Fingelkurts Alexander A, Fingelkurts Andrew A, Ermolaev Victor A, Kaplan Alexander Ya
BM-SCIENCE, Brain and Mind Technologies Research Centre, PO Box 77, FI-02601, Espoo, Finland.
Int J Psychophysiol. 2006 Feb;59(2):116-26. doi: 10.1016/j.ijpsycho.2005.03.014. Epub 2005 Jun 6.
In the present experimental study, we examined the compositions of electroencephalographic (EEG) brain oscillations and their percent ratio in 12 subjects during resting conditions (closed and open eyes) and during the memory task (waiting, encoding and keeping-in-mind stages). The exact compositions of brain oscillations and their percent ratio were assessed by the probability-classification analysis of short-term EEG spectral patterns, which results in the probability-classification profile (PCP). Within sessions the PCPs are found to be stable, as reflected by a relatively low coefficient of variability, and between sessions the PCPs are highly reproducible. Finally, test-retest reliability of subject's PCPs shows a dependency on task, being higher for the memory task, and in particular for the encoding stage. It was suggested that these findings support and strengthen the superposition principle where integrative brain functions are manifested in the superposition of distributed multiple oscillations.
在本实验研究中,我们检测了12名受试者在静息状态(闭眼和睁眼)以及记忆任务(等待、编码和记忆阶段)期间脑电图(EEG)脑振荡的组成及其百分比。通过对短期EEG频谱模式的概率分类分析来评估脑振荡的确切组成及其百分比,该分析产生概率分类图谱(PCP)。在各次实验中,PCP被发现是稳定的,这通过相对较低的变异系数得以体现,并且在不同次实验之间,PCP具有高度的可重复性。最后,受试者PCP的重测信度显示出对任务的依赖性,在记忆任务中更高,尤其是在编码阶段。有人认为,这些发现支持并强化了叠加原理,即整合性脑功能体现在分布式多个振荡的叠加中。