreased 1.04 times in the left, 1.18 times in the right hemisphere, and also the coefficient (alpha + theta) / beta - decreased 1.17 times in the left and 1.21 times in the right. Differences in the saturation of blood vessels index at the last visit were 1.69 times greater than at the first visit. Neurophysiological changes correlated with an improvement in the emotional shpere. By the time of discharge, the indicators on the Beck depression scale decreased by 1.4 times, on the Spielberger-Khanin scale, situational anxiety decreased by 1.63 times, personal anxiety - by 1.4 times; regression of indicators in the hospital scale of anxiety and depression (HADS) was observed in 1.89 times. Conclusion: The data presented indicate that the use of the neurofeedback
method leads to a reduction of anxiety-depressive disorders, which positively affects the usefulness of combine rehabilitation.

Keywords: stroke, neurofeedback, electroencephalogram, alpha rhythm, rehabilitation.

[1] Cho, H.-Y., Kim, K.-T., & Jung, J.-H. (2016). Effects of neurofeedback and computer-assisted cognitive rehabilitation on relative brain wave ratios and activities of daily living of stroke patients: a randomized control trial. Journal of Physical Therapy Science, 28(7), 2154–8. https://doi.org/10.1589/jpts.28.2154


[2] Chrapusta, A., Pąchalska, M., Wilk-Frańczuk, M., Starczyńska, M., & Kropotov, J. D. (2015). Evaluation of the effectiveness of neurofeedback in the reduction of Posttraumatic stress disorder (PTSD) in a patient following high-voltage electric shock with the use of ERPs. Annals of Agricultural and Environmental Medicine, 22(3),
556–563. https://doi.org/10.5604/12321966.1167734


[3] Claassen, J., Hirsch, L. J., Kreiter, K. T., Du, E. Y., Sander Connolly, E., Emerson, R. G., & Mayer, S. A. (2004). Quantitative continuous EEG for detecting delayed cerebral ischemia in patients with poor-grade subarachnoid hemorrhage. Clinical Neurophysiology, 115(12), 2699–2710. https://doi.org/10.1016/j.clinph.2004.06.017


[4] Doppelmayr, M., Nosko, H., & Fink, A. (2007). An Attempt to Increase Cognitive Performance After Stroke With Neurofeedback. Biofeedback, 35(4), 126–130. http: //www.ncbi.nlm.nih.gov/pubmed/22081825


[5] Egner, T., Zech, T., & Gruzelier, J. (2004). The effects of neurofeedback training on the spectral topography of the electroencephalogram. Clinical Neurophysiology, 115(11), 2452-2460. https://doi.org/10.1016/j.clinph.2004.05.033


[6] Escolano, C., Olivan, B., Lopez-Del-Hoyo, Y., Garcia-Campayo, J., & Minguez, J. (2012). Double-blind single-session neurofeedback training in upper-alpha for cognitive enhancement of healthy subjects. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, 4643–4647. https: //doi.org/10.1109/EMBC.2012.6347002


[7] Finnigan, S. P., Walsh, M., Rose, S. E., & Chalk, J. B. (2007). Quantitative EEG indices of sub-acute ischaemic stroke correlate with clinical outcomes. Clinical Neurophysiology, 118(11), 2525–2532 https://doi.org/10.1016/j.clinph.2007.07.021


[8] Finnigan, S., & van Putten, M. J. (2013). EEG in ischaemic stroke: Quantitative EEG can uniquely inform (sub-)acute prognoses and clinical management. Clinical Neurophysiology, 124(1), 10–19. https://doi.org/10.1016/j.clinph.2012.07.003


[9] Giaquinto, S., Cobianchi, A., Macera, F., & Nolfe, G. (1994). EEG recordings in the course of recovery from stroke. Stroke: A Journal of Cerebral Circulation. Stroke, 25(11), 2204–2209 ISSN 0039-2499, PMID 7974546.


[10] Gruzelier, J. H. (2014). EEG-neurofeedback for optimising performance. I: A review of cognitive and affective outcome in healthy participants. Neuroscience & Biobehavioral Reviews, 44, 124–141. https://doi.org/10.1016/j.neubiorev.2013.09. 015


[11] Jacobson, L., Koslowsky, M., & Lavidor, M. (2012). tDCS polarity effects in motor and cognitive domains: a meta-analytical review. Experimental Brain Research, 216(1), 1–10. https://doi.org/10.1007/s00221-011-2891-9


[12] Jordan, K. (2004). Emergency EEG and continuous EEG monitoring in acute ischemic stroke. Journal of Clinical Neurophysiology, 21(5), 341–352. ISSN 0736-0258, PMID 15592008.


