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基于脑电信号溯源分析的音乐类型对学习记忆影响的研究
引用本文:李继鹏,李颖,张东颖,冯浩,尹宁. 基于脑电信号溯源分析的音乐类型对学习记忆影响的研究[J]. 中国生物医学工程学报, 2019, 38(6): 679-686. DOI: 10.3969/j.issn.0258-8021.2019.06.005
作者姓名:李继鹏  李颖  张东颖  冯浩  尹宁
作者单位:1(河北工业大学省部共建电工装备可靠性与智能化国家重点实验室,天津 300130)2(河北工业大学河北省电磁场与电器可靠性重点实验室,天津 300130)
基金项目:国家自然科学基金(51707055);河北省自然科学基金(E2016202155);河北省高等学校自然科学基金(QN2016097)
摘    要:音乐在日常生活中充当着重要的角色,它对学习认知活动的影响受到越来越多学者的重视。在无音乐、古典音乐、摇滚音乐等3种背景音乐下,对20名被试记忆单词的脑电实验,采用sLORETA溯源方法对脑电数据进行分析,并采用统计非参数映射方法(SnPM)对3种溯源结果进行两两对比分析。结果发现,不同音乐类型下的事件相关电位(ERP)源主要分布在额叶和颞叶。其中,无音乐状态下P300溯源结果主要分布在额叶和左侧大脑的颞叶部分,古典音乐和摇滚音乐状态下P300溯源结果主要分布在额叶和右侧大脑的颞叶部分。对溯源结果进行统计分析,发现不同音乐类型下的ERP源电流密度两两之间均有显著性差异(P<0.05),其中:无音乐和古典音乐两种情形相比,差异主要集中在颞叶;无音乐和摇滚音乐两种情形相比,差异主要集中在颞叶和额叶;古典音乐和摇滚音乐两种情形相比,差异主要集中在额叶和部分枕叶。对行为学数据进行统计分析发现,无音乐状态下被试记忆单词的正确率均值约为91.00%±0.64%,古典音乐状态下约为86.00%±0.45%,摇滚音乐状态下约为80.00%±0.24%。研究结果表明,音乐对大脑产生的刺激,可能会减少大脑用于当前认知加工过程时的资源,降低学习记忆的效率。

关 键 词:脑电信号溯源  背景音乐  工作记忆  标准化低分辨率脑电磁层析成像算法(sLORETA)  事件相关电位(ERP)  
收稿时间:2018-10-08

Research on the Influence of Music Type on Learning and Memory Based on EEG Signal Source Tracing Analysis
Li Jipeng,Li Ying,Zhang Dongying,Feng Hao,Yin Ning. Research on the Influence of Music Type on Learning and Memory Based on EEG Signal Source Tracing Analysis[J]. Chinese Journal of Biomedical Engineering, 2019, 38(6): 679-686. DOI: 10.3969/j.issn.0258-8021.2019.06.005
Authors:Li Jipeng  Li Ying  Zhang Dongying  Feng Hao  Yin Ning
Affiliation:(State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China)(Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, Hebei University of Technology, Tianjin 300130, China)
Abstract:Music plays an important role in our daily life, and more and more scholars pay attention to the influence of music on learning cognitive activities. In this paper, 20 subjects in the EEG experiment for memorizing English words under three music conditions (non-music, classical music and rock music) was enrolled, and standardized low resolution brain electromagnetic tomography algorithm (sLORETA) was applied to reconstruct the sources, and statistical nonparametric mapping method (SnPM) was used to make pairwise comparison analysis of source localization results under three conditions. The localization analyses of EEG signals showed that ERP sources under different music types were mainly distributed in frontal lobes and temporal lobes. The localization results of P300 under non-music condition were mainly distributed in frontal lobe and left temporal lobes, and the localization results of P300 under classical music and rock music were mainly distributed in frontal lobe and right temporal lobe. Statistical analysis of the reconstruction results showed that there were significant differences between the ERP source current densities under different music types (P<0.05). The differences between non-music condition and classical music condition were mainly concentrated in temporal lobe. The differences between non-music condition and rock music condition were mainly concentrated in temporal lobe and frontal lobe. The differences between classical music condition and rock music condition were mainly concentrated in frontal lobe and occipital lobe. Statistical analysis of the behavioral data showed that the correct response rates of the subjects for memorizing words under non-music condition was about 91.00%±0.64%, that of classical music was about 86.00%±0.45%, and that of rock music was about 80.00%±0.24%. The results suggest that music may stimulate the brain, and it may waste the resources of the brain for the current cognitive processing and reduce the efficiency of learning and memory.
Keywords:EEG source localization  background music  working memory  standardized low resolution brain electromagnetic tomography algorithm(sLORETA)  event related potential(ERP)  
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