不同意识状态对音乐感知的差异性:基于音乐特征与脑电张量分解的研究  

The Difference of Music Processing among Different State of Consciousness:A Study Based on Music Features and EEG Tensor Decomposition

作　　者：梅戬 王小宇[2] 刘杨 李景琦 刘克洪[5] 杨勇[1] 丛丰裕[2] Mei Jian;Wang Xiaoyu;Liu Yang;Li Jingqi;Liu Kehong;Yang Yong;Cong Fengyu(School of Automation,Hangzhou Dianzi University,Hangzhou 310018,China;School of Biomedical Engineering,Dalian University of Technology,Dalian 116024,Liaoning,China;Graduate Office,Zhejiang Conservatory of Music,Hangzhou 310024,China;Department of Nerve Rehabilitation,Hangzhou Mingzhou Naokang Rehabilitation Hospital,Hangzhou 310000,China;Department of Rehabilitation,Hangzhou Hospital of Zhejiang Armed Police Corps,Hangzhou 310051,China)

机构地区：[1]杭州电子科技大学自动化学院,杭州310018 [2]大连理工大学生物医学工程学院,辽宁大连116024 [3]浙江音乐学院研究生院,杭州310024 [4]杭州明州脑康康复医院神经康复科,杭州310000 [5]武警浙江省总队杭州医院康复科,杭州310051

出　　处：《中国生物医学工程学报》2021年第3期257-265,共9页Chinese Journal of Biomedical Engineering

基　　金：国家自然科学基金(81671038)。

摘　　要：研究不同意识水平对音乐感知的差异性,探索不同意识水平与音乐感知之间的关系。被试共43名,其中7名正常意识被试、17名微意识状态(MCS)被试和19名植物状态(VS)被试。获取3种不同意识水平被试在聆听传统民乐《茉莉花》时的脑电,利用基于层次交替最小二乘法(HALS)非负张量分解,对被试在听音乐时产生的脑电提取张量成分,对这些成分做功率谱比率分析和脑地形图分析;在此基础上,对音乐包含的5种信息学特征的EEG响应进行研究,包括中心化波动值(fluctuation centroid)、波动熵(fluctuation entropy)、音阶清晰值(key clarity)、脉冲清晰值(pulse clarity)和调值(mode)。结果表明:1)正常意识被试、MCS被试和VS被试对5种音乐特征的脑电响应在节律上存在显著差异,正常意识被试的alpha波占比高于MCS和VS被试,其中:fluctuation centroid,正常意识被试、MCS被试和VS被试分别为0.687±0.193、0.033±0.022、0.063±0.040(P<0.001);fluctuation entropy,正常意识被试、MCS被试和VS被试分别为0.588±0.132、0.041±0.025、0.085±0.077(P<0.001);key clarity,正常意识被试、MCS被试和VS被试分别为0.668±0.295、0.096±0.103、0.057±0.065(P<0.001);pulse clarity,正常意识被试、MCS被试和VS被试分别为0.672±0.064、0.144±0.242、0.044±0.044(P<0.001);mode,正常意识被试、MCS被试和VS被试分别为0.432±0.273、0.057±0.049、0.033±0.026(P<0.001)。除mode特征外,beta波与alpha波体现相同的统计特征(P<0.05)。2)MCS和VS被试对音乐特征的响应在节律上没有差异,均以delta波和theta波的慢波为主。3)在响应激活区域上,正常意识被试对5种音乐特征的响应主要分布于前额叶,MCS和VS被试的响应主要分布在颞叶。研究表明,不同意识水平对大脑加工音乐特征有影响,这为音乐感知与意识关系探索提供新的模型和研究范式。In this study,we explored the relationship between different levels of consciousness and music processing. We used the EEG data of 43 participants,including 7 normal participants,17 minimally conscious state (MCS) participants and 19 vegetative state (VS) participants. During the experiment,participants were requested to listen to the traditional folk music "Jasmine". We extracted tensor components from the EEG by using hierarchical alternating least squares (HALS) non-negative tensor decomposition. After that,we selected components correlated with the five music informatic features (fluctuation centroid,fluctuation entropy,key clarity,pulse clarity and mode) respectively. Then power spectrum ratio analysis and brain topography analysis were applied to the components selected to study the EEG response. The results showed that: 1) differences existed in the proportion of alpha waves of the EEG response to the 5 music features among the normal group,the MCS group and the VS group: fluctuation centroid (normal group 0. 687 ± 0. 193,MCS group 0. 033 ±0. 022,VS group 0. 063 ± 0. 040,P < 0. 001),fluctuation entropy (normal group 0. 588 ± 0. 132,MCS group 0. 041±0. 025,VS group 0. 085 ± 0. 077,P < 0. 001),key clarity (normal group 0. 668 ± 0. 295,MCS group0. 096±0. 103,VS group 0. 057±0. 065,P<0. 001),pulse clarity (normal group 0. 672±0. 064,MCS group0. 144±0. 242,VS group 0. 044±0. 044,P<0. 001),mode (normal group 0. 432±0. 273,MCS group 0. 057±0. 049,VS group 0. 033±0. 026,P<0. 001). Except feature mode,beta wave of the EEG response to the rest 4 music features have the same statistical results as alpha wave (P < 0. 05). 2) The rhythm of the response of MCS group and VS group to the 5 music features was mainly the slow wave of delta wave and theta wave. 3) As for the EEG activation area,the normal group EEG response to the 5 music features mainly distributed in frontal lobe but the MCS and VS group EEG response mainly in parietal lobe. The results showed that the level of consciousness had effects on b

关 键 词：脑电信号 音乐感知 张量分解 意识水平 

分 类 号：R318[医药卫生—生物医学工程]