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首页> 外文期刊>Physica, A. Statistical mechanics and its applications >Study on Brain Dynamics by Non Linear Analysis of Music Induced EEG Signals
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Study on Brain Dynamics by Non Linear Analysis of Music Induced EEG Signals

机译：通过音乐诱发的脑电信号的非线性分析研究脑动力学

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Music has been proven to be a valuable tool for the understanding of human cognition, human emotion, and their underlying brain mechanisms. The objective of this study is to analyze the effect of Hindustani music on brain activity during normal relaxing conditions using electroencephalography (EEG). Ten male healthy subjects without special musical education participated in the study. EEG signals were acquired at the frontal (F3/F4) lobes of the brain while listening to music at three experimental conditions (rest, with music and without music). Frequency analysis was done for the alpha, theta and gamma brain rhythms. The finding shows that arousal based activities were enhanced while listening to Hindustani music of contrasting emotions (romantic/sorrow) for all the subjects in case of alpha frequency bands while no significant changes were observed in gamma and theta frequency ranges. It has been observed that when the music stimulus is removed, arousal activities as evident from alpha brain rhythms remain for some time, showing residual arousal. This is analogous to the conventional 'Hysteresis' loop where the system retains some 'memory' of the former state. This is corroborated in the non linear analysis (Detrended Fluctuation Analysis) of the alpha rhythms as manifested in values of fractal dimension. After an input of music conveying contrast emotions, withdrawal of music shows more retention as evidenced by the values of fractal dimension. (C) 2015 Elsevier B.V. All rights reserved.
机译：音乐已被证明是理解人类认知，人类情感及其潜在大脑机制的宝贵工具。这项研究的目的是使用脑电图（EEG）分析印度斯坦音乐对正常放松条件下大脑活动的影响。十名未经特殊音乐教育的男性健康受试者参加了这项研究。在三个实验条件下（静息，有音乐和无音乐）听音乐时，在大脑的额叶（F3 / F4）采集到EEG信号。对α，θ和γ脑节律进行了频率分析。该发现表明，在阿尔法频段的情况下，听所有对象的对比情绪（浪漫/悲伤）的印度斯坦尼音乐时，基于唤醒的活动得到了增强，而在γ和theta频率范围内未观察到明显变化。已经观察到，当去除音乐刺激时，从阿尔法脑节律明显可见的唤醒活动保持了一段时间，显示出残留的唤醒。这类似于常规的“滞后”循环，在该循环中，系统保留了先前状态的某些“内存”。分形维数值表明，这在阿尔法节奏的非线性分析（去趋势波动分析）中得到了证实。输入音乐传达对比情绪后，撤消音乐表现出更多的保留力，这由分形维数的值证明。 （C）2015 Elsevier B.V.保留所有权利。

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