[13] Kaplan, P., & Rossetti, A. (2011). EEG patterns and imaging correlations in encephalopathy: encephalopathy Part II. Journal of Clinical Neurophysiology, 28(3), 233–251. https://doi.org/10.1097/WNP.0b013e31821c33a0


[14] Klimesch, W. (1999). EEG alpha and theta oscillations reflect cognitive and memory performance: A review and analysis. Brain Research, 29(2–3), 169–195. PMID 10209231


[15] Kober, S. E., Schweiger, D., Witte, M., Reichert, J. L., Grieshofer, P., Neuper, C., & Wood, G. (2015b). Specific effects of EEG based neurofeedback training on memory functions in post-stroke victims. Journal of Neuroengineering and Rehabilitation, 12(107), 1–13. https://doi.org/10.1186/s12984-015-0105-6


[16] Kober, S. E., Schweiger, D., Reichert, J. L., Neuper, C., & Wood, G. (2017). Upper Alpha Based Neurofeedback Training in Chronic Stroke: Brain Plasticity Processes and Cognitive Effects. Applied Psychophysiology Biofeedback. https://doi.org/10.1007/ s10484-017-9353-5


[17] Kropotov, J. D. (2009). Quantitative EEG, event-related potentials and neurotherapy (1st edn.). Amsterdam: Elsevier/Academic press.


[18] Krucoff, M. O., Rahimpour, S., Slutzky, M. W., Edgerton, V. R., & Turner, D. A. (2016). Enhancing nervous system recovery through neurobiologics, neural interface training, and neurorehabilitation. Frontiers in Neuroscience. https://doi. org/10.3389/fnins.2016.00584


[19] Legarda, S. B., McMahon, D., Othmer, S., & Othmer, S. (2011). Clinical Neurofeedback: Case Studies, Proposed Mechanism, and Implications for Pediatric Neurology Practice. Journal of Child Neurology, 26(8), 1045–1051. https://doi.org/10.1177/ 0883073811405052


[20] Melkas, S., Jokinen, H., Hietanen, M., & Erkinjuntti, T. (2014). Poststroke cognitive impairment and dementia: prevalence, diagnosis, and treatment. Gegenerative Neurological and Neuromuscular Disease, 4, 21-27. https://doi.org/10.2147/DNND. S37353


[21] Nelson, L. (2007). The Role of biofeedback in stroke rehabilitation: Past and future directions. Topics in Stroke Rehabilitation, 14(4), 59–66. https://doi.org/10.1310/ tsr1404-59


[22] Niedermeyer, E. (2005). Cerebrovascular disorders and EEG. In E. Niedermeyer, & F. H. Lopes da Silva (Eds.), Electroencephalography: Basic principles, Clinical applications, and related fields. (pp. 339–362). Baltimore, MD: Lippincott Williams & Wilkins, (5 th ed.).


[23] Putman, J. (2002). EEG Biofeedback on a female stroke patient with depression: A case study. Journal of Neurotherapy, 5(3), 27–38. https://doi.org/10.1300/ J184v05n03_04


[24] Reichert, J. L., Kober, S. E., Schweiger, D., Grieshofer, P., Neuper, C., & Wood, G. (2016). Shutting down sensorimotor interferences after stroke. A proof-of-principle SMR neurofeedback study. Frontiers in Human Neuroscience, 10(348), 1–14. https://doi. org/10.3389/fnhum.2016.00348


[25] Rozelle, G. R., & Budzynski, T. H. (1995). Neurotherapy for stroke rehabilitation: A single case study. Biofeedback and self-regulation, 20(3), 211–228. PMID 7495916.


[26] Sheorajpanday, R. V., Nagels, G., Weeren, A. J., van Putten, M. J., & de Deyn, P. P. (2011). Quantitative EEG in ischemic stroke: Correlation with functional status after 6 months. Clinical Neurophysiology, 122(5), 874–883. https://doi.org/10.1016/ j.clinph.2010.07.028


[27] Sitaram, R., Ros, T., Stoeckel, L., Haller, S., Scharnowski, F., Lewis-Peacock, J., … Sulzer, J. (2016). Closed-loop brain training: the science of neurofeedback. Nature Reviews Neuroscience, 18(2). https://doi.org/10.1038/nrn.2016.164


[28] Tecchio, F., Pasqualetti, P., Zappasodi, F., Tombini, M., Lupoi, D., Vernieri, F., & Rossini, P. M. (2007). Outcome prediction in acute monohemispheric stroke via magnetoencephalography. Journal of Neurology, 254(3), 296–305. https://doi.org/ 10.1007/s00415-006-0355-0


[29] Tibbles, A., Renton, T., & Topolovec-Vranic, J. (2017). Neurofeedback as a Form of Cognitive Rehabilitation Therapy Following Stroke: A Systematic Review. Archives of Physical Medicine and Rehabilitation, 96(12), e27. https://doi.org/10.1016/j.apmr. 2015.10.075


[30] Tolonen, U., & Sulg, I. A. (1981). Comparison of quantitative EEG parameters from four different analysis techniques in evaluation of relationships between EEG and CBF in brain infarction. Electroencephalography and Clinical Neurophysiology, 51(2), 177–185.


[31] Zappasodi, F., Tombini, M., Milazzo, D., Rossini, P. M., & Tecchio, F. (2007). Delta dipole density and strength in acute monohemispheric stroke. Neuroscience Letters, 416(3), 310–314. https://doi.org/10.1016/j.neulet.2007.02.017