Feng Zhou-yan, Zheng Xiao-xiang
Space Med Med Eng (Beijing). 2002 Aug;15(4):276-80.
Objective. To study the complexity and the power spectrum of cortical EEG and hippocampal potential in rats under waking and sleep states. Method. Cortical EEG and hippocampal potential were collected by implanted electrodes in freely moving rats. Algorithmic complexity (Kc), approximate entropy (ApEn), power spectral density (PSD) and gravity frequency of PSD of the potential waves were calculated. Result. The complexity of hippocampal potential was higher than that of cortical EEG under every state. The complexity of cortical EEG was lowest under the state of non rapid eye movement (NREM) sleep. The complexity of hippocampal potential was highest under waking state. The total power of both potentials in 0.5- 30 Hz frequency band showed their highest values under NREM state. Conclusion. The values of Kc and ApEn are closely related to the distributions of PSD. When there are evident peaks in PSD, the complexities of signals will decrease. The complexities may be used to distinguish the difference between cortical EEG and hippocampal potential, or large differences between the same kind of potentials under different behavioral states.
目的。研究清醒和睡眠状态下大鼠皮层脑电图(EEG)和海马电位的复杂性及功率谱。方法。通过植入电极采集自由活动大鼠的皮层EEG和海马电位。计算电位波的算法复杂度(Kc)、近似熵(ApEn)、功率谱密度(PSD)以及PSD的重心频率。结果。在每种状态下,海马电位的复杂性均高于皮层EEG。皮层EEG的复杂性在非快速眼动(NREM)睡眠状态下最低。海马电位的复杂性在清醒状态下最高。两种电位在0.5 - 30 Hz频段的总功率在NREM状态下显示出最高值。结论。Kc和ApEn值与PSD的分布密切相关。当PSD出现明显峰值时,信号的复杂性会降低。这些复杂性可用于区分皮层EEG和海马电位之间的差异,或同一类电位在不同行为状态下的较大差异。