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The brain's favorite type of music

Musical preferences might be rooted in how humans learn

Date:
October 21, 2019
Source:
Society for Neuroscience
Summary:
People prefer songs with only a moderate amount of uncertainty and unpredictability, according to new research.
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People prefer songs with only a moderate amount of uncertainty and unpredictability, according to research recently published in JNeurosci.

Scientists have long struggled to understand why activities of little apparent evolutionary value, like listening to music, bring so much pleasure. Previous studies have linked listening to and making predictions about music with activation in reward centers of the brain but have produced conflicting results on how musical predictions and surprises relate to pleasure.

Gold et al. employed a mathematical model to determine the predictability and uncertainty of musical fragments and then asked listeners to rate how much they liked the songs.

Listeners preferred songs of medium complexity, such as those that counterbalanced uncertain expectations with ultimately predictable musical events. Conversely, songs affording more certain expectations could contain more surprising musical events and still be liked.


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Materials provided by Society for Neuroscience. Note: Content may be edited for style and length.


Journal Reference:

  1. Benjamin P. Gold, Marcus T. Pearce, Ernest Mas-Herrero, Alain Dagher, Robert J. Zatorre. Predictability and uncertainty in the pleasure of music: a reward for learning? The Journal of Neuroscience, 2019; 0428-19 DOI: 10.1523/JNEUROSCI.0428-19.2019

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Society for Neuroscience. "The brain's favorite type of music." ScienceDaily. ScienceDaily, 21 October 2019. <www.sciencedaily.com/releases/2019/10/191021135033.htm>.
Society for Neuroscience. (2019, October 21). The brain's favorite type of music. ScienceDaily. Retrieved March 28, 2024 from www.sciencedaily.com/releases/2019/10/191021135033.htm
Society for Neuroscience. "The brain's favorite type of music." ScienceDaily. www.sciencedaily.com/releases/2019/10/191021135033.htm (accessed March 28, 2024).

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