Decoding Musical Valence and Arousal: Exploring the Neural Correlates of Music-Evoked Emotions and the Role of Expressivity Features

IF 9.8 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE IEEE Transactions on Affective Computing Pub Date : 2024-11-27 DOI:10.1109/TAFFC.2024.3507192
Alexandre Sayal;Ana Gabriela Guedes;Inês Almeida;Daniela Jardim Pereira;César F. Lima;Renato Panda;Rui Pedro Paiva;Teresa Sousa;Miguel Castelo-Branco;Inês Bernardino;Bruno Direito
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Abstract

Music conveys both basic emotions, like joy and sadness, and complex ones, such as tenderness and nostalgia. Its effects on emotion regulation and reward have attracted much research attention, as the neural correlates of music-evoked emotions may inform neurorehabilitation interventions. Here, we used fMRI to decode and examine the neural correlates of perceived valence and arousal in music excerpts. Twenty participants were scanned while listening to 96 music excerpts, classified beforehand into four categories varying in valence and arousal. Music modulated activity in cortical regions, most noticeably in music-specific subregions of the auditory cortex, thalamus, and regions of the reward network such as the amygdala. Using multivoxel pattern analysis, we created a computational model to decode the perceived valence and arousal of the music excerpts with above-chance accuracy. We further explored associations between musical features and brain activity in valence-, arousal-, reward-, and auditory-related networks. The results emphasize the involvement of distinct musical features, notably expressive features such as vibrato and tonal and spectral dissonance in valence, arousal, and reward brain networks. Using ecologically valid music stimuli, we contribute to delineating the neural correlates of music-evoked emotions with potential implications in the development of novel music-based neurorehabilitation strategies.
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解码音乐效价与觉醒:探索音乐诱发情绪的神经关联及表达性特征的作用
音乐既能传达基本的情感,如喜悦和悲伤,也能传达复杂的情感,如温柔和怀旧。它对情绪调节和奖励的影响引起了许多研究的关注,因为音乐诱发情绪的神经关联可能为神经康复干预提供信息。在这里,我们使用功能磁共振成像来解码和检查音乐节选中感知效价和觉醒的神经相关性。20名参与者在听96段音乐节选时进行了扫描,事先根据效价和兴奋程度将其分为四类。音乐调节了皮层区域的活动,最明显的是听觉皮层、丘脑和奖励网络区域(如杏仁核)的音乐特定亚区。使用多体素模式分析,我们创建了一个计算模型,以高于机会的准确性解码音乐节选的感知价和唤醒。我们进一步探索了音乐特征和大脑活动在价、唤醒、奖励和听觉相关网络之间的联系。结果强调了不同的音乐特征的参与,特别是表达特征,如颤音、音调和频谱的不和谐,在价、唤醒和奖励的大脑网络。利用生态有效的音乐刺激,我们有助于描绘音乐诱发情绪的神经相关性,并在发展新的基于音乐的神经康复策略中具有潜在的意义。
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来源期刊
IEEE Transactions on Affective Computing
IEEE Transactions on Affective Computing COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, CYBERNETICS
CiteScore
15.00
自引率
6.20%
发文量
174
期刊介绍: The IEEE Transactions on Affective Computing is an international and interdisciplinary journal. Its primary goal is to share research findings on the development of systems capable of recognizing, interpreting, and simulating human emotions and related affective phenomena. The journal publishes original research on the underlying principles and theories that explain how and why affective factors shape human-technology interactions. It also focuses on how techniques for sensing and simulating affect can enhance our understanding of human emotions and processes. Additionally, the journal explores the design, implementation, and evaluation of systems that prioritize the consideration of affect in their usability. We also welcome surveys of existing work that provide new perspectives on the historical and future directions of this field.
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