Abstract: Metric structure is the temporal framework of music. It is not only the basis for composers to create music, but also the prerequisite for people to process musical aesthetics, musical emotion and musical meaning. Hence, within the predictive coding framework, the proposed project explores the cognitive and neural mechanisms underlying the prediction and integration of metric structure, using behavioral experiments and electroencephalogram techniques. Specifically, it includes the following four studies: (1) track the dynamic neural activity during the representation construction of metric structure and the prediction establishment as rhythmic sequences unfold, (2) explore how listeners use prediction errors to update the prediction of metric structure, (3) examine the neural mechanisms underlying the integration of multiple hierarchical metric structure at the phrase level and (4) investigate how listeners integrate nested metric structure according to long-distance dependency at the period level. The above research will reveal the general cognitive mechanism of the processing of musical structure and lay the foundation for the construction of cognitive neural model of music. Simultaneously, the results will provide empirical evidence for music appreciation activities and music aesthetics research, which has potential application prospects in the field of music.

Key words: music cognition, literary and artistic psychology, neural mechanisms, metric structure, electroencephalogram