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High and low pitch sound stimuli effects on heart-brain coupling

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Abstract

This study aimed to explore the influence of sound stimulation on heart rate and the potential coupling between cardiac and cerebral activities. Thirty-one participants underwent exposure to periods of silence and two distinct continuous, non-repetitive pure tone stimuli: low pitch (110 Hz) and high pitch (880 Hz). Electroencephalography (EEG) data from electrodes F3, F4, F7, F8, Fp1, Fp2, T3, T4, T5, and T6 were recorded, along with R-R interval data for heart rate. Heart-brain connectivity was assessed using wavelet coherence between heart rate variability (HRV) and EEG envelopes (EEGE). Heart rates were significantly lower during high and low-pitch sound periods than in silence (p < 0.002). HRV-EEGE coherence was significantly lower during high-pitch intervals than silence and low-pitch sound intervals (p < 0.048), specifically between the EEG Beta band and the low-frequency HRV range. These results imply a differential involvement of the frontal and temporal brain regions in response to varying auditory stimuli. Our findings highlight the essential nature of discerning the complex interrelations between sound frequencies and their implications for heart-brain connectivity. Such insights could have ramifications for conditions like seizures and sleep disturbances. A deeper exploration is warranted to decipher specific sound stimuli’s potential advantages or drawbacks in diverse clinical scenarios.

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References

  1. Bartsch RP, Liu KKL, Bashan A, Ivanov PC. Network Physiology: how Organ systems dynamically interact. PLoS ONE. 2015;10. https://doi.org/10.1371/JOURNAL.PONE.0142143.

  2. Pfurtscheller K, Bauernfeind G, Müller-Putz GR, Urlesberger B, Müller W, Pfurtscheller G. Correlation between EEG burst-to-burst intervals and HR acceleration in preterm infants. Neurosci Lett. 2008;437:103–6. https://doi.org/10.1016/J.NEULET.2008.03.079.

    Article  CAS  PubMed  Google Scholar 

  3. Piper D, Schiecke K, Leistritz L, Pester B, Benninger F, Feucht M, et al. Synchronization analysis between heart rate variability and EEG activity before, during, and after Epileptic Seizure. Biomed Tech (Berl). 2014;59:343–55. https://doi.org/10.1515/BMT-2013-0139.

    Article  PubMed  Google Scholar 

  4. Sattin D, Duran D, Visintini S, Schiaffi E, Panzica F, Carozzi C, et al. Analyzing the loss and the recovery of consciousness: functional connectivity patterns and changes in Heart Rate Variability during Propofol-Induced Anesthesia. Front Syst Neurosci [Internet]. 2021. https://doi.org/10.3389/fnsys.2021.652080. [citado 17 de outubro de 2023];15. Disponível em. https://www.frontiersin.org/articles/.

    Article  PubMed  Google Scholar 

  5. Bernardi L, Porta C, Sleight P. Cardiovascular, cerebrovascular, and respiratory changes induced by different types of music in musicians and non-musicians: the importance of silence. Heart. 2006;92:445–52. https://doi.org/10.1136/HRT.2005.064600.

    Article  CAS  PubMed  Google Scholar 

  6. Orini M, Bailón R, Enk R, Koelsch S, Mainardi L, Laguna P. A method for continuously assessing the autonomic response to music-induced emotions through HRV analysis. Med Biol Eng Comput. 2010;48:423–33. https://doi.org/10.1007/S11517-010-0592-3.

    Article  PubMed  Google Scholar 

  7. Hartikainen K, Rorarius M, Mäkelä K, Yli-Hankala A, Jäntti V. Propofol and isoflurane induced EEG burst suppression patterns in rabbits. Acta Anaesthesiol Scand. 1995;39:814–8.

    Article  CAS  PubMed  Google Scholar 

  8. Schnabel RB, Hasenfuß G, Buchmann S, Kahl KG, Aeschbacher S, Osswald S, et al. Heart and brain interactions. Herz. 1o de março de 2021;46(2):138–49.

  9. Rajesh P, Umamaheswari K. Coherence analysis between heart and brain of healthy and unhealthy subjects. Em: 2017 11th International Conference on Intelligent Systems and Control (ISCO) [Internet]. 2017 [citado 17 de outubro de 2023]. p. 351–6. Disponível em: https://ieeexplore.ieee.org/abstract/document/7856015.

  10. Signal Processing Techniques for Coherence Analysis Between ECG. and EEG Signals with a Case Study | SpringerLink [Internet]. [citado 17 de outubro de 2023]. Disponível em: https://link.springer.com/chapter/10.1007/978-981-33-6984-9_48.

