Reconfiguration of the brain during aesthetic experience on Chinese calligraphy—Using brain complex networks

IF 3.8 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Visual Informatics Pub Date : 2022-03-01 DOI:10.1016/j.visinf.2022.02.002
Rui Li , Xiaofei Jia , Changle Zhou , Junsong Zhang
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引用次数: 4

Abstract

Chinese calligraphy, as a well-known performing art form, occupies an important role in the intangible cultural heritage of China. Previous studies focused on the psychophysiological benefits of Chinese calligraphy. Little attention has been paid to its aesthetic attributes and effectiveness on the cognitive process. To complement our understanding of Chinese calligraphy, this study investigated the aesthetic experience of Chinese cursive-style calligraphy using brain functional network analysis. Subjects stayed on the coach and rested for several minutes. Then, they were requested to appreciate artwork of cursive-style calligraphy. Results showed that (1) changes in functional connectivity between fronto-occipital, fronto-parietal, bilateral parietal, and central–occipital areas are prominent for calligraphy condition, (2) brain functional network showed an increased normalized cluster coefficient for calligraphy condition in alpha2 and gamma bands. These results demonstrate that the brain functional network undergoes a dynamic reconfiguration during the aesthetic experience of Chinese calligraphy. Providing evidence that the aesthetic experience of Chinese calligraphy has several similarities with western art while retaining its unique characters as an eastern traditional art form.

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中国书法审美体验中的脑重构——利用脑复杂网络
中国书法作为一种著名的表演艺术形式,在中国非物质文化遗产中占有重要地位。以前的研究主要集中在中国书法的心理生理益处上。对其审美属性和对认知过程的影响却鲜有关注。为了补充我们对中国书法的认识,本研究利用脑功能网络分析来研究中国草书书法的审美体验。受试者在马车上休息几分钟。然后,他们被要求欣赏草书风格的书法艺术品。结果表明:(1)书法条件下大脑额枕区、额顶叶区、双侧顶叶区和中枕区功能连通性的变化显著;(2)书法条件下大脑功能网络在α 2和γ波段的归一化聚类系数增加。这些结果表明,在中国书法审美体验过程中,脑功能网络发生了动态重构。提供证据表明,中国书法的审美体验与西方艺术有许多相似之处,同时保留了其作为东方传统艺术形式的独特特征。
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来源期刊
Visual Informatics
Visual Informatics Computer Science-Computer Graphics and Computer-Aided Design
CiteScore
6.70
自引率
3.30%
发文量
33
审稿时长
79 days
期刊最新文献
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