Waking and sleeping states in the rat from an EEG data analysis point of view.

Waking and sleeping Pub Date : 1980-01-01
P Etevenon, F Giannella
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Abstract

This article presents the characteristics of ECoGs of arousal, slow wave sleep and paradoxical sleep in the rat, in terms of analysis of data. In a first part, we have applied four different methods of analysis to the three tracings: the instantaneous amplitude histograms computation, the integrative method of Drohocki, the spectral analysis and the normalized slope descriptor method of Hjorth. Each method provides, after data reduction, characteristic parameters of the tracings. A graph which displays peak spectral frequency versus mean integrated value is enough to discriminate between the 3 quantified tracings. Multivariate discriminant analysis reveals that 3 coefficients altogether allow a good discrimination. In the second part we ask the question: which kind of signal is the paradoxical sleep tracing? After the impossibility to choose between a narrow-band Gaussian process or a sinusoidal wave burried in noise, we propose a third kind of signal found after modulation analysis. This signal is modulated both in amplitude and frequency around a carrier frequency beeing the dominant theta rhythm.

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从脑电图数据分析的角度看大鼠的清醒和睡眠状态。
本文从数据分析的角度介绍了大鼠觉醒、慢波睡眠和矛盾睡眠的脑电图特征。在第一部分中,我们应用了四种不同的分析方法来分析三种跟踪:瞬时振幅直方图计算,Drohocki的综合方法,频谱分析和Hjorth的归一化斜率描述符方法。每种方法都提供了经过数据约简后的跟踪特征参数。显示峰值频谱频率与平均积分值的图表足以区分3种量化跟踪。多元判别分析表明,3个系数合在一起具有较好的判别性。在第二部分,我们提出了一个问题:这种矛盾的睡眠追踪是哪种信号?在无法选择窄带高斯过程还是杂波正弦波之后,我们提出了经过调制分析发现的第三种信号。这个信号在幅度和频率上都被调制,围绕一个载波频率作为主导的θ节奏。
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