Dergiler / Rast Müzikoloji Dergisi / 2026 / Volume: 13 Issue: 2

Differences in brain electrical activity between musicians and non-musicians while listening to 440 Hz and 432 Hz musical compositions

Sayfa
—
Yayın Tarihi
2025-06-30
🏛️Bu makalenin bibliyografik verileri ve tam metin bağlantısı DergiPark üzerinden sağlanmıştır.
DergiPark Kaydı ↗
✨

Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

In conclusion, the findings suggest that music frequency can influence brain activity and that there are significant differences in brain responses between musicians and non-musicians.

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:The aim of this study was to examine the effects of music played at 432 Hz and 440 Hz on brain electrical activity, considering the specialization in music.
📊
Temel Bulgular & Veri:The study included 11 non-musicians and 10 musicians, with participants completing two sessions, 24 hours apart.
💡
Sonuç & Katkı:In conclusion, the findings suggest that music frequency can influence brain activity and that there are significant differences in brain responses between musicians and non-musicians.
🔬Tür:Research Article
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:connectivity · EEG · frequency

Özet

The aim of this study was to examine the effects of music played at 432 Hz and 440 Hz on brain electrical activity, considering the specialization in music. The study included 11 non-musicians and 10 musicians, with participants completing two sessions, 24 hours apart. In the first session, participants listened to the 432 Hz Samuel Osmond Barber “Adagio for Strings Op. 11” and the 440 Hz Petrovich Mussorgsky “Night on Bald Mountain” compositions. In the second session, the 440 Hz “Adagio for Strings Op. 11” and the 432 Hz “Night on Bald Mountain” were performed. Brain electrical activity was assessed using coherence and Power Spectral Density (PSD) methods. The results revealed differences in brain electrical activity between musicians and non-musicians when listening to music at different frequencies. In the PSD analysis, a two-way ANOVA showed a significant group effect (p < 0.05; ηp2=0.086) in the O1 channel within the theta frequency. Post hoc Tukey HSD tests revealed that O1 theta values were higher in musicians. Additionally, a significant frequency effect was observed in the Pz channel within the theta frequency (p<0.05; ηp2=0.128), with 440 Hz producing higher Pz theta values. In the T8 channel, a significant frequency effect was found across the alpha 1, alpha 2, and beta 1 bands (p<0.05; ηp2=0.103, 0.102, 0.118), with higher values observed at 440 Hz, but no significant group effect or interaction between group and frequency. Furthermore, coherence analysis indicated higher coherence values in the fronto-occipital region while listening to music at 432 Hz (p<0.05; ηp2=0.101). In conclusion, the findings suggest that music frequency can influence brain activity and that there are significant differences in brain responses between musicians and non-musicians.

Abstract

The aim of this study was to examine the effects of music played at 432 Hz and 440 Hz on brain electrical activity, considering the specialization in music. The study included 11 non-musicians and 10 musicians, with participants completing two sessions, 24 hours apart. In the first session, participants listened to the 432 Hz Samuel Osmond Barber “Adagio for Strings Op. 11” and the 440 Hz Petrovich Mussorgsky “Night on Bald Mountain” compositions. In the second session, the 440 Hz “Adagio for Strings Op. 11” and the 432 Hz “Night on Bald Mountain” were performed. Brain electrical activity was assessed using coherence and Power Spectral Density (PSD) methods. The results revealed differences in brain electrical activity between musicians and non-musicians when listening to music at different frequencies. In the PSD analysis, a two-way ANOVA showed a significant group effect (p < 0.05; ηp2=0.086) in the O1 channel within the theta frequency. Post hoc Tukey HSD tests revealed that O1 theta values were higher in musicians. Additionally, a significant frequency effect was observed in the Pz channel within the theta frequency (p<0.05; ηp2=0.128), with 440 Hz producing higher Pz theta values. In the T8 channel, a significant frequency effect was found across the alpha 1, alpha 2, and beta 1 bands (p<0.05; ηp2=0.103, 0.102, 0.118), with higher values observed at 440 Hz, but no significant group effect or interaction between group and frequency. Furthermore, coherence analysis indicated higher coherence values in the fronto-occipital region while listening to music at 432 Hz (p<0.05; ηp2=0.101). In conclusion, the findings suggest that music frequency can influence brain activity and that there are significant differences in brain responses between musicians and non-musicians.

🔖

Bu Makaleye Atıf Yap

Dirik, H. B., Çınar, C. B. B. (2025). Differences in brain electrical activity between musicians and non-musicians while listening to 440 Hz and 432 Hz musical compositions. Rast Müzikoloji Dergisi, Volume: 13 Issue: 2. https://doi.org/10.12975/rastmd.20251322

📄 Tam Metin PDF Okuyucu

📄

PDF görüntüleyici hazırlanıyor...