  11. EEG and HRV markers of sleepiness. and loss of control during car driving | IEEE Conference Publication | IEEE Xplore [Internet]. [citado 17 de outubro de 2023]. Disponível em: https://ieeexplore.ieee.org/document/4649724.

  12. Clerico A, Tiwari A, Gupta R, Jayaraman S, Falk TH. Electroencephalography Amplitude Modulation Analysis for Automated Affective Tagging of Music Video Clips. Front Comput Neurosci [Internet]. 2018 [citado 17 de outubro de 2023];11. Disponível em: https://www.frontiersin.org/articles/https://doi.org/10.3389/fncom.2017.00115.

  13. Ulrich T. Envelope Calculation from the Hilbert Transform. 17 de março de 2006.

  14. Sheen YT. On the study of applying Morlet wavelet to the Hilbert transform for the envelope detection of bearing vibrations. Mech Syst Signal Process. 1o de julho de 2009;23(5):1518–27.

  15. Luccas FJC, Anghinah R, Braga NIO, Fonseca LC, Frochtengarten ML, Jorge MS, et al. [Guidelines for recording/analyzing quantitative EEG and evoked potentials. Part II: clinical aspects]. Arq Neuropsiquiatr. 1999;57:132–46. https://doi.org/10.1590/S0004-282X1999000100026.

    Article  CAS  PubMed  Google Scholar 

  16. Otero TM, Barker LA. The frontal lobes and executive functioning. In: Goldstein S, Naglieri J, editors. Handbook of executive functioning. New York, NY: Springer; 2014. https://doi.org/10.1007/978-1-4614-8106-5_3.

    Chapter  Google Scholar 

  17. Hosseini M-P, Hosseini A, Ahi K. A review on machine learning for EEG Signal Processing in Bioengineering. IEEE Rev Biomed Eng. 2021;14:204–18. https://doi.org/10.1109/TBME.2020.2969915.

    Article  PubMed  Google Scholar 

  18. Bahmer A, Gupta DS. Role of oscillations in auditory temporal Processing: a General Model for Temporal Processing of Sensory Information in the brain? Front. Neurosci. 2018;12:793. https://doi.org/10.3389/fnins.2018.00793. - Google Search.

    Article  Google Scholar 

  19. Neto OP, Oliveira Pinheiro A, Pereira VL, Pereira R, Baltatu OC, Campos LA. Morlet wavelet transforms of heart rate variability for autonomic nervous system activity. Appl Comput Harmon Anal. 1o de janeiro de 2016;40(1):200–6.

  20. Cysarz D, Lange S, Matthiessen PF, van Leeuwen P. Regular heartbeat dynamics are associated with cardiac health. Am J Physiol-Regul Integr Comp Physiol janeiro de. 2007;292(1):R368–72.

    Article  CAS  Google Scholar 

  21. Hyvärinen A. Fast and robust fixed-point algorithms for Independent component analysis. IEEE Trans Neural Networks. 1999;10(3):626–34.

    Article  PubMed  Google Scholar 

  22. Mognon A, Jovicich J, Bruzzone L, Buiatti M. ADJUST: an automatic EEG artifact detector based on the joint use of spatial and temporal features. Psychophysiology. 2011;48(2):229–40.

    Article  PubMed  Google Scholar 

  23. Thayer JF, Åhs F, Fredrikson M, Sollers JJ, Wager TD. A meta-analysis of heart rate variability and neuroimaging studies: implications for heart rate variability as a marker of stress and health. Neurosci Biobehav Rev. 2012;36:747–56. https://doi.org/10.1016/J.NEUBIOREV.2011.11.009.

    Article  PubMed  Google Scholar 

  24. Jurysta F, van de Borne P, Migeotte PF, Dumont M, Lanquart JP, Degaute JP, et al. A study of the dynamic interactions between sleep EEG and heart rate variability in healthy young men. Clin Neurophysiol. 2003;114:2146–55. https://doi.org/10.1016/S1388-2457(03)00215-3.

    Article  CAS  PubMed  Google Scholar 

  25. Grinsted A, Moore JC, Jevrejeva S. Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear Process Geophys. 2004;11:561–6. https://doi.org/10.5194/NPG-11-561-2004.

    Article  ADS  Google Scholar 

  26. Pinto Neto O, Pinto IRCA, Pinto O. The relationship between thunderstorm and solar activity for Brazil from 1951 to 2009. J Atmospheric Sol-Terr Phys. 1o de junho de 2013;98:12–21.

  27. Wang Y, Neto OP, Weinrich MM, Castro R, Wright T, Kennedy DM. The influence of distal and proximal muscle activation on neural crosstalk. PLoS One. 2022;17. https://doi.org/10.1371/JOURNAL.PONE.0275997.

