He's one of classical music’s most important composers - and on the eve of his 80th birthday, we got to ask him what he thinks about the state of classical music in 2016.
A new study by Cambridge University has found that taste in music is linked to how a person thinks. People who are more empathetic were found to prefer ‘mellow’ music while those who enjoy analysing rules and patterns preferred ‘intense’ music.
The study was published in the journal PLOS ONE and was led by a PhD student called David Greenberg, who is also a jazz saxophonist.
The researchers asked 4,000 participants to take a psychology-based questionnaire and then, some time later, to listen to and rate 50 pieces of music from a wide range of genres.
People who scored high on empathy were found to prefer mellow music – such as R&B and soft rock, music that was low in energy and music that had emotional depth.
By contrast, people who scored high on systemizing said they preferred intense music, such as punk and heavy metal. They also preferred high-energy music with what the researchers called ‘cerebral depth’.
Four songs likely to appeal to people who scored high on empathy were: Jeff Buckley's 'Hallelujah', Norah Jones's 'Come away with me', Billie Holliday's 'All of me' and Queen's 'Crazy little thing called love'.
According to the researchers, four songs that may well appeal to people who are score highly on systemizing are: Vivaldi's Concerto in C, Scriabin's Etude Opus 65 No.3, The Sex Pistols' 'God save the Queen' and Metallica's 'Enter Sandman.
David Greenberg, who led the study, said: “Although people’s music choices fluctuates over time, we’ve discovered a person’s empathy levels and thinking style predicts what kind of music they like. In fact, their cognitive style – whether they’re strong on empathy or strong on systems – can be a better predictor of what music they like than their personality.”
Greenberg hopes that the research could have an impact on software used by the likes of Spotify and Apple Music.
“A lot of money is put into algorithms to choose what music you may want to listen to,” he said. “By knowing an individual’s thinking style, such services might in future be able to fine tune their music recommendations to an individual.”