Abstract

Music can be thought of as a dynamic path over time. In most cases, the rhythmic structure of this path, such as specific sequences of strong and weak beats or recurring patterns, allows us to predict what and particularly when sounds are going to happen. Without this ability we would not be able to entrain body movements to music, like we do when we dance. By combining EEG and behavioral measures, the current study provides evidence illustrating the importance of ongoing neural oscillations at beat-related frequencies—i.e., neural entrainment—for tracking and predicting musical rhythms. Participants (13 musicians and 13 non-musicians) listened to drum rhythms that switched from a quadruple rhythm to a 3-over-4 polyrhythm. After a silent period of ~2–3 s, participants had to decide whether a target stimulus was presented on time with the triple beat of the polyrhythm, too early, or too late. Results showed that neural oscillations reflected the rhythmic structure of both the simple quadruple rhythm and the more complex polyrhythm with no differences between musicians and non-musicians. During silent periods, the observation of time-frequency plots and more commonly used frequency spectra analyses suggest that beat-related neural oscillations were more pronounced in musicians compared to non-musicians. Neural oscillations during silent periods are not driven by an external input and therefore are thought to reflect top-down controlled endogenous neural entrainment. The functional relevance of endogenous neural entrainment was demonstrated by a positive correlation between the amplitude of task-relevant neural oscillations during silent periods and the number of correctly identified target stimuli. In sum, our findings add to the evidence supporting the neural resonance theory of pulse and meter. Furthermore, they indicate that beat-related top-down controlled neural oscillations can exist without external stimulation and suggest that those endogenous oscillations are strengthened by musical expertise. Finally, this study shows that the analysis of neural oscillations can be a useful tool to assess how we perceive and process complex auditory stimuli such as polyrhythms.

Highlights

  • Temporal aspects of music—the organization of sounds into patterns and the unfolding of those patterns over time—allow us to predict what and when sounds are likely to occur

  • We found a negative correlation between the amplitude of neural oscillations at triple and quadruple beat frequencies [r(26) = −0.48, p = 0.014], indicating that high amplitudes at triple-beat-related frequencies were associated with low amplitudes at quadruple-beat-related frequencies

  • Computational models, hypotheses and theories suggest that the entrainment of neural oscillations to musical rhythm enables us to disentangle and organize temporal structures and to perceive a steady beat (Large et al, 2015)

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Summary

Introduction

Temporal aspects of music—the organization of sounds into patterns and the unfolding of those patterns over time—allow us to predict what and when sounds are likely to occur next. The question of how we track the temporal structure of music is key for understanding why we love music. Musical rhythms can be defined as acoustic sequences with patterns of duration and accentuation; they represent the structure of music (London, 2004; Large et al, 2015). We can tap our feet or bob our heads in time with music because we are usually able to perceive a regular beat or pulse within a rhythm. If we perceive strong and weak beats, detect regularly recurring events, and use these events to group a fixed number of beats in cycles, we can be said to have found the meter of a musical piece (London, 2004). A quadruple meter encourages us to tap our feet four times (beat-level) in each cycle (bar-level), whereas a triple meter encourages us to tap three times in each cycle

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