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目的:探讨振幅整合脑电图(a EEG)在颞叶癫痫模型癫痫脑电记录中的应用价值。方法:选用成年雄性恒河猴4只,应用单侧杏仁核海人酸(2μg/μL)注射法构建颞叶癫痫模型。对模型动物进行定期的头皮脑电监测。脑电记录采用原始脑电图联合量化脑电图同步进行记录。对a EEG上的异常节点进行定位并对同时段的原始脑电图进行回顾性分析,判断其对动物模型的癫痫发作诊断的准确性。结果:排除明显接触不良造成的异常片段后,4只模型动物的a EEG趋势图分析共取得23处与背景活动明显不同的节点。对上述11处节点对应原始脑电图进行分析,均考虑为癫痫发作事件。结论:a EEG趋势图对于该颞叶癫痫模型的癫痫发作诊断具有高度敏感性,在超长程脑电监测中联合应用此方法可对癫痫发作进行快速定位,为实验研究节省大量人力成本。
Objective: To investigate the value of amplitude-integrated electroencephalogram (EEG) in the epileptic EEG recording of temporal lobe epilepsy model. Methods: Four adult male rhesus monkeys were selected and the temporal lobe epilepsy model was established by injecting 2μg / μL unilateral amygdala. Periodic scalp EEG monitoring of model animals. EEG recording using the original EEG simultaneous quantitative EEG recording. The abnormal nodes on a EEG were located and the original EEG of the same period was retrospectively analyzed to determine the accuracy of the diagnosis of seizures in animal models. Results: After eliminating the abnormal fragments caused by obvious contact failure, a total of 23 nodes with significantly different background activities were obtained from the aEGEG trend analysis of 4 model animals. The corresponding eleven nodes corresponding to the original EEG analysis, are considered as seizures. Conclusion: The EEG trend graph is highly sensitive to the diagnosis of epilepsy in this temporal lobe epilepsy model. This method can be used to rapidly locate epileptic seizures during long-term EEG monitoring, saving a lot of labor costs for experimental research.