不同年龄及状态下儿童脑电复杂度的特征

目的：应用非线性分析方法，研究儿童在不同年龄和不同生理状态下脑电复杂度的变化特征。方法：对45例健康状态基本正常的0～15岁儿童进行16导脑电连续24h监测，分析清醒睁眼、闭眼、NREM(非快速眼动期)睡眠Ⅰ～Ⅱ期(浅睡期)、Ⅲ～Ⅳ期(深睡期)及REM(眼速动期)睡眠共7种状态的脑电复杂度特征，并对复杂度与年龄的相关性进行分析。结果：(1)全脑复杂度在睁眼状态大于闭眼状态，清醒状态大于睡眠期。NREM睡眠期随睡眠深度增加，复杂度逐渐减低。REM期复杂度高于深睡期，但低于清醒期。(2)全脑平均脑电复杂度在睁眼、闭眼及浅睡期与年龄呈正相关，在深睡期及REM期与年龄无明显相关性。(3)在清醒闭眼状态下各脑区脑电复杂度与年龄均呈正相关，睁眼及浅睡期则以旁中线区复杂度与年龄有较好的相关性。结论：复杂度可用于研究不同生理状态下的脑动力学特征及脑电活动与脑发育的关系，可作为评价脑功能状态及脑发育水平的一个客观指标。

Characteristic of children's EEG complexity at different ages and in different states

OBJECTIVE: To study characteristics of children's EEG complexity at different ages and in different physiological states. METHODS: The continuous 24-hour EEG recordings were obtained from 16 electrodes in 45 essential healthy children between the ages of 0 to 15 years. EEG complexity was analyzed by non-linear measure in 7 states: awake with eyes opened, awake with eyes closed, NREM (nonrapid eye movements) sleep including stages I and II (light sleep), III and IV (deep sleep) and REM (rapid eye movements) sleep. Meanwhile, the correlation was analyzed between complexity and ages. RESULTS: (1) The global EEG complexity in state of being awake with eyes opened was greater than that with eyes closed; that in wakefulness state was greater than in sleep state. The EEG complexity gradually decreased with the increase of deep sleep in NREM sleep state. The complexity in REM sleep state was greater than that in deep sleep state, but lower than in wakefulness state. (2) The global EEG complexity was positively related to ages in state of being awake with eyes opened, state of being awake with eyes closed, light sleep, and not related to ages in deep-sleep state and REM sleep state. (3) In every brain area EEG complexity was positively related to ages in state of being awake with eyes closed. In paracentral region EEG complexity was positively related to ages in states of being awake with eyes opened and light sleep. CONCLUSION: The EEG complexity was used to study the brain dynamical characteristics in different physiology states and the relationship between encephalic electric activity and brain development. It can be used as an objective index to evaluate the function and development of brain.