The songs our brains love most follow a science-backed recipe

Charles Darwin, a man famous for his attempts to figure out how we came to be the way we are, understood that music is important to humankind and that it would serve him well to listen to more of it. What Darwin couldn’t quite put his finger on was what use music has — why it creates such a pleasurable feeling even though its adaptive benefits aren’t as clear as say, eating or making friends.

In a study released Monday in the Journal of Neuroscience, a team of neuroscience researchers offer an answer, joining a long line of scientists who’ve strived to explain why the brain responds positively to music. They posit that the songs people enjoy most are those of “intermediate complexity” — in other words, tunes that balance uncertain expectations with ultimately predictable events. We want our songs to be interesting, but we still want them to be a bit like what we’ve heard before.

The team, which represents the Montreal Neurological Institute, Queen Mary University of London, and McGill University, argues that we enjoy that particular musical recipe because it zeros in on the human brain’s intrinsic desire to learn. The process of learning involves updating inaccurate predictions and validating accurate ones. When we learn something, our brain releases dopamine, which makes us feel good and be motivated to learn again.

The idea here is that, when songs contain an “intermediate degree of predictability,” they capture our brain’s attention and curiosity — while still allowing us to accurately predict certain components. When music manipulates patterns of melody and rhythm, it exploits our expectations. However, when we can accurately anticipate what’s going to happen, the brain gives us a boost of dopamine because we’ve evolved to be rewarded when we get things right. Previous studies have shown that when a person enjoys music, their nucleus accumbens becomes activated — which is a central node in the brain’s reward system.

Meanwhile, a completely predictable song couldn’t cause the same effect because it offers us no new information to become interested in. At the same time, the researchers write, “unforeseeable, seemingly random surprises are equally unhelpful because they’re indecipherable.”

To get to the bottom of this, the researchers conducted a study in two parts. In the first, 43 volunteers were asked to listen to 55 clips of Western folk and classical music and rate how much they enjoyed the songs (the study excluded the volunteers who were into music that tends to lacks predictability, like jazz).

These clips were also evaluated by a statistical modeling algorithm known as Information Dynamics of Music, or IDyOM. IDyOM was trained to determine how unexpected musical fragments within these songs were, as well as how easy it was to predict what notes would come next.

The second study was designed the same way as the first in an effort to confirm its findings, save for the fact that, this time, there were 27 participants and 12 clips of music.

Consistently, the team found that people enjoyed a mix of uncertain expectations and moments of predictability in their music. There was a certain scale to this — songs could contain very surprising moments and still be enjoyed, but those had to be balanced with even more moments of musical predictability.

“Together,” the researchers write, “these findings support long-hypothesized optimal zones of predictability and uncertainty in musical pleasure with formal modeling, relating the pleasure of music listening to the intrinsic reward of learning.”

This study confirms previous research on pleasurable music’s balance of complexity and knowability, sometimes known as the “Wundt curve,” and links our experience of enjoying the pleasure of music to our very human need to seek out information and learn. It’s established that few things stimulate our brains, and unite our brains, quite like music. When we listen to music, we take part in a ritual of encoding — and we’re eager to know the song.

Abstract:

Music ranks among the greatest human pleasures. It consistently engages the reward system, and converging evidence implies it exploits predictions to do so. Both prediction confirmations and errors are essential for understanding one’s environment, and music offers many of each as it manipulates interacting patterns across multiple timescales. Learning models suggest that a balance of these outcomes, i.e., intermediate complexity, optimizes the reduction of uncertainty to rewarding and pleasurable effect. Yet evidence of a similar pattern in music is mixed, hampered by arbitrary measures of complexity. In the present studies, we applied a well-validated information-theoretic model of auditory expectation to systematically measure two key aspects of musical complexity: predictability (operationalized as information content, IC), and uncertainty (entropy). In Study 1, we evaluated how these properties affect musical preferences in 43 male and female participants; in Study 2, we replicated Study 1 in an independent sample of 27 people and assessed the contribution of veridical predictability by presenting the same stimuli seven times. Both studies revealed significant quadratic effects of IC and entropy on liking that outperformed linear effects, indicating reliable preferences for music of intermediate complexity. An interaction between IC and entropy further suggested preferences for more predictability during more uncertain contexts, which would facilitate uncertainty reduction. Repeating stimuli decreased liking ratings but did not disrupt the preference for intermediate complexity. Together, these findings support long-hypothesized optimal zones of predictability and uncertainty in musical pleasure with formal modeling, relating the pleasure of music listening to the intrinsic reward of learning.