When listening to music, our brains don’t just sit back and relax. Instead, they get hard to work trying to predict the patterns of the song.

We know from past research that our brains are surprisingly active when we’re listening to music, much more so than would be the case if they were simply processing the sounds. New research shows that the human brain processes music by analyzing what we’ve already heard, and using that to try to predict what’s coming next.

Music to my ears

“The brain is constantly one step ahead and matches expectations to what is about to happen,” said Niels Chr. Hansen, a fellow at the Aarhus Institute of Advanced Studies and one of two lead authors on the paper. “This finding challenges previous assumptions that musical phrases feel finished only after the next phrase has begun.”

“We only know a little about how the brain determines when things start and end. Here, music provides a perfect domain to measure something that is otherwise difficult to measure — namely, uncertainty.”

The study focused on musical phrases, one of the most basic units of music — if notes are treated as equivalent to individual letters, musical phrases would be words that go together. Musical phrases are made up of a sequence of sounds that together form a distinct element within a larger melody. They’re coherent within themselves, meaning that although they are only a part of a larger melody, they do “make sense” so to speak even when played alone.

The team chose this as the basis for their research particularly because of this property. Being coherent by themselves means that our brains can perceive them as music, but they don’t offer any information about what comes after them, because they’re a full sequence in themselves and do not necessarily impact other phrases in the melody, although they can.

What the team wanted to determine was how our brains react to the uncertainty this creates. Our brains like to look for patterns in the world around us (an inclination they developed while trying to keep us alive in the wild). They worked with 38 participants who were asked to listen to Bach chorale melodies, note by note. They were able to pause and restart the music at will by pressing the spacebar on a computer keyboard and were told that they would be tested afterward to check how well they remembered the melodies. This allowed the researchers to use the time participants dwelled on each tone as an indirect measure of their understanding of musical phrasing.

In a second experiment, 31 participants listened to the same musical phrases and were then asked to rate them on how ‘complete’ they sounded. They rated melodies that ended on high-entropy tones (those with higher uncertainty) to be more complete and tended to listen to them more on average.

“We were able to show that people have a tendency to experience high-entropy tones as musical-phrase endings. This is basic research that makes us more aware of how the human brain acquires new knowledge not just from music, but also when it comes to language, movements, or other things that take place over time,” said Haley Kragness, a postdoctoral researcher at the University of Toronto Scarborough and the paper’s second lead author.

“This study shows that humans harness the statistical properties of the world around them not only to predict what is likely to happen next, but also to parse streams of complex, continuous input into smaller, more manageable segments of information,” adds Hansen.

While studying how our brains interpret music might seem trivial, it feeds into the much wider topic of the mechanisms that allow us to perceive and process the world around us. It might also be valuable for researchers seeking to understand the very foundation of communication between people, as this involves an exchange of information in various forms that our brains may or may not try to interpret and understand in the same ways seen in this study’s participants.

The paper “Predictive Uncertainty Underlies Auditory Boundary Perception” has been published in the journal Psychological Science.