Abstract

Music perception is one of the most complex human neurophysiological phenomena invoked by sensory stimuli, which infers an internal representation of the structured events present in a piece of music and then forms long-term echoic memory for the music. An intrinsic relationship between the basic acoustic property (physics) of music and human emotional response (physiology) to the music is suggested, which can be statistically modeled and explained by using a novel notion termed as quantitative physics–physiology relationship (QPPR). Here, we systematically analyzed the complex response profile of people to traditional/ancient music in the Shu area, a geographical concept located in the Southwest China and one of three major origins of the Chinese nation. Chill was utilized as an indicator to characterize the response strength of 18 subjects to an in-house compiled repertoire of 86 music samples, consequently creating a systematic subject-to-sample response (SSTSR) profile consisting of 1,548 (18 × 86) paired chill elements. The multivariate statistical correlation of measured chill values with acoustic features and personal attributes was modeled by using random forest (RF) regression in a supervised manner, which was compared with linear partial least square (PLS) and non-linear support vector machine (SVM). The RF model exhibits possessed strong fitting ability (rF2 = 0.857), good generalization capability (rP2 = 0.712), and out-of-bag (OOB) predictability (rO2 = 0.731) as compared to SVM and, particularly, PLS, suggesting that the RF-based QPPR approach is able to explain and predict the emotional change upon musical arousal. It is imparted that there is an underlying relationship between the acoustic physical property of music and the physiological reaction of the audience listening to the music, in which the rhythm contributes significantly to emotional response relative to timbre and pitch. In addition, individual differences, characterized by personal attributes, is also responsible for the response, in which gender and age are most important.

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