Music and Emotions: The Effects of Commercially Available and Computer-Generated Music on Brain Activity

The use of background music while completing mentally stimulating tasks has recently gained popularity. What gives music its potential to improve learning outcomes has to do with characteristics like tempo and tone.

This research investigated the changes in EEG signals under numerous experimental conditions: silence, 3 ascending tempos of commercially available music, and 3 ascending tempos of computer-generated music with two different genres: classic and modern. The order in which music was played was randomized for each participant. The first three trials used commercially available classical music across 3 tempos: slow, moderate, and fast. The other six trials used computer-generated music to test each of the following modern and classic music genres: calm, stimulus, and focus.

During testing, brainwave activity and heart rate were measured by the means of electroencephalography (EEG) and electrocardiography (ECG) respectively. The Muse 2 headband from InteraXon was used to measure alpha, beta, theta, delta, and gamma waves using four different channels. The E4 Empatica wristband measured heart rate throughout the different music tests as a parameter to indicate if spikes in brain activity can have a direct effect on heart rate.

The results indicated that different types of commercially available music had an overall higher power spectral density than that of computer-generated music. This suggests that brain activity was stronger when listening to commercially available music. With the computer-generated music, all the Muse 2 channels were synchronized with one another in terms of brain activity. This indicates that computer-generated music has the effect of causing identical activity in terms of power spectral density, while showing spikes at frequencies in the front and back areas of the right and left hemispheres of the brain. The testing of computer-generated music was used to examine the frequencies to see if the music piece evokes the intended emotion.

Slide 1: Hi, my name is Omar Alsuhaibani and today I will be presenting my URSP research, Music and Emotions: The Effects of Commercially-Available and Computer-Generated Music on Brain Activity.

Slide 2: Music is almost everywhere, from shopping malls to elevators and ice cream trucks, that it has essentially embedded itself in the human genome. What gives music its potential to improve learning outcomes has to do with characteristics like tempo and tone. The use of background music while completing mentally stimulating tasks, such as homework, has recently gained popularity. This research aims to examine the effects that computer-generated and commercially available music has on human brain activity and heart rate, and to see if they relate and differ by analyzing the power of different types of brainwaves that indicate the different types of activity. The objective of this research is to identify if computer-generated music that is intended to evoke certain emotions truly achieves that effect by examining physiological signals, such as brainwave activity and heart rate, and comparing it to commercially available music with similar levels of tempos.

Slide 3: To gain a better understanding of the effects of computer-generated music in comparison to commercially available music, this study investigated the changes in EEG signals under numerous experimental conditions: silence, 3 ascending tempos of commercially available music, and 3 ascending tempos of computer-generated music with two different genres: classic and modern. Participants were recruited for an experiment that exposed them to 9 pieces of music for a duration of 56 minutes. The order in which the music played was randomized for each participant. Three of the music pieces were commercially available classic music with slow, moderate, and fast tempos. The other six were different types of computer-generated music, known as classic calm, classic stimulus, classic focus, modern calm, modern stimulus, and modern focus. Each computer-generated music piece was meant to evoke a certain emotion within participants such as calmness, stimulus, and concentration (e.g. calmness when listening to calm music, concentration when listening to focus music). Differences among conditions will be observed through brainwave activity, which was measured by the means of electroencephalography (EEG) using a Muse 2 Headband, and heart rate, measured by the means of electrocardiography (ECG) using the E4 Empatica wristband. The Muse 2 headband from InteraXon was used to measure alpha, beta, theta, delta, and gamma waves. By extracting the data from the Muse 2 headband, the muse monitor app is used to import it into EEGLAB for analyzation. The visualization of this data may be conceived through a spectral density graph which aids in understanding the measured activity across areas (the sulcus and the gyrus) at the right and left hemispheres of the brain. The E4 Empatica wristband measured heart rate throughout the different music pieces as a parameter to indicate if spikes in brain activity can have a direct effect on heart rate. The changes of the music styles and tempos allowed us to determine its influences on physiological modulation. Studies have also shown that music with slow and steady rhythms reduce stress by changing body rhythms like heart rate (Witte et, al.).

Slide 4: We can see here the results with a baseline test of the typical brain activity, a commercially available slow tempo music piece (also known ad adagio), and a computer-generated modern focus music piece. The results indicated that different types of commercially available music had an overall higher power spectral density than that of computer-generated music. This suggests that brain activity was stronger when listening to commercially available music. With the computer-generated music, all the Muse 2 channels were synchronized with one another in terms of brain activity. This indicates that computer-generated music has the effect of causing identical activity in terms of power spectral density, while showing spikes at frequencies in the front and back areas of the right and left hemispheres of the brain. The testing of computer-generated music was used to examine the frequencies to see if the music piece evokes the intended emotion.

Slide 5: The future implication of computer-generated music poses great potential in music therapy development by analyzing how the mind, emotions, and physiological signals can react towards different types of simulations. For upcoming plans for the future, we will be recruiting more students for testing to gather more data. In addition, we will try to gain more understanding on brainwave activity and what certain values in terms of spectral density and frequency can indicate particular emotions. We will also begin to write a paper to be published.