ISSN 1671-3710
CN 11-4766/R
主办:中国科学院心理研究所
出版:科学出版社

心理科学进展 ›› 2024, Vol. 32 ›› Issue (10): 1567-1577.doi: 10.3724/SP.J.1042.2024.01567

• 研究构想 •    下一篇

预期视角下音乐节拍结构的认知与神经机制

孙丽君1, 杨玉芳2,3   

  1. 1南京航空航天大学艺术学院, 南京 211106;
    2中国科学院心理研究所行为科学重点实验室, 北京 100101;
    3中国科学院大学心理学系, 北京 100101
  • 收稿日期:2024-04-07 出版日期:2024-10-15 发布日期:2024-08-13
  • 通讯作者: 杨玉芳, E-mail: yangyf@psych.ac.cn
  • 基金资助:
    * 国家自然科学基金青年项目(32300865)、教育部人文社会科学研究青年基金项目(22YJC760086)

The cognitive and neural mechanisms of metric structure in music: A predictive perspective

SUN Lijun1, YANG Yufang2,3   

  1. 1College of Arts, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China;
    2CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China;
    3Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100101, China
  • Received:2024-04-07 Online:2024-10-15 Published:2024-08-13

摘要: 节拍结构作为音乐在时间维度的组织框架, 不仅是作曲家的创作基础, 还是人们欣赏音乐美感、体验音乐情绪以及理解音乐意义的前提。在预期编码理论的框架下, 本文拟围绕节拍结构的预期与整合两方面, 通过行为实验和脑电技术, 探查音乐节拍结构的认知神经基础。具体包括以下4个方面研究:(1)考察在节奏序列展开过程中, 听者构建节拍结构心理表征从而建立预期的动态神经响应; (2)考察听者通过预期错误实现节拍结构预期更新的神经机制; (3)以乐句为结构单元, 考察听者在小时间尺度上整合多层级节拍结构的认知神经机制; (4)在乐段水平上, 考察听者如何依据远距离依存关系整合嵌套节拍结构。以上研究将有利于揭示音乐结构认知的一般机制, 为音乐认知神经模型的构建奠定基础。同时, 相关研究结论还将为音乐鉴赏活动与音乐美学研究提供客观依据, 在音乐学领域具有潜在的应用前景。

关键词: 音乐认知, 文艺心理学, 神经机制, 节拍结构, 脑电图

Abstract: Music is the crystallization of human culture, characterized by its diversity and complexity specific to human society. As an auditory art form, music essentially consists of a structured sequence of sounds unfolding over time. Every musical composition is composed of varying lengths of sounds and rests, with these sound events always combining in alternating patterns, forming the basis for repetition and development. The concept of metric structure refers to the repetitive organization of strong and weak beats within the sequence of sounds. However, due to the complexity of temporal organization in music, metric structure remains a challenging aspect in the study of music cognition. 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.
This study integrates predictive coding theory with the processing of metric structure, exploring how musical structural information is integrated and updated over time within a framework of prediction errors. Forming structured internal representations based on existing information is fundamental and prerequisite for perceiving musical metric structure. Once these structural representations are formed, listeners predict upcoming musical events. Upon the occurrence of a musical event, listeners assess whether it aligns with their predictions, integrate it into their existing musical context, and adjust their structural representations based on whether the expectation was met or violated, thereby enhancing future predictions. Therefore, prediction and integration are two indispensable stages in the brain's processing of metric structure. They are interdependent and mutually influential, reflecting an iterative process of autonomous metric structure processing in the brain. Hence, 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.
This study reveals the general cognitive mechanism of the processing of musical structure and lay the foundation for the construction of cognitive neural model of music. Firstly, based on predictive coding theory, this paper examines the neural responses preceding the occurrence of musical events by focusing on the anticipatory phase. It provides direct neural evidence for the pre-activation stage of expectation formation. Additionally, it distinguishes between the stages of expectation formation and expectation updating, investigating the role of prediction errors in updating metric structure expectations. The study explores how prediction errors regulate the latter stage, revealing the neural mechanisms underlying the updating of metric structure expectations. Secondly, we investigate how listeners integrate nested metric structure within long-duration musical units based on long-distance dependency relationships. It reveals the processing mechanisms of metric structure within complex musical organizations. Thirdly, through the design of musical materials, not only controls for the interference of psychoacoustic factors but also enhances ecological validity in our study.
In summary, within the framework of predictive coding theory, this paper focuses on the processing of metric structure, with four studies forming an integrated whole that collectively addresses the scientific questions regarding the cognitive mechanisms of musical metric structure. A robust theoretical foundation ensures the feasibility of the research. The experimental materials are adapted from real musical works but undergo rigorous manipulation and control, ensuring internal validity and ecological validity of the research outcomes. EEG allows for precise capture of real-time brain responses to each note change during the unfolding of music, making it a feasible and necessary method for exploring the brain mechanisms and dynamic processes involved in processing musical metric structure. This study not only contributes to revealing the nature of music structure cognition and laying the groundwork for constructing neural models of music cognition, but also provides objective evidence for music appreciation and aesthetics research, with promising potential applications in the field of music.

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