  28. Topographic EEG/MEG plot - File Exchange - MATLAB Central [Internet]. [citado 17 de outubro de 2023]. Disponível em: https://www.mathworks.com/matlabcentral/fileexchange/72729-topographic-eeg-meg-plot.

  29. Nakajima Y, Tanaka N, Mima T, Izumi SI. Stress Recovery effects of High- and low-frequency amplified music on Heart Rate Variability. Behavioural Neurology. 2016;2016. https://doi.org/10.1155/2016/5965894.

  30. Veternik M, Tonhajzerova I, Misek J, Jakusova V, Hudeckova H, Jakus J. The impact of sound exposure on heart rate variability in adolescent students. Physiol Res. 2018;67:695–702.

    Article  CAS  PubMed  Google Scholar 

  31. Calamassi D, Pomponi GP. Music tuned to 440 hz Versus 432 hz and the Health effects: a double-blind cross-over pilot study. Explore (NY). 2019;15:283–90. https://doi.org/10.1016/J.EXPLORE.2019.04.001.

    Article  PubMed  Google Scholar 

  32. Hori K, Yamakawa M, Tanaka N, Murakami H, Kaya M, Hori S. Influence of sound and light on heart rate variability. J Hum Ergol (Tokyo). 2005;34:25–34.

  33. Hülsdünker T, Riedel D, Käsbauer H, Ruhnow D, Mierau A. Auditory information accelerates the Visuomotor reaction speed of Elite Badminton players in Multisensory environments. Front Hum Neurosci [Internet]. 2021.

  34. Collins A, Koechlin E. Reasoning, Learning, and Creativity: frontal lobe function and human decision-making. PLOS Biol. 27 de março de. 2012;10(3):e1001293.

    Article  CAS  Google Scholar 

  35. McKay CM, Lim HH, Lenarz T. Temporal Processing in the Auditory System. J Assoc Res Otolaryngol. 1o de fevereiro de 2013;14(1):103–24.

  36. Sounds and words are processed separately and simultaneously in the brain | ScienceDaily [Internet]. [citado 17 de outubro de 2023]. Disponível em: https://www.sciencedaily.com/releases/2021/08/210818130509.htm.

  37. An Overview of Heart Rate Variability Metrics and Norms - PMC [Internet]. [citado 17 de outubro de 2023]. Disponível em: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5624990/.

  38. Intrinsic Neural Timescales in the Temporal Lobe Support an Auditory Processing Hierarchy. | Journal of Neuroscience [Internet]. [citado 17 de outubro de 2023]. Disponível em: https://www.jneurosci.org/content/43/20/3696.

  39. Stuldreher et al. Found that physiological synchrony in EEG, electrodermal activity, and heart rate - Google search [Internet]. [citado 17 de outubro de 2023]. 2020.

  40. Blood AJ, Zatorre RJ. Intensely pleasurable responses to music correlate with activity in brain regions implicated in reward and emotion. Proc Natl Acad Sci U S A. 2001;98:11818–23. https://doi.org/10.1073/PNAS.191355898. - Google Search [Internet]. [citado 17 de outubro de 2023].

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  41. Bigliassi M, Karageorghis CI, Wright MJ, Orgs G, Nowicky AV. Effects of auditory stimuli on electrical activity in the brain during cycle ergometry. Physiol Behav. 1o de agosto de 2017;177:135–47.

  42. Alba et al. Frontiers | The Relationship between Heart Rate Variability and Electroencephalography Functional Connectivity variability is Associated with Cognitive Flexibility (frontiersin.org) - Google search [Internet]. [citado 17 de outubro de 2023].

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Funding

The research conducted by authors Osmar Pinto Neto and Ovidiu Constantin Baltatu was supported by scholarships provided by the Anima Institute.

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All authors contributed to the study conception and design. Data collection was performed by Camila Bomfim vonJakitsch. Material preparation was performed by Osmar Pinto Neto, Camila Bomfim vonJakitsch, Tatiana Okubo Rocha Pinho, and Rafael Pereira. The first draft of the manuscript was written by Osmar Pinto Neto, Rafael Pereira and Ovidiu Constantin Baltatu; all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Osmar Pinto Neto.

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Camila Bomfim von Jakitsch and Osmar Pinto Neto contributed equally as the first author.

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von Jakitsch, C.B., Pinto Neto, O., Pinho, T.O.R. et al. High and low pitch sound stimuli effects on heart-brain coupling. Biomed. Eng. Lett. 14, 331–339 (2024). https://doi.org/10.1007/s13534-023-00340-5

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