STEM I

In STEM I, we work on an independent research project on a topic of our choice. This project not only helps to teach time management and research skills, but it allows us to work on and really dive into something that interests us. I chose to work on finding a treatment option for Bipolar Disorder in music as I was interested in the medical uses of different genres of music. More on this project is shown below.

The Impact of Music on Bipolar Disorder

My project prosposal can be viewed if you click here.

Phrase 1

As music has been shown to aid in treatments of other serious mental illnesses, how can different genres of music be used as a treatment option for those with bipolar disorder?

Phrase 2

If music has been used in treatments for serious mental illnesses in the past, it can also be used to create a more specialized, cheaper alternative or supplement to current treatments for Bipolar Disorder. As lithium, a common pill-based treatment for bipolar disorder causes a change in a patient’s brainwaves, a genre of music can provide similar changes to help aid in the treatment process or provide more conclusive evidence of a connection between the disorder and genres of music.

Background

The Impact of Genres of Music on Bipolar Disorder Patients

Costs for treatments for bipolar disorder are increasing and are increasingly inaccessible for individuals in need of treatment (Bessonova et al., 2020). An alternative, cheaper treatment or treatment add-on is needed by many. Music may fit this need for those with Bipolar Disorder while having many of the same benefits, like bringing the brain to a more normalized state, and fewer side effects (Raglio et al., 2015). Also, because of the vast number of genres of music, it allows for more specific treatment for some with Bipolar Disorder. Although it has been around a while, music therapy has yet to be significantly tested with bipolar disorder (Golden et al., 2021). Potential solutions, as well as what genres work best to help treat the disorder continue to remain unknown, resulting in a lack of wide-spread non-medication-based treatments.

Bipolar Disorder

Bipolar Disorder is typically genetically inherited, yet the mode of transmission remains unknown (Kerner, 2014). Those with Bipolar Disorder (BD) struggle with increased energy levels, impulsive behavior, and agitation (McCormick et al., 2015). These symptoms stem from poor sleep cycles and energy level control, which cause the symptoms to be more sporadic. Current treatments for BD like pill-based and psychotherapy-based (treatments involving speaking about symptoms a patient has been facing) treatments work to help regulate these energy levels. Still, they can be expensive, making it difficult for those who are less financially fortunate and have symptoms to acquire (Bessonova et al., 2020).

Hypothesis

The goal of this project was to help develop a music-based alternative treatment to Bipolar Disorder that is cheaper and more widely available. This solution would have similar benefits, like an improved sleep cycle (Loewy, 2020), with less side effects as well. It was hypothesized that if a genre of music can cause changes in brain waves in a person without BD, those same changes will occur in a person with BD. This project was needed to give a cheaper alternative treatment to those with bipolar disorder and one that is easier access as genres of music are widely available on online streaming services. Whether it is used as an alternative treatment or a supplement, it would provide benefits of treatments without the potential side effects or risks from pill-based treatments (Degli Stefani & Biasutti, 2016). Patients can also use the music-based treatment more frequently than pill- based treatments, as there is no dosage interval for listening to music. The treatment option could be used more frequently to treat symptoms as well as provide benefits such as improved sleep and energy levels throughout the day, leading to a decrease in symptoms for those with bipolar disorder. In past observations of the symptoms of Bipolar Disorder, bipolar patients have shown an increase in beta brain waves when compared to normal patients without Bipolar Disorder (Kim et al., 2013). Because this evidence exists, we can look for a treatment that causes a change in the beta brainwaves of normal patients and see if the same treatment causes a change in those with bipolar disorder. To do this, a test was run on people without bipolar disorder, where they listened to different genres of music while attached to an EEG, as music therapy is easily accepted by the brains of those with mood disorders (Trimble & Hesdorffer, 2018). By doing this, the experimenters looked for decreases in the beta waves to see what genre of music best simulates this result. An inference was then drawn that the results shown by non-bipolar patients will likely be similar to the results shown by patients with Bipolar Disorder

Significance

This project’s success is important as bipolar treatments can be difficult to acquire and treatments needed by some are not FDA-approved for bipolar, making treatment difficult for many suffering with the disorder. Music can help bridge this gap for many; it is readily available and has many of the same benefits as bipolar treatments with a much lower cost and little to no side effects. Also, music has been studied very little with bipolar disorder, so a connection between genres of music and treatments for bipolar disorder is yet to have a significant basis to support further research. With this project, the experimenters intend to find evidence of a connection that can allow for cheaper, more effective treatment for those suffering from bipolar disorder.

