Ogawa T, Sugiyama A, Ishiwa S, Suzuki M, Ishihara T, Sato K
Brain Dev. 1984;6(3):289-303. doi: 10.1016/s0387-7604(84)80042-x.
Waking EEGs of 150 normal children aged from 20 days to 15 years were subjected to analysis. Discrete time series of an artifact free segment of the EEG record at 50 samples/sec for twenty seconds was generated and autoregressive (AR) and component analyses were carried out with a minicomputer PDP 11/40 (DEC). The results may be summarized as follows: 1) In the group of 1 year old and less, the power increased with the monthly age, whereas the bio-informing activity amount decreased. In those older than 1 year, both parameters showed maximal values at 1 year and then decreased with age, and the decreases were marked from 1 to 3 years. 2) The first- and second-order component activities of 129 and 677 waves, respectively, were obtained by applying component analysis to 152 EEG records. The frequency polygons of natural frequency of second-order component waves verified several modes, each of which was enhanced in the frequency range of the well-known delta 0, delta 1, theta 1, theta 2, alpha 1, alpha 2, beta 1, beta 2 and beta 3 waves, respectively. 3) The average percent-power of the delta wave (delta 0 + delta 1) decreased with age, especially from 1 to 3 years old, whereas those of beta- and alpha-waves increased with advancing age. That of the theta wave tended to increase from 2 to 4 years of age, and thereafter decreased gradually with increasing age. 4) With increasing age, the durations of damped oscillations were significantly lengthened in delta 1, alpha 1 and beta 3 waves, whereas that in the theta 1 wave was significantly shortened. 5) The bio-informing activity amounts of alpha waves increased from 1 to 3 years with increasing age, whereas those of delta and theta waves decreased. No significant developmental change in the parameters, however, was observed in the beta wave. The results indicate that AR-power spectral and component analyses of EEG are sensitive methods for obtaining valuable information regarding the electrical brain maturation in childhood.
对150名年龄在20天至15岁的正常儿童的清醒脑电图进行了分析。以每秒50个样本的频率生成了脑电图记录中一段20秒无伪迹片段的离散时间序列，并使用小型计算机PDP 11/40（数字设备公司）进行了自回归（AR）分析和成分分析。结果可总结如下：1）在1岁及以下的儿童组中，功率随月龄增加，而生物信息活动量减少。在1岁以上的儿童中，这两个参数在1岁时均显示最大值，然后随年龄下降，且在1至3岁时下降明显。2）通过对152份脑电图记录进行成分分析，分别获得了129个和677个波的一阶和二阶成分活动。二阶成分波自然频率的频率多边形验证了几种模式，每种模式分别在著名的δ0、δ1、θ1、θ2、α1、α2、β1、β2和β3波的频率范围内增强。3）δ波（δ0 + δ1）的平均功率百分比随年龄下降，尤其是在1至3岁时，而β波和α波的平均功率百分比随年龄增长而增加。θ波的平均功率百分比在2至4岁时趋于增加，此后随年龄增长逐渐下降。4）随着年龄的增加，δ1、α1和β3波的阻尼振荡持续时间显著延长，而θ1波的阻尼振荡持续时间显著缩短。5）α波的生物信息活动量在1至3岁时随年龄增加而增加
