Sanyal Shankha, Nag Sayan, Banerjee Archi, Sengupta Ranjan, Ghosh Dipak
1Sir C.V. Raman Centre for Physics and Music, Jadavpur University, Kolkata, India.
2Department of Physics, Jadavpur University, Kolkata, India.
Cogn Neurodyn. 2019 Feb;13(1):13-31. doi: 10.1007/s11571-018-9502-4. Epub 2018 Aug 28.
Can we hear the sound of our brain? Is there any technique which can enable us to hear the neuro-electrical impulses originating from the different lobes of brain? The answer to all these questions is YES. In this paper we present a novel method with which we can sonify the electroencephalogram (EEG) data recorded in "control" state as well as under the influence of a simple acoustical stimuli-a tanpura drone. The tanpura has a very simple construction yet the tanpura drone exhibits very complex acoustic features, which is generally used for creation of an ambience during a musical performance. Hence, for this pilot project we chose to study the nonlinear correlations between musical stimulus (tanpura drone as well as music clips) and sonified EEG data. Till date, there have been no study which deals with the direct correlation between a bio-signal and its acoustic counterpart and also tries to see how that correlation varies under the influence of different types of stimuli. This study tries to bridge this gap and looks for a direct correlation between music signal and EEG data using a robust mathematical microscope called Multifractal Detrended Cross Correlation Analysis (MFDXA). For this, we took EEG data of 10 participants in 2 min "control condition" (i.e. with white noise) and in 2 min 'tanpura drone' (musical stimulus) listening condition. The same experimental paradigm was repeated for two emotional music, "Chayanat" and "Darbari Kanada". These are well known Hindustani classical ragas which conventionally portray contrast emotional attributes, also verified from human response data. Next, the EEG signals from different electrodes were sonified and MFDXA technique was used to assess the degree of correlation (or the cross correlation coefficient γ) between the EEG signals and the music clips. The variation of γ for different lobes of brain during the course of the experiment provides interesting new information regarding the extraordinary ability of music stimuli to engage several areas of the brain significantly unlike any other stimuli (which engages specific domains only).
我们能听到大脑的声音吗？有没有什么技术能让我们听到源自大脑不同脑叶的神经电脉冲？所有这些问题的答案都是肯定的。在本文中，我们提出了一种新颖的方法，利用该方法我们可以将在“对照”状态下以及在一种简单声学刺激——坦布拉琴持续低音的影响下记录的脑电图（EEG）数据进行声化处理。坦布拉琴结构非常简单，但坦布拉琴持续低音呈现出非常复杂的声学特征，它通常用于在音乐表演中营造氛围。因此，对于这个试点项目，我们选择研究音乐刺激（坦布拉琴持续低音以及音乐片段）与声化处理后的EEG数据之间的非线性相关性。到目前为止，还没有研究涉及生物信号与其声学对应物之间的直接相关性，也没有尝试去探究这种相关性在不同类型刺激的影响下是如何变化的。本研究试图填补这一空白，并使用一种强大的数学显微镜——多重分形去趋势交叉相关性分析（MFDXA）来寻找音乐信号与EEG数据之间的直接相关性。为此，我们获取了10名参与者在2分钟“对照条件”（即伴有白噪声）下以及在2分钟“坦布拉琴持续低音”（音乐刺激）聆听条件下的EEG数据。对于两首情感音乐《Chayanat》和《Darbari Kanada》，重复了相同的实验范式。这两首是著名的印度斯坦古典拉格，传统上描绘了对比鲜明的情感属性，这也从人类反应数据中得到了验证。接下来，对来自不同电极的EEG信号进行声化处理，并使用MFDXA技术评估EEG信号与音乐片段之间相关性的程度（或交叉相关系数γ）。实验过程中大脑不同脑叶的γ变化提供了有趣的新信息，揭示了音乐刺激与其他任何刺激（其他刺激仅涉及特定区域）不同，具有显著激活大脑多个区域的非凡能力。