Procedure

Role of Student vs. Mentor

My mentor helped teach how use the Electroencephalograph (EEG) and helped narrow the scope of my project. All planning of this study as well as the conducting of tests and analysis of results was done by the student. The project was worked on for approximately 4 months, with testing beginning around the third month.

Specific Methods

Firstly, a saline solution was created to allow the electric signals from your brain to have improved conduction and be more accurately picked up by the electroencephalograph (EEG). This solution was made by filling a plastic beaker with 200mL of water and stirring in 1 teaspoon of sodium chloride. We then soaked 16 Hydro-link sponges into the solution to allow for this improved conductivity. Once set up, the EEG was placed on the subject’s head with the Cz node halfway on the midline of the subject’s head. The OpenBCI GUI was used for real-time tracking of the subject’s brainwaves. Once the EEG is on the subject’s head and connected to the OpenBCI GUI software, the subject was placed in a dark room with no sound or other potential distractions. This was done to ensure no outside factors impacted the results gathered through the study. Brown noise was then played for the subject for 4 minutes to gather a baseline measurement by simulating the act of “empty” listening. This was done to ensure that the baseline measurement is not impacted by the action of listening as silence (which would be the alternative listening activity done when gathering this baseline) does not engage the muscles in the ear and the movement of muscles can impact the change in brainwaves shown on the EEG. After the baseline measurement is gathered, the first genre of music is played for 4 minutes, with one song taking up the first two minutes and the second taking up the second. This is done to ensure each genre gets the same amount of time played so the lengths of songs do not impact the changes caused to the subject’s brainwaves.

The first genre is Classical. The first song is “Sonata No. 14 ‘Moonlight’ in C-Sharp Minor” by Beethoven and the second is “Requiem in D Minor” by Mozart

The second genre is Pop. The first song is “Save Your Tears by The Weeknd and the second is “I Want it That Way” by The Backstreet Boys

The third genre is Rock. The first song is “Born to Run” by Bruce Springsteen and the second is “Stairway to Heaven” by Led Zeppelin

The fourth genre is Hip-hop/Rap. The first song is “Devil in a New Dress” by Kanye West and the second is “One Beer” by MF DOOM

The fifth genre is EDM. The first song is “Sacrifice” by Deadmau5 and the second is “Want U 2” by Marshmello

The sixth genre is Jazz. The first song is Blue in Green by Miles Davis and the second is Watermelon Man by Herbie Hancock

The seventh genre is Country. The first song is “I Walk the Line” by Johnny Cash and the second is “Achy Breaky Heart” by Billy Ray Cyrus

After the test is conducted, it is important to clean the EEG to lessen the risk of skin irritation to the next test subject. This is done by removing the electrode holders and the Hydro-link sponges from the EEG. Then, the Hydro-link sponges were washed with tap water four times while the water within them was squeezed out. After washing is done, they were left to airdry. The electrode holders and the BCI cap (EEG body) were then rinsed with tap water and left to airdry and stored with the Hydro-link sponges once dry. The results are measured through the amplitude values as shown in the OpenBCI GUI software. Calculations made to find the average differences in the brainwave’s amplitudes will be calculated with the MATLAB extension within this software. The statistic test used in the study is an ANOVA test. This was done to compare the mean differences between the 7 groups and as ANOVA tests allow means from multiple groups to be compared, it was the clear choice.

Equipment and Materials

The only equipment used for this study was an electroencephalograph and a laptop to read the changes in the subject’s brainwaves in real time. The EEG used openBCI’s software to visually see and record the changes to the subject’s brainwaves and a MATLAB extension within that same software was used to measure the exact difference in brainwave amplitude to lessen the chance of human error in measurement. Spotify was also used to play the music required for the study.

Statistical Test

The null hypothesis is that each mean difference will be the same, and each genre of music will cause the same change to a listener’s brainwaves. The alternative is that they are not equal and will each cause a different change in the brainwaves of subjects. An ANOVA test with a significance level of 0.05 was selected as the means of the different genres per subject were compared. At a significance level of 95%, every test’s p-value (classical, pop, rock, hip-hop/rap, EDM, jazz, and country) was approximately equal to 0.001. Therefore, we reject the null hypothesis in favor of the alternative, suggesting that the genres of music do cause different changes within the brainwaves of subjects.