Suppr超能文献

大脑、音乐与非泊松更新过程。

Brain, music, and non-Poisson renewal processes.

作者信息

Bianco Simone, Ignaccolo Massimiliano, Rider Mark S, Ross Mary J, Winsor Phil, Grigolini Paolo

机构信息

Center for Nonlinear Science, University of North Texas, P.O. Box 311427, Denton, Texas 76203-1427, USA.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2007 Jun;75(6 Pt 1):061911. doi: 10.1103/PhysRevE.75.061911. Epub 2007 Jun 21.

Abstract

In this paper we show that both music composition and brain function, as revealed by the electroencephalogram (EEG) analysis, are renewal non-Poisson processes living in the nonergodic dominion. To reach this important conclusion we process the data with the minimum spanning tree method, so as to detect significant events, thereby building a sequence of times, which is the time series to analyze. Then we show that in both cases, EEG and music composition, these significant events are the signature of a non-Poisson renewal process. This conclusion is reached using a technique of statistical analysis recently developed by our group, the aging experiment (AE). First, we find that in both cases the distances between two consecutive events are described by nonexponential histograms, thereby proving the non-Poisson nature of these processes. The corresponding survival probabilities Psi(t) are well fitted by stretched exponentials [Psi(t) proportional, variant exp (-(gammat){alpha}) , with 0.5<alpha<1 .] The second step rests on the adoption of AE, which shows that these are renewal processes. We show that the stretched exponential, due to its renewal character, is the emerging tip of an iceberg, whose underwater part has slow tails with an inverse power law structure with power index mu=1+alpha. Adopting the AE procedure we find that both EEG and music composition yield mu<2. On the basis of the recently discovered complexity matching effect, according to which a complex system S with mu{S}<2 responds only to a complex driving signal P with mu{P}< or =mu{S}, we conclude that the results of our analysis may explain the influence of music on the human brain.

摘要

在本文中,我们表明,通过脑电图(EEG)分析揭示的音乐创作和大脑功能都是存在于非遍历领域的更新非泊松过程。为了得出这一重要结论,我们使用最小生成树方法处理数据,以检测重大事件,从而构建一个时间序列,即用于分析的时间序列。然后我们表明,在脑电图和音乐创作这两种情况下,这些重大事件都是非泊松更新过程的特征。这一结论是使用我们团队最近开发的一种统计分析技术——老化实验(AE)得出的。首先,我们发现在这两种情况下,两个连续事件之间的距离都由非指数直方图描述,从而证明了这些过程的非泊松性质。相应的生存概率Psi(t) 能很好地用拉伸指数拟合 [Psi(t) 成正比,变量 exp (-(γt)^α),其中 0.5 < α < 1 。] 第二步基于采用老化实验,该实验表明这些是更新过程。我们表明,由于其更新特性,拉伸指数是冰山露出水面的一角,其水下部分具有幂指数为 mu = 1 + α 的逆幂律结构的慢尾。采用老化实验程序,我们发现脑电图和音乐创作的 mu 均小于 2。基于最近发现的复杂性匹配效应,即具有 mu{S} < 2 的复杂系统 S 仅对具有 mu{P} ≤ mu{S} 的复杂驱动信号 P 做出响应,我们得出结论,我们的分析结果可能解释了音乐对人类大脑的影响。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验