Kaynakça (36)

  1. Agrillo, C., & Piffer, L. (2012). Musicians outperform nonmusicians in magnitude estimation: Evidence of a common processing mechanism for time, space and numbers. Quarterly Journal of Experimental Psychology, 65(12), 2321-2332. https://doi. org/10.1080/17470218.2012.680895
  2. Ajjimaporn, A., Noppongsakit, P., Ramyarangsi, P., Siripornpanich, V., & Chaunchaiyakul, R. (2022). A low- dose of caffeine suppresses EEG alpha power and improves working memory in healthy University males. Physiology & Behavior, 256, 113955. https://doi.org/10.1016/j. physbeh.2022.113955
  3. Atan, T. (2013). Effect of music on anaerobic exercise performance. Biology of Sport, 30(1), 35-39. https://doi. org/10.5604/20831862.1029819
  4. Belkhir, Y., Rekik, G., Chtourou, H., & Souissi, N. (2019). Listening to neutral or self-selected motivational music during warm-up to improve short-term maximal performance in soccer players: Effect of time of day. Physiology & Behavior, 204, 168-173. https://doi.org/10.1016/j. physbeh.2019.02.033
  5. Calamassi, D., & Pomponi, G. P. (2019). Music tuned to 440 Hz Versus 432 Hz and the health effects: a double-blind cross-over pilot study. Explore, 15(4), 283–290. https:// doi.org/10.1016/j.explore.2019.04.001
  6. Calamassi, D., Li Vigni, M. L., Fumagalli, C., Gheri, F., Pomponi, G. P., & Bambi, S. (2022). The Listening to music tuned to 440 Hz versus 432 Hz to reduce anxiety and stress in emergency nurses during the COVID-19 pandemic: a double-blind, randomized controlled pilot study. Acta Bio-medica: Atenei Parmensis, 93(S2), e2022149. https://doi.org/10.23750/abm. v93iS2.12915
  7. Carvalhaes, C., & De Barros, J. A. (2015). The surface Laplacian technique in EEG: Theory and methods. International Journal of Psychophysiology, 97(3), 174-188. https:// doi.org/10.1016/j.ijpsycho.2015.04.023
  8. Chang, C. Y., Hsu, S. H., Pion-Tonachini, L., & Jung, T. P. (2018, July). Evaluation of artifact subspace reconstruction for automatic EEG artifact removal. In 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 1242-1245). IEEE. https://doi. org/10.1109/EMBC.2018.8512547
  9. Crossley, E., Biggs, T., Brown, P., & Singh, T. (2021). The accuracy of iPhone applications to monitor environmental noise levels. The Laryngoscope, 131(1), E59-E62. https://doi. org/10.1002/lary.28590
  10. Delorme, A., & Makeig, S. (2004). EEGLAB: An open-source toolbox for analysis of single- trial EEG dynamics including independent component analysis. Journal of Neuroscience Methods, 134(1), 9-21. https://doi. org/10.1016/j.jneumeth.2003.10.009
  11. Di Nasso, L., Nizzardo, A., Pace, R., Pierleoni, F., Pagavino, G., & Giuliani, V. (2016). Influences of 432 Hz music on the perception of anxiety during endodontic treatment: a randomized controlled clinical trial. Journal of Endodontics, 42(9), 1338–1343. https:// doi.org/10.1016/j.joen.2016.05.015
  12. Ding, Y., Gray, K., Forrence, A., Wang, X., & Huang, J. (2018). A behavioral study on tonal working memory in musicians and non-musicians. PloS one, 13(8), e0201765. https://doi.org/10.1371/journal. pone.0201765
  13. D’Souza, A. A., Moradzadeh, L., & Wiseheart, M. (2018). Musical training, bilingualism, and executive function: working memory and inhibitory control. Cognitive Research: Principles and Implications, 3(1), 11. https://doi.org/10.1186/s41235-018-0095-6
  14. Dubey, P., Kumar, Y., Singh, R., Jha, K., & Kumar, R. (2019). Effect of music of specific frequency upon the sleep architecture and electroencephalographic pattern of individuals with delayed sleep latency: A daytime nap study. Journal of Family Medicine and Primary Care, 8(12), 3915– 3919. https://doi.org/10.4103/jfmpc. jfmpc_575_19
  15. Francois, C., & Schon, D. (2011). Musical expertise boosts implicit learning of both musical and linguistic structures. Cerebral Cortex, 21(10), 2357–2365. https://doi. org/10.1093/cercor/bhr022
  16. Frühholz, S., Trost, W., & Kotz, S. A. (2016). The sound of emotions-Towards a unifying neural network perspective of affective sound processing. Neuroscience and Biobehavioral Reviews, 68, 96–110. https:// doi.org/10.1016/j.neubiorev.2016.05.002
  17. George, E. M., & Coch, D. (2011). Music training and working memory: An ERP study. Neuropsychologia, 49(4), 1083–1094. https://doi.org/10.1016/j. neuropsychologia.2011.02.001
  18. Gribenski, F. (2021). Sounding standards: A history concert pitch, between musicology and STS. In Rethinking Music through Science and Technology Studies (pp. 26-46). Routledge.
