颅内压增高皮层脑电的复杂度分析

为研究颅内压增高对脑功能的影响,以家兔为实验对象建立侧脑室灌注加压的单纯颅高压模型.采集皮层脑电信号并同步记录颅内压(ICP)、心电、呼吸、动脉血压等信号,采用迟滞粗粒化方法和Lempel-Ziv算法计算脑电信号的复杂度,分析不同ICP状态下脑电信号的非线性变化特征.发现以灌注加压前基础ICP时的状态为对照,ICP为2,4倍基础值时的脑电信号复杂度显著降低(P＜0.01);ICP越高,复杂度越低;ICP恢复正常后,脑电复杂度有恢复趋势.研究结果表明,脑电信号的复杂度可用于检测由于ICP增高引起的脑损伤并有可能对其损伤程度进行定量评估.

Using complexity measurement to study the electrocorticogram of increased intracranial pressure

To explore the effects of increased intracranial pressure (ICP) on brain function, a rabbit experimental model of increased ICP is presented. The ICP was adjusted by artificial cerebrospinal fluid (ACSF) perfusion. Based on this model the electrocorticogram(ECoG) signals were collected under different ICP stages. Meanwhile, the electrocardiogram (ECG), respiration waveform (Resp), arterial blood pressure (ABP) and ICP were recorded. In order to investigate nonlinear characteristics of ECoG under different ICP stages, the ECoG complexities were calculated by using the sluggish partitioning method and Lemp-Ziv algorithm and the results showed that the ECoG complexities under double and fourfold baseline ICP were decreased significantly compared with the baseline control. And the complexity under fourfold baseline ICP was less than that under double baseline. After the ICP back to the baseline, the ECoG complexity had an increased tendency. The study indicates that ECoG complexity could be useed to detect brain injury and to estimate the extent of the injury induced by increased ICP.