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基因对持续振荡中长程时间相关性的贡献。

Genetic contributions to long-range temporal correlations in ongoing oscillations.

作者信息

Linkenkaer-Hansen Klaus, Smit Dirk J A, Barkil Andre, van Beijsterveldt Toos E M, Brussaard Arjen B, Boomsma Dorret I, van Ooyen Arjen, de Geus Eco J C

机构信息

Department of Experimental Neurophysiology, Institute for Neuroscience, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands.

出版信息

J Neurosci. 2007 Dec 12;27(50):13882-9. doi: 10.1523/JNEUROSCI.3083-07.2007.

Abstract

The amplitude fluctuations of ongoing oscillations in the electroencephalographic (EEG) signal of the human brain show autocorrelations that decay slowly and remain significant at time scales up to tens of seconds. We call these long-range temporal correlations (LRTC). Abnormal LRTC have been observed in several brain pathologies, but it has remained unknown whether genetic factors influence the temporal correlation structure of ongoing oscillations. We recorded the ongoing EEG during eyes-closed rest in 390 monozygotic and dizygotic twins and investigated the temporal structure of ongoing oscillations in the alpha- and beta-frequency bands using detrended fluctuation analysis (DFA). The strength of LRTC was more highly correlated in monozygotic than in dizygotic twins. Statistical analysis attributed up to approximately 60% of the variance in DFA to genetic factors, indicating a high heritability for the temporal structure of amplitude fluctuations in EEG oscillations. Importantly, the DFA and EEG power were uncorrelated. LRTC in ongoing oscillations are robust, heritable, and independent of power, suggesting that LRTC and oscillation power are governed by distinct biophysical mechanisms and serve different functions in the brain. We propose that the DFA method is an important complement to classical spectral analysis in fundamental and clinical research on ongoing oscillations.

摘要

人类大脑脑电图(EEG)信号中持续振荡的幅度波动呈现出自相关性,这种自相关性衰减缓慢,在长达数十秒的时间尺度上仍很显著。我们将这些称为长程时间相关性(LRTC)。在几种脑部病变中已观察到异常的LRTC,但遗传因素是否会影响持续振荡的时间相关结构仍不清楚。我们记录了390对同卵双胞胎和异卵双胞胎闭眼休息时的持续脑电图,并使用去趋势波动分析(DFA)研究了α和β频段持续振荡的时间结构。同卵双胞胎中LRTC的强度比异卵双胞胎的相关性更高。统计分析表明,DFA中高达约60%的方差可归因于遗传因素,这表明脑电图振荡幅度波动的时间结构具有高度遗传性。重要的是,DFA与脑电图功率不相关。持续振荡中的LRTC是稳健的、可遗传的且与功率无关,这表明LRTC和振荡功率受不同的生物物理机制支配,在大脑中发挥不同的功能。我们认为,DFA方法是对持续振荡的基础和临床研究中经典频谱分析的重要补充。

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