Neurologist strikes a chord with what makes a hit

15 January 2020

Luis Fonsi and Daddy Yangkee’s 2017 hit song Despacito (Despacito quiero respirar tu cuello despacito) was YouTube’s most streamed music video of the last decade, with over 6.5 billion views. What’s so captivating about this Latino music that it topped the Billboard chart for a record-equalling 16 weeks?

Research led by neurologist Vincent Cheung (Croucher Scholarship 2015), a Hong Kong PhD student at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig, Germany, suggests that the reason involves the right combination of uncertainty and surprise.

When we hear a song for the first time, our brain automatically makes predictions about what sound will come next, based on music we have heard in the past. We experience pleasure when our expectations are sometimes met, but not all the time.

Composers and songwriters seem to have known this for centuries. So at what point is music pleasurable? And what mechanism in the brain is involved?

To answer these questions, Cheung and his team examined listeners’ brain activity using functional magnetic resonance imaging (fMRI) and machine learning. The outcomes have been published in Current Biology.

A statistical-learning model was trained to quantify the expectancy of 80,000 chords from famous American Billboard hits.

This allowed the team to determine whether pleasantness could be predicted by the uncertainty concerning the upcoming chord or the surprise experienced upon hearing it. To rule out factors such as memories associated with particular songs, the chords were stripped of other aspects of the original material, such as their lyrics and melody. The chord progressions remained the same but were no longer recognisable.

The team found two distinct patterns associated with chord pleasantness: those with low uncertainty and high surprise, or the opposite, highly uncertain but not surprising.

The uncertainty of an upcoming chord was assumed to be predictable from the music structure and distinct from the actual reaction to the chord. If the participant was sure what was coming next (low uncertainty) but the song unexpectedly deviated and surprised them, they found that pleasant. However, if the chord progression was harder to predict (high uncertainty) but the actual chord that arrived did not surprise them, they also found the stimuli pleasant, possibly suggesting they had guessed correctly.

“In other words, what is crucial is the dynamic interplay between two temporally dissociable aspects of expectations: the anticipation beforehand, and the surprise afterwards,” Cheung said.

Using fMRI, the team found that the interactive effect between the uncertainty of the upcoming chord and its level of surprise was associated with brain activity changes in emotion and auditory-related areas. Importantly, activity of the nucleus accumbens was associated only with the level of uncertainty. This reward-related brain region is thought to play a central role in musical pleasure.

This suggests that the nucleus accumbens might not be driving the experience of pleasure per se, and its role in music-evoked emotions may be more nuanced than previously thought.

“This is intriguing because it means that the actual experience of pleasure is elicited elsewhere, and its role may instead be to direct the listener towards the music to find out what will happen next - just as cliff-hangers in TV shows keep us hooked on wanting to find out how the story will unfold in the next episode,” Cheung said.

This research could have direct relevance for the music industry. “On one hand, our results could be applied to assist composers or even computers in writing music. On the other, algorithms could be developed to predict musical trends and how well a song would do based on its structure. The possibilities are endless,” he added.

“Our next step would be to look at how information flows across different parts of the brain over time, and perhaps why we sometimes get goosebumps when we listen to music.”

Vincent Cheung is a PhD student at the International Max Planck Research School on Neuroscience of Communication at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig, Germany. He completed his master’s degree in computational neuroscience at the Bernstein Center for Computational Neuroscience (BCCN), Berlin, Germany, and undergraduate master’s degree in mathematics at the University of Warwick, UK. Vincent received his Croucher Scholarship in 2015.

To view Vincent Cheung’s Croucher profile, please click here.