Statistical Learning of Chord-Transition Regularities in a Novel Equitempered Scale: An MMN Study

Abstract

In music and language domains, it has been suggested that patterned transitions of sounds can be acquired implicitly through statistical learning. Previous studies have investigated the statistical learning of auditory regularities by recording early neural responses to a sequence of tones presented at high or low transition probabilities. However, it remains unclear whether the statistical learning of musical chord transitions is reflected in endogenous, regularity-dependent components of the event-related potential (ERP). The present study aimed to record the mismatch negativity (MMN) elicited by chord transitions that deviated from newly learned transitional regularities. Chords were generated in a novel 18 equal temperament pitch class scale to avoid interference from the existing tonal representations of the 12 equal temperament pitch class system. Thirty-six adults without professional musical training listened to a sequence of randomly inverted chords in which certain chords were presented with high (standard) or low (deviant) transition probabilities. An irrelevant timbre change detection task was assigned to make them attend to the sequence during the ERP recording. After that, a familiarity test was administered in which the participants were asked to choose the more familiar chord sequence out of two successive sequences. The results showed that deviant transitions elicited the MMN, although the participants could not recognize the standard transition beyond the level of chance. These findings suggest that humans can statistically learn new transitional regularities of chords in a novel musical scale, even though they did not recognize them explicitly. This study provides further evidence that music-syntactic regularities can be acquired implicitly through statistical learning.