Vol. 12 No. 3 (2020): Archives of Public Health
Review

Applied neuroscience: Why and how biofeedback methodology work?

Nada Pop-Jordanova
Macedonian Academy of Sciences and Arts, Skopje
Sofija Loleska
Public Health Doctoral Studies, Faculty of Medicine,University Ss Ciril and Methodius, Skopje, Republic of North Macedonia

Published 2020-12-15

Keywords

  • biofeedback,
  • assessment,
  • treatment,
  • public health

How to Cite

1.
Pop-Jordanova N, Loleska S. Applied neuroscience: Why and how biofeedback methodology work?. Arch Pub Health [Internet]. 2020 Dec. 15 [cited 2021 Dec. 7];12(3):61-7. Available from: https://id-press.eu/aph/article/view/5635

Abstract

Science cannot achieve its purpose without some practical applications. The aim of this article is to inform our colleagues about some practical uses of the methodology named biofeedback in the general population. It is important for the staff, especially for those employed in the public health service, because this method is not useful only for treating some disorders, but also for obtaining some health attitudes, performances and mental relaxation in the general population.

Downloads

Download data is not yet available.

References

1. Cherry K. What Is Biofeedback and How Does It Work? Very well Mind 2019, May 16. Available at https://www.verywellmind.com/what-is-biofeedback-2794875.
2. Frantzidis CA, Ladas AK, Vivas A B, Tsolaki M, Bamidis PD. Cognitive and physical training for the elderly: evaluating outcome efficacy by means of neurophysiological synchronization. Int J Psychophysiol 2014; 93, 1–11.
3. Frantzidis CA, Vivas AB, Tsolaki A, Klados M A, Tsolaki M, Bamidis P D. Functional disorganization of small-world brain networks in mild Alzheimer’s disease and amnestic mild cognitive impairment: an EEG study using relative wavelet entropy (RWE). Front Aging Neurosci 2014b; 6:224.
4. Becerra J, Fernández T, Roca-Stappung M, Díaz-Comas L, Galán L, Bosch J, Espino M et al. Neurofeedback in healthy elderly human subjects with electroencephalographic risk for cognitive disorder. J Alzheimers Dis 2012; 28(2): 357-67.
5. Omejc N, Rojc B, Battaglini PP, Marusic U. Neurofeedback for insomnia: a pilot study of Z-score SMR and individualized protocols. Bosn J Basic Med Sci 2019;19(3):213-220.
6. Hammer BU, Colbert AP, Brown KA, Ilioi EC. EEG neurofeedback: a brief overview and an example of peak alpha frequency training for cognitive enhancement in the elderly. Appl Psychophysiol Biofeedback 2011; 36(4):251-64.
7. Angelakis E, Stathopoulou S, Frymiare JL, Green DL, Lubar JF, Kounios . EEG neurofeedback: a brief overview and an example of peak alpha frequency training for cognitive enhancement in the elderly. J Clin Neuropsychol 2007;21(1):110-29.
8. Lecomte G, Juhel J. The effects of neurofeedback training on memory performance in elderly subjects. Psychology 2011; 2(8): 846-852
9. Jirayucharoensak S, Israsena P, Panngum S, Hemrungrojn S, Maes M. A game-based neurofeedback training system to enhance cognitive performance in healthy elderly subjects and in patients with amnestic mild cognitive impairment. Clin Interv Aging 2019; 14:347-360.
10. Bamidis PD , Vivas AB, Styliadis C, Frantzidis C , Klados M , Schlee W, Siountas A , Papageorgiou SG. . A review of physical and cognitive interventions in aging. Neurosci Biobehav Rev 2014; 44:206-20.
11. Pagani LS., Fitzpatrick C, Belleau L, Janosz M. Predicting academic achievement in fourth grade from kindergarten cognitive, behavioural and motor skills,” Québec Longitudinal Study of Child Development (QLSCD 1998-2010) – From Birth to 10 Years, Québec. Institut de la statistique du Québec. 2011; Vol. 6, Fascicle 1.
12. Stankovic D, Nikolic V, Djordjevic M, Cao DB. A survey study of critical success factors in agile software projects in former Yugoslavia IT companies. Journal of Systems and Software 2013; 86(6):1663–1678.
