Archives of Acoustics, 47, 2, pp. 169-179, 2022
10.24425/aoa.2022.141647

The Influence of a Low-Frequency Musical Fragment on the Neural Oscillations

Kateryna DROZDENKO
National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"
Ukraine

Sergey NAIDA
National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"
Ukraine

Oleksandr DROZDENKO
National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"
Ukraine

Anastasiia DAMARAD
National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"
Ukraine

Dmytro PARENIUK
National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"
Ukraine

Liudmyla VAKULENKO
State Institution National Scientific Center "The M.D. Strazhesko Institute of Cardiology", National Academy of Medical Sciences of Ukraine
Ukraine

Zhanna ADARICHEVA
State Institution National Scientific Center "The M.D. Strazhesko Institute of Cardiology", National Academy of Medical Sciences of Ukraine
Ukraine

Study of musical-acoustic influences, which are used to improve the functional state of a person, as well as her/his neurophysiological or psychological rehabilitation, is very relevant nowadays. It is related with a large number of conflict situations, significant psychological and informational overloads of modern human, permanent stress due to the pandemic, economic crisis, natural and man-made disasters. This work examines the effect of listening to low-frequency music on the percentage of alpha, beta, delta, and theta waves in the total spectral power of the electroencephalogram in the frequency band 0.5–30 Hz. To obtain rhythms of the brain the spectral analysis of filtered native electroencephalogram was used. For statistical analysis of neural oscillations the Student’s t-test and the sign test were implemented with usage of the Lilliefors normality criterion and the Shapiro-Wilk test. Statistically significant differences were identified in alpha, theta and delta oscillations. For the beta rhythm presented music did not play any significant role. An increase in the activity of the alpha rhythm in the temporal (for 2.20 percentage point), central (for 1.51 percentage point), parietal (for 2.70 percentage point), occipital (for 2.22 percentage point) leads of the right hemisphere and the parietal (for 1.74 percentage point) and occipital (for 2.46 percentage point) leads of the left hemisphere and also of the theta rhythm in the temporal leads of the left hemisphere (for 1.13 percentage point) were observed. The downfall of delta rhythm in the frontal lead of the left hemisphere (for 1.51 percentage point) and occipital in both hemispheres (for 1.64 and 1.33 percentage points respectively in the left and right hemispheres) was detected. These may indicate that listening to low-frequency compositions helps to restore the brain in physiological conditions at different functional overload levels, decrease the level of emotional tone, and promote relaxation.
Keywords: electroencephalogram; brain rhythms; music therapy; acoustic influences; bioelectrical activity; spectral analysis
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References

Amaral J.A., Guida H.L., Abreu L.C., Barnabé V., Vanderlei F.M., Valenti V.E. (2016), Effects of auditory stimulation with music of different intensities on heart period, Journal of Traditional and Complementary Medicine, 6(1): 23–28, doi: 10.1016/j.jtcme.2014.11.032.

Buzsáki G. (2006), Rhythms of the Brain, Oxford University Press: New York, doi: 10.1093/acprof:oso/9780195301069.001.0001.

Cherninskyi A.O., Kryzhanovskyi S.A., Zyma I.H. (2011), Elektrofiziolohiia golovnoho mozku ludyny: metodychni rekomendatsii do praktykumu [in Ukrainian], pp. 49, Vydavets V. S. Martyniuk, Kyiv.

Crocker R. (1963), Pythagorean Mathematics and Music, The Journal of Aesthetics and Art Criticism, 22(2): 189–198, doi: 10.2307/427754.

Fancourt D., Ockelford A., Belai A. (2014), The psychoneuroimmunological effects of music: a systematic review and a new model, Brain, Behavior and Immunity, 36: 15–26, doi: 10.1016/j.bbi.2013.10.014.

Fedotchev A.I., Bondar A.T., Bakhchina A.V., Parin S.B., Polevaya S.A., Radchenko G.S. (2016), Music-acoustic signals controlled by subject’s brain potentials in the correction of unfavorable functional states [in Russian], Advances in Physiological Sciences, 47(1): 69–79.

Fedotchev A.I., Radchenko G.S. (2013), Music therapy and “brain music”: state of the art, problems and perspectives [in Russian], Advances in Physiological Sciences, 44(4): 35–50.

Fedotchev A., Radchenko G., Zemlianaia A. (2018), Music of the brain approach to health protection, Journal of Integrative Neuroscience, 17(3): 291–293, doi: 10.31083/JIN-170053.

Ferreri L., Verga L. (2016), Benefits of music on verbal learning and memory: how and when does it work?, Music Perception: An Interdisciplinary Journal, 34(2): 167–182, https://www.jstor.org/stable/26417442.

Fukui H., Toyoshima K. (2008), Music facilitates the neurogenesis, regeneration and repair of neurons, Medical Hypotheses, 71(5): 765–769, doi: 10.1016/j.mehy.2008.06.019.

Harmony T. (2013), The functional significance of delta oscillations in cognitive processing, Frontiers in Integrative Neuroscience, 7: article 83, doi: 10.3389/fnint.2013.00083.

Hughes J.R., Daaboul Y., Fino J.J., Shaw G.L. (1998), The “Mozart effect” on epileptiform activity, Clinical Neurophysiology, 29(3): 109–119, doi: 10.1177/155005949802900301.

Jacobs G.D., Friedman R. (2004), EEG spectral analysis of relaxation techniques, Applied Psychophysiology and Biofeedback, 29(4): 245–254, doi: 10.1007/s10484-004-0385-2.

Jantzen M.G., Howe B.M., Jantzen K.J. (2014), Neurophysiological evidence that musical training influences the recruitment of right hemispheric homologues for speech perception, Frontiers in Psychology, 5: article 171, doi: 10.3389/fpsyg.2014.00171.

