音乐增强大脑网络小世界特性

发布时间：2018-06-22 20:22

本文选题：音乐 + 脑电信号　；参考：《复旦学报(自然科学版)》2017年06期

【摘要】：近年来实验发现音乐相比其他机械噪声对人脑感知系统更能增强大脑内部复杂网络特性.优美音乐在频谱上普遍具有1/f统计特征.在音乐增强脑电信号记录分析中,我们发现对比具有1/f特征的音乐信号,在仍保留1/f特征的随机乱乐刺激下,大部分脑皮层区域的脑功能网络连接密度普遍下降,并且增强的脑功能网络小世界特性在一定阈值范围内也会有显著下降.随机打乱的音乐虽然仍保留长程相关特征,但打乱后每分钟节拍数和节拍清晰度出现了明显降低.这两种音乐特性的降低与音乐打乱前后的大脑小世界网络统计指标的CMean/LMean降低有显著关联.说明音乐信号除了1/f长程相关统计特征之外的其他有效音乐信息在增强脑功能网络方面也起到重要作用.
[Abstract]:In recent years, it has been found that music can enhance the complex network characteristics of the brain more than other mechanical noise. Beautiful music generally has a 1 / F statistical feature on the spectrum. In music enhanced EEG recording and analysis, we found that compared with music signals with a 1 / f feature, the density of functional network connections in most cortical regions generally decreased under random stimuli that still retain the 1 / f feature. And the enhanced small-world characteristics of brain functional networks also decrease significantly within a certain threshold range. Although the randomly disturbed music still retains the characteristics of long range correlation, the number of beats per minute and the clarity of the beat were significantly decreased after the disturbance. The decrease in these two musical characteristics was significantly associated with the decrease of Cmean / LMean, a statistical measure of the small world network of the brain before and after musical disruption. The results show that other effective musical information, besides the statistical features of 1 / f long range correlation, also play an important role in enhancing the brain function network.
【作者单位】：复旦大学生命科学学院生理学和生物物理学系脑科学协同创新中心;复旦大学计算系统生物学中心;
【基金】：国家自然科学基金(31571070) 国家高级术研究发展计划(2015AA020508) 上海市“东方学者”和国家癫痫精准医学(2016YFC0904400)项目
【分类号】：J60-05;Q42

【相似文献】