Investigation of Brain Activity While Listening to Music by Using Brain Control Interface (BCI)
Authors: Hovhannisyan Anahit , Kulhandjian Hovannes , Savala Daniel , Gill Sukhraj , Behan Rachel , Rubio Rodrigo , Perry Jacob 
Published: May 2024

There are five main types of brain waves: alpha, beta, delta, gamma, and theta, which are associated with different states of the mind1. Previous research has shown that music alters the ratio of brain waves in the brain and has significant effects on the brain and body in a clinical setting2. Bigliassi et al. (2015) study showed that calm music can lower vagal withdrawal through increased activation of the prefrontal cortex. Additionally, Nawaz et al. (2018) explained that stimulating and calm music increases the beta and alpha waves in the frontal and parietal regions of the brain, respectively. Although the effects of music on the brain are well studied, the quantification of these effects is not well documented in the current literature. Therefore, our study focuses on the quantification of these effects. We have used BCI technology, which creates a communication pathway between neural activity and external devices, such as drones or prosthetic arms, via neural signals. BCI technology requires recording of brain activity, which can be done invasively or non-invasively with electrical conductors5. The neural activity required for BCI is measured through electroencephalograms (EEGs), which are thought to be generated by cortical pyramidal neurons6. For our research, we used our BCI technology to accumulate and quantify EEG data to address the effects of music on brain waves. References: Frey, St Louis, E. K., & Britton, J. W. (2016). Electroencephalography (EEG): an introductory text and atlas of normal and abnormal findings in adults, children, and infants (Frey & E. K. St Louis, Eds.). American Epilepsy Society. Kučikienė, D., & Praninskienė, R. (2018). The impact of music on the bioelectrical oscillations of the brain. Acta Medica Lituanica, 25(2). DOI: 10.6001/actamedica.v25i2.3763. Bigliassi, M., Barreto-Silva, V., Altimari, L. R., Vandoni, M., Codrons, E., & Buzzachera, C. F. (2015). How Motivational and Calm Music May Affect the Prefrontal Cortex Area and Emotional Responses: A Functional Near-Infrared Spectroscopy (fNIRS) Study. Perceptual and Motor Skills, 120(1), 202–218. DOI: 10.2466/27.24.pms.120v12x5. Nawaz, R., Nisar, H., & Voon, Y. V. (2018). The Effect of Music on Human Brain; Frequency Domain and Time Series Analysis Using Electroencephalogram. IEEE Access, 6, 45191–45205. DOI: 10.1109/access.2018.2855194. Hinterberger, T., & Neumann, N. (2018). Invasive and non-invasive brain-computer interfaces. In S. Coyle, M. Prasad, & H. Lotze (Eds.), Brain-Computer Interfaces Handbook: Technological and Theoretical Advances (pp. 33-42). CRC Press. DOI: 10.1201/9781315371605-3. Frey, St Louis, E. K., & Britton, J. W. (2016). Electroencephalography (EEG): an introductory text and atlas of normal and abnormal findings in adults, children, and infants (Frey & E. K. St Louis, Eds.). American Epilepsy Society. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.