Jaušovec N., Jaušovec K., Gerlic I. (2006), The influence of Mozart’s music on brain activity in the process of learning, Clinical Neurophysiology, 117(12): 2703–2714, doi: 10.1016/j.clinph.2006.08.010.

Jenkins J.S. (2001), The Mozart Effect, Journal of the Royal Society of Medicine, 94(4): 170–172, doi: 10.1177/014107680109400404.

Kabuto M., Kageyama T., Nitta H. (1993), EEG power spectrum changes due to listening to pleasant music and their relation to relaxation effects, Nihon Eiseigaku Zasshi, 48(4): 807–818, doi: 10.1265/jjh.48.807.

Kulaychev A.P. (2018), Kompiuternaia elektrofiziolohiya i funktsionalnaya diahnostika [in Russian], p. 469, Izdatelskyi Dom “Infra-M“, Moskva.

Kunavin M.A., Sokolova L.V. (2014), Spectral characteristics of bioelectrical brain activity of students in listening to audio-stimuli of different componentstructural composition [in Russian], Human Ecology, 3: 34–42, doi: 10.33396/1728-0869-2014-3-34-42.

Lehmann J., Seufert T. (2017), The influence of background music on learning in the light of different theoretical perspectives and the role of working memory capacity, Frontiers in Psychology, 8: article 1902, doi: 10.3389/fpsyg.2017.01902.

Liashko D.A., Naida S.A. (2019), Research spectra of complex audio signals and methods of music therapy [in Ukrainian], Electronic and Acoustic Engineering, 2(2): 58–62, doi: 10.20535/2617-0965.2019.2.2.

Lin Y.P., Duann J.R., Chen J.H., Jung T.P. (2010), Electroencephalographic dynamics of musical emotion perception revealed by independent spectral components, Neuroreport, 21(6): 410–415, doi: 10.1097/WNR.0b013e32833774de.

Miendlarzewska E.A., Trost W.J. (2014), How musical training affects cognitive development: rhythm, reward and other modulating variables, Frontiers in Psychology, 7: article 279, doi: 10.3389/fnins.2013.00279.

Mohd Razali N., Yap B. (2011), Power Comparisons of Shapiro-Wilk, Kolmogorov-Smirnov, Lilliefors and Anderson-Darling Tests, Journal of Statistical Modeling and Analytics, 2(1): 21–33.

Montelpare W.J., Read E.A., McComber T., Mahar A., Ritchie K. (2021), Applied Statistics in Healthcare Research, https://pressbooks.library.upei.ca/montelpare/.

Nazarova K.A. (2013), Impact assessment subjective perception of music the functional state of human, Akmeologiya, 46(2): 69–72.

Pareniuk D. (2021), Method of evaluation of the minimal sample size for acoustical signal therapy monitored via electroencephalographic activity of human brain, ScienceRise, 2: 75–82, doi: 10.21303/2313-8416.2021.001736.

Riganello F., Cortese M., Arcuri F., Quintieri M., Dolce G. (2015), How can music influence the autonomic nervous system response in patients with severe disorder of consciousness?, Frontiers in Neuroscience, 9: article 461, doi: 10.3389/fnins.2015.00461.

Rodriguez A.H., Nath Zallek S., Xu M., Aldag J., Russel-Chapin L., Mattei T.A., Litofsky N.S. (2019), Neurophysiological effects of various music genres on electroencephalographic cerebral cortex activity, Journal of Psychedelic Studies JPS, 5(2): 128–148, doi: 10.1556/2054.2019.027.

Sachdev R.N.S., Gaspard N., Gerrard J.L., Hirsch L.J., Spencer D.D., Zaveri H.P. (2015), Delta rhythm in wakefulness: evidence from intracranial recordings in human beings, Journal of Neurophysiology, 114(2): 1248–1254, doi: 10.1152/jn.00249.2015.

Semiletova V.A. (2017), Influence of music of different musical directions on psychophysiological state of human depend on the background eeg-activity, Sciences of Europe, 21(1): 16–22.

Shpenkov O.O., Tukaiev S.V., Zyma I.G., Kryzhanovskyi S.A. (2014), EEG dynamics during the listening to the rock music with modified frequency structure, Bulletin of the Cherkasy Bohdan Khmelnytsky National University. Biological sciences, 2: 121–128.

Smolen D., Topp R., Singer L. (2002), The effect of self-selected music during colonoscopy on anxiety, heart rate, and blood pressure, Applied Nursing Research, 15(3): 126–136, doi: 10.1053/apnr.2002.34140.

Sulewski P. (2019), Modified Lilliefors goodness-offit test for normality, Communications in Statistics – Simulation and Computation, 51(3): 1199–1219, doi: 10.1080/03610918.2019.1664580.

Taylor A.C., Dewhurst S.A. (2017), Investigating the influence of music training on verbal memory, Psychology of Music, 45(6): 814–820, doi: 10.1177/030573561769024.

Trochidis K., Bigand E. (2012), EEG-based emotion perception during music listening, Proceedings of the 12th International Conference on Music Perception and Cognition and the 8th Triennial Conference of the European Society for the Cognitive Sciences of Music, pp. 1018–1021, Thessaloniki.

Ward L.M. (2003), Synchronous neural oscillations and cognitive processes, Trends in Cognitive Sciences, 7(12): 553–559, doi: 10.1016/j.tics.2003.10.012.

Zhou Z., Zhou R., Wei W., Luan R., Li K. (2021), Effects of music-based movement therapy on motor function, balance, gait, mental health, and quality of life for patients with Parkinson’s disease: A systematic review and meta-analysis, Clinical Rehabilitation, 35(7): 937–951, doi: 10.1177/0269215521990526.




DOI: 10.24425/aoa.2022.141647

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