  19. Haynes, B. (2002). A history of performing pitch: the story of ‘A’. Scarecrow Press.
  20. Herholz, S. C., & Zatorre, R. J. (2012). Musical training as a framework for brain plasticity: behavior, function, and structure. Neuron, 76(3), 486–502. https://doi.org/10.1016/j. neuron.2012.10.011
  21. Hernandez-Ruiz, E., & Dvorak, A. L. (2021). Music and mindfulness meditation: Comparing four music stimuli composed under similar principles. Psychology of Music, 49(6), 1620–1636. https://doi.org/10.1177/0305735620969798
  22. Husain, G., Thompson, W. F., & Schellenberg, E. G. (2002). Effects of musical tempo and mode on arousal, mood, and spatial abilities. Music Perception, 20(2), 151-171. https:// doi.org/10.1525/mp.2002.20.2.151
  23. Klimesch, W. (1999). EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis. Brain Research. Brain Research Reviews, 29(2-3), 169–195. https://doi.org/10.1016/s0165- 0173(98)00056-3
  24. Li, H. C., Wang, H. H., Chou, F. H., & Chen, K. M. (2015). The effect of music therapy on cognitive functioning among older adults: A systematic review and meta-analysis. Journal of the American Medical Directors Association, 16(1), 71-77. https://doi. org/10.1016/j.jamda.2014.10.004
  25. Menziletoglu D, Guler AY, Cayır T, Isik BK. (2021). Binaural beats or 432 Hz music? which method is more effective for reducing preoperative dental anxiety? Med Oral Patol Oral Cir Bucal., 26(1):e97-e101. https:// doi.org/10.4317/medoral.24051
  26. Mikutta, C. A., Maissen, G., Altorfer, A., Strik, W., & König, T. (2014). Professional musicians listen differently to music. Neuroscience, 268, 102-111. https://doi. org/10.1016/j.neuroscience.2014.03.007
  27. Neves, L., Correia, A. I., Castro, S. L., Martins, D., & Lima, C. F. (2022). Does music training enhance auditory and linguistic processing? A systematic review and meta- analysis of behavioral and brain evidence. Neuroscience & Biobehavioral Reviews, 140, 104777. https://doi.org/10.1016/j. neubiorev.2022.104777
  28. Palmblad, S. (2018). A=432: A superior tuning or just a different intonation? How tuning standards affect emotional response, timbre, and sound quality in music. Bachelor’s thesis, Media Arts, Aesthetics, and Narration, University of Skövde, Sweden.
  29. Pavlygina, R. A., Sakharov, D. S., & Davydov, V. I. (2004). Spectral analysis of the human EEG during listening to musical compositions. Human Physiology, 30(1), 54-60. https://doi. org/10.1023/B:HUMP.0000013765.64276.e6
  30. Plechawska-Wojcik, M., Kaczorowska, M., & Zapala, D. (2019). The artifact subspace reconstruction (ASR) for EEG signal correction. A comparative study. In Proceedings of 39th International Conference on Information Systems Architecture and Technology – ISAT 2018, eds J. Świątek, L. Borzemski, and Z. Wilimowska (Cham: Springer), 125–135. https://doi.org/10.1007/978-3-319-99996- 8_12
  31. Rodríguez-Rodríguez, R. C., Noreña-Peña, A., Chafer-Bixquert, T., Lorenzo Vásquez, A., González de Dios, J., & Solano Ruiz, C. (2022). The relevance of music therapy in pediatric and adolescent cancer patients: a scoping review. Global Health Action, 15(1), 2116774. https://doi.org/10.1080/16549716.2022.2116774
  32. Rosenberg, R. E. (2021). Perfect pitch: 432 hz music and the promise of frequency. Journal of Popular Music Studies, 33(1), 137-154. https://doi.org/10.1525/ jpms.2021.33.1.137
  33. Sesso, G., & Sicca, F. (2020). Safe and sound: Meta-analyzing the Mozart effect on epilepsy. Clinical neurophysiology: official journal of the International Federation of Clinical Neurophysiology, 131(7), 1610–1620. https:// doi.org/10.1016/j.clinph.2020.03.039
  34. Verrusio, W., Ettorre, E., Vicenzini, E., Vanacore, N., Cacciafesta, M., & Mecarelli, O. (2015). The Mozart Effect: A quantitative EEG study. Consciousness and Cognition, 35, 150–155. https://doi.org/10.1016/j. concog.2015.05.005
  35. Yi, F., & Kang, J. (2019). Effect of background and foreground music on satisfaction, behavior, and emotional responses in public spaces of shopping malls. Applied Acoustics, 145, 408-419. https://doi.org/10.1016/j. apacoust.2018.10.029
  36. Rodríguez-Rodríguez, R. C., Noreña-Peña, A., Chafer-Bixquert, T., Lorenzo Vásquez, A., González de Dios, J., & Solano Ruiz, C. (2022). The relevance of music therapy in pediatric and adolescent cancer patients: a scoping review. Global Health Action, 15(1), 2116774. https://doi.org/10.1080/16549716.2022.2116774