Dingyue Tian, Ziyuan Xu, Han Yan, Bijie Tie, Wen Zhao, Yuanluo Jing, Yazhi Pang, Xiaolin Liu, Jia Zhao, Yong Liu
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引用次数: 0
Abstract
Studies have shown that a cross-modal association between listening to music and eating. This study aims to explore the influence of music style on individuals' food preferences and provide evidence for understanding multi-sensory research. Twenty-seven participants participated in the experiment which consisted of two parts. First, participants completed basic demographic information, followed by a food choice task after exposure to four different music styles: classical, jazz, rap, and rock, with ERP data recorded simultaneously. The behavioral results showed that participants selected more high-calorie foods after exposure to jazz and rock music compared to low-calorie foods. Additionally, during jazz and rock music, participants selected more high-calorie foods, while they favored low-calorie foods during classical music. The ERP results showed that the N1 amplitudes were smallest during the food choice task following the classical music and greatest during the food choice task following the rock music, while the N450 amplitudes were smallest during the food choice task following the jazz music. P2 amplitudes were smallest during the food choice task following the rock music and greatest during the food choice task following the classical music, and P3 amplitudes during the food choice task following jazz music were the greatest. The aforementioned ERP differences were observed irrespective of food choices. However, we did not find a significant interaction between foods (high and low-calorie) and music. Pearson correlation analysis revealed a positive relationship between body satisfaction and P3 amplitudes for classical, jazz, and rock music, with BMI negatively correlated with body satisfaction. This study provides innovative practical perspectives for healthy eating.
期刊介绍:
Brain Topography publishes clinical and basic research on cognitive neuroscience and functional neurophysiology using the full range of imaging techniques including EEG, MEG, fMRI, TMS, diffusion imaging, spectroscopy, intracranial recordings, lesion studies, and related methods. Submissions combining multiple techniques are particularly encouraged, as well as reports of new and innovative methodologies.