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[视觉信息处理中的脑电图活动模式:特征、方差分析界定、不可或缺变量的判别分析确定及量表水平]

[EEG-activity patterns in visual information processing: characteristics, variance-analytical deliminiation, discriminance-analytical determination of undispensable variables and scale level].

作者信息

Otto E, Bräuer D, Wilhelm M

出版信息

Acta Biol Med Ger. 1979;38(4):571-86.

PMID:525137
Abstract
  1. In order to determine the variable distributions of 5 activation dependent EEG activity patterns occurring during visual information processing, mean values and standard deviations of the percental quantities of the frequencies 4, 5, ..., 13 Hz, 14 to 20 Hz and 21 to 30 Hz, as well as the mean amplitudes in the frequency bands 3.5 ... 7.4 Hz, 7.5 ... 13.4 Hz and 13.5 to 30 Hz were determined on corresponding to 10 s samples. It could be demonstrated by regression analysis that an interval scale level can be assumed already on the basis of cethe percental quantities in the three last mentioned frequency bands. 2. On the basis of 18 relevant variables, all the adjacent activity patterns could be separated from each other by means of univariate variance analysis at pairwise mean value comparison by at least two variables. 3. After stepwise reduction of dispensable variables in the framework of a linear discriminance analysis an optimal set of variables was determined, comprising the percental quantities of the frequencies 4, 5, 6, 10, 12 Hz, and 14 to 20 Hz, as well as the mean value of the amplitudes in the frequency band 3.5 to 7.4 Hz. In 4 our of 5 elementary discriminance functions, the mean values calculated for each pattern were significantly distinguishable from each other (analysis of variance, Newman-Keuls test). 4. By linear regression analysis it could be shown that the classification system of the EEG activity patterns at visual information processing can be mapped on an interval scale after the reduction of variables, too. Finally, data about the reliability of the scoring procedure are presented.
摘要
  1. 为了确定视觉信息处理过程中出现的5种激活依赖型脑电图活动模式的变量分布,在对应10秒的样本上,测定了4、5、…、13赫兹、14至20赫兹以及21至30赫兹频率的百分比量的平均值和标准差,以及3.5…7.4赫兹、7.5…13.4赫兹和13.5至30赫兹频段的平均振幅。通过回归分析可以证明,仅根据最后提到的三个频段中的百分比量就可以假定为区间量表水平。2. 基于18个相关变量,通过单变量方差分析在两两均值比较时,至少用两个变量就可以将所有相邻的活动模式相互分离。3. 在线性判别分析框架内逐步减少可舍弃变量后,确定了一组最优变量,包括4、5、6、10、12赫兹以及14至20赫兹频率的百分比量,以及3.5至7.4赫兹频段振幅的平均值。在5个基本判别函数中的4个中,为每种模式计算的均值彼此之间有显著差异(方差分析,纽曼-库尔兹检验)。4. 通过线性回归分析可以表明,视觉信息处理时脑电图活动模式的分类系统在变量减少后也可以映射到区间量表上。最后,给出了关于评分程序可靠性的数据。

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