On February 2, the D’Or Institute for Research and Education published a study in Scientific Reports which claims they have found a way to identify what song people are listening to with phenomenal accuracy through the use of human brain scans.

With the help of a magnetic resonance machine and “brain decoding”, a technique that studies brain responses when exposed to various stimuli, the study showed six participants to 40 pieces of pop, rock, jazz and classical music to see if their code could match their brain responses with each song's features: such as tonality, dynamics, rhythm, and timbre.

Reading the participants brain patterns, the computer was able to identify the the “neural fingerprint” of each song with up to 85 per cent accuracy. This is not the first time this type of study has been conducted, but this most recent experiment has set a new standard for accuracy in the field of neural decoding. Sebastian Hoefle, a researcher from the D’Or Institute, hopes that the study will lead to new possibilities of communication and eventually believes that “machines will be able to translate our musical thoughts into songs.”

In addition to providing insight in regards to how our brains function, Hoefle hopes that studies such as this will help us answer the questions: “What musical features make some people love a song while others don't? Is our brain adapted to prefer a specific kind of music?"

|via EurekaAlert!|



Cameron is Mixmag's US Editorial Intern. Follow him on Twitter here