Van Albada Sacha J, Rennie Christopher J, Robinson Peter A
School of Physics, University of Sydney, NSW 2006, Australia.
J Integr Neurosci. 2007 Jun;6(2):279-307. doi: 10.1142/s0219635207001520.
Variable contributions of state and trait to the electroencephalographic (EEG) signal affect the stability over time of EEG measures, quite apart from other experimental uncertainties. The extent of intraindividual and interindividual variability is an important factor in determining the statistical, and hence possibly clinical significance of observed differences in the EEG. This study investigates the changes in classical quantitative EEG (qEEG) measures, as well as of parameters obtained by fitting frequency spectra to an existing continuum model of brain electrical activity. These parameters may have extra variability due to model selection and fitting. Besides estimating the levels of intraindividual and interindividual variability, we determined approximate time scales for change in qEEG measures and model parameters. This provides an estimate of the recording length needed to capture a given percentage of the total intraindividual variability. Also, if more precise time scales can be obtained in future, these may aid the characterization of physiological processes underlying various EEG measures. Heterogeneity of the subject group was constrained by testing only healthy males in a narrow age range (mean = 22.3 years, sd = 2.7). Eyes-closed EEGs of 32 subjects were recorded at weekly intervals over an approximately six-week period, of which 13 subjects were followed for a year. QEEG measures, computed from Cz spectra, were powers in five frequency bands, alpha peak frequency, and spectral entropy. Of these, theta, alpha, and beta band powers were most reproducible. Of the nine model parameters obtained by fitting model predictions to experiment, the most reproducible ones quantified the total power and the time delay between cortex and thalamus. About 95% of the maximum change in spectral parameters was reached within minutes of recording time, implying that repeat recordings are not necessary to capture the bulk of the variability in EEG spectra.
状态和特质对脑电图（EEG）信号的不同贡献会影响EEG测量随时间的稳定性，这与其他实验不确定性无关。个体内和个体间变异性的程度是决定EEG中观察到的差异的统计学意义以及可能的临床意义的一个重要因素。本研究调查了经典定量脑电图（qEEG）测量的变化，以及通过将频谱拟合到现有的脑电活动连续模型而获得的参数的变化。由于模型选择和拟合，这些参数可能具有额外的变异性。除了估计个体内和个体间变异性的水平外，我们还确定了qEEG测量和模型参数变化的近似时间尺度。这提供了捕获给定百分比的个体内总变异性所需的记录长度的估计。此外，如果未来能够获得更精确的时间尺度，这些尺度可能有助于表征各种EEG测量背后的生理过程。通过仅在狭窄年龄范围内（平均=22.3岁，标准差=2.7）测试健康男性来限制受试者组的异质性。在大约六周的时间内，每周对32名受试者进行闭眼EEG记录，其中13名受试者被跟踪了一年。从Cz频谱计算得到的qEEG测量值包括五个频段的功率、α峰值频率和频谱熵。其中，θ、α和β频段功率的重复性最高。在通过将模型预测与实验拟合而获得的九个模型参数中，重复性最高的参数量化了总功率以及皮层和丘脑之间的时间延迟。在记录时间的几分钟内，频谱参数的最大变化约95%就已达到，这意味着无需重复记录就能捕获EEG频谱中大部分的变异性。