13. Liu C, Yao R, Wang Z, Zhou R. N450 as a candidate neuronal marker for interference control deficits in children with learning disabilities. Int J Psychophysiol 2014; 1: 70-77.
14. Gruzelier JH. EEG-neurofeedback for optimising performance. II: creativity, the performing arts and ecological validity. Neurosci Biobehav Rev 2014;44:142-58.
15. Gruzelier JH. Differential effects on mood of 12-15 (SMR) and 15-18 (beta1) Hz neurofeedback. Int J Psychophysiol 2014;93(1):112-5.
16. Gruzelier JH. EEG-neurofeedback for optimising performance. I: a review of cognitive and affective outcome in healthy participants. Neurosci Biobehav Rev 2014;44:124-41.
17. Gruzelier JH. EEG-neurofeedback for optimising performance. III: a review of methodological and theoretical considerations. Neurosci Biobehav Rev 2014;44:159-82
18. Pop-Jordanova N, Bazanova O, Georgiev D, Kondratenko A, Kondratenko O, Markovska-Simoska S, Mernaya J. Simultaneous EEG and EMG Biofeedback for Peak Performance in Musicians. Proceedings of Workshops and Scientific Programme: [Inaugural Meeting of the SAN & EU COST B27, 14th - 19th September 2006; Swansea, UK], Swansea University, 2006: 23.
19. Peeters F, Ronner J, Bodar L, van Os J, Lousberg R. Validation of a neurofeedback paradigm: Manipulating frontal EEG alpha-activity and its impact on mood. International Journal of Psychophysiology 2014; 93(1), 116-120.
20. Tenev A, Markovska-Simoska S, Kocarev Lj, Pop-Jordanov J, Müller A, Candrian G et al. Machine learning approach for classification of ADHD adults. International Journal of Psychophysiology 2014; 93(1): 162-166.
21. Pop-Jordanova N., Pop-Jordanov J. Spectrum Weighted EEG Frequency (“Brain-rate”) as a Quantitative Indicator of Mental Arousal. Contributions.MASA(Sec. Biol. Med. Sci.), 2005; 26 (2): 35-42.
22. Pop-Jordanov J., Pop-Jordanova N. Neurophysical substrates of arousal and attention. Cognitive Processing 2009; 10(Suppl. 1): S1-S9.
23. Pop-Jordanov J, Pop-Jordanova N, Kocevski S. EEG spectrum gravity as a preliminary arousal indicator and neurofeedback parameter. Neuroscience Letters 2011; 500, Suppl.
24. Pop-Jordanova N, Demerdzieva A. Biofeedback Training for Peak Performance in Sport- Case Report, Macedonian Journal of Medical Sciences 2010; 3(2): 113-118.
25. Pop-Jordanova N, Cakalaroska I. Comparison of Biofeedback Modalities for Better Achievement in High School Students, Macedonian Journal of Medical Science, 2008; 1 (2): 25-30.
26. Pop-Jordanova N, Zorcec T, Demerdzieva A. Electrodermal Biofeedback in Treating Psychogenic Nonepileptic Seizures, Contributions MASA (Sec. Biol. Med. Sci.), 2005; 26 (2): 43-51.
27. Pop-Jordanova N. Biofeedback application for somatoform disorders and attention deficit hyperactivitydisorder (ADHD) in children. International Journal of Medicine and Medical Sciences 2009; 1 (2): 17–22.
28. Pop-Jordanova N, Markovska-Simoska S, Kocubovski M. Neurofeedback and peripheral biofeedback study of children exposed to lead emissions, Abstracts:International Society for Neuronal Regulation (ISNR) European Chapter, 2nd Annual Meeting 2004, 24-28 February, Winterthur, Switzerland, ISNR-EU, 2004: 12.

29. Pop-Jordanova N. Chapter IV: Biofeedback modalities for children and adolescents. In: New Research on Biofeedback, ed. H. L. Puckhaber, Nova Biomedical Books, New York, 2005: 117-131.
30. Pop-Jordanova N. Heart rate variability in the assessment and biofeedback training of common mental health problems in children. Medical Archives 2009; 63 (5): 248-252

31. Pop-Jordanova N. Chapter 13: QEEG characteristics and biofeedback modalities in children with ADHD. In: Current Directions in ADHD and its Treatment, ed. J.M. Norvilitis, InTech, Rijeka, Croatia, 2012: 249-268.

32. Pop-Jordanova N., Pop-Jordanov J. Psychophysiological comorbidity and computerized biofeedback. The International Journal of Artificial Organs 2002; 25 (2):429-433.