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On-line Access: 2014-10-09

Received: 2014-06-06

Revision Accepted: 2014-09-11

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Journal of Zhejiang University SCIENCE C 2014 Vol.15 No.10 P.821-831

http://doi.org/10.1631/jzus.C1400199


Scale-free brain ensemble modulated by phase synchronization


Author(s):  Dan Wu, Chao-yi Li, Jie Liu, Jing Lu, De-zhong Yao

Affiliation(s):  Department of Biomedical Engineering, School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China; more

Corresponding email(s):   wudan@bjtu.edu.cn, dyao@uestc.edu.cn

Key Words:  Brainwave, Ensemble, Music, Scale-free, Synchronization


Dan Wu, Chao-yi Li, Jie Liu, Jing Lu, De-zhong Yao. Scale-free brain ensemble modulated by phase synchronization[J]. Journal of Zhejiang University Science C, 2014, 15(10): 821-831.

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DOI - 10.1631/jzus.C1400199


Abstract: 
To listen to brain activity as a piece of music, we proposed the scale-free brainwave music (SFBM) technology, which could translate the scalp electroencephalogram (EEG) into music notes according to the power law of both EEG and music. In the current study, this methodology was further extended to a musical ensemble of two channels. First, EEG data from two selected channels are translated into musical instrument digital interface (MIDI) sequences, where the EEG parameters modulate the pitch, duration, and volume of each musical note. The phase synchronization index of the two channels is computed by a Hilbert transform. Then the two MIDI sequences are integrated into a chorus according to the phase synchronization index. The EEG with a high synchronization index is represented by more consonant musical intervals, while the low index is expressed by inconsonant musical intervals. The brain ensemble derived from real EEG segments illustrates differences in harmony and pitch distribution during the eyes-closed and eyes-open states. Furthermore, the scale-free phenomena exist in the brainwave ensemble. Therefore, the scale-free brain ensemble modulated by phase synchronization is a new attempt to express the EEG through an auditory and musical way, and it can be used for EEG monitoring and bio-feedback.

基于相位同步的无标度合奏脑音乐

研究目的:将不同状态下的脑电信号转换为音乐进行聆听和分析,该音乐能反映大脑活动本身的无标度性,同时反映不同电极位置信号的相位同步情况。
创新要点:无标度性是脑电信号和音乐都遵循的规律。我们使用了一种满足无标度特征的脑音乐生成方法,将相位同步信息用于调整音乐的协和性,使得到的音乐可以表达不同电极位置信号之间的同步关系。
研究方法:首先,将来自两个不同电极位置的脑电信号分别转换为两段音乐旋律,其中脑电信号的振幅等参数映射为音乐中音符的音高、音长和音量。然后,将这两段音乐合成为一段合奏,为其设定调式。通过计算两道脑电信号之间的相位同步指数,得到音乐的协和性序列。对每个时间点而言,均有两个音同时发出。根据音乐的调式,可确定一个固定的音符,再根据协和性序列,调整另一个音符,从而使音乐的协和性可以表达相位同步指数的变化(图1)。最后,将静息状态下的睁眼和闭眼的EEG数据用于产生音乐(图2,3),显示出在音域、标度指数等方面的差异(图4)。
重要结论:基于相位同步的无标度合奏脑音乐生成方法可以将来自不同电极的脑电信号的特征用音乐的形式进行表达,得到的音乐保留了原始脑电信号的无标度特征(图6,7)。该方法在脑电监测和生物反馈方面有一定的应用潜力。
脑波;脑音乐;合奏音乐;无标度;相位同步

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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