癫痫模型中痫样棘波自动检测的新算法及其应用

发布时间：2018-03-16 21:15

本文选题：癫痫模型　切入点：群峰电位　出处：《生物医学工程学杂志》2017年04期 　论文类型：期刊论文

【摘要】：癫痫的典型特征是神经元群体产生异常同步发放,在记录的神经电信号中呈现为痫样棘波。为了定量分析癫痫发生时的痫样棘波,本文设计了一种基于窗口的检测法用于自动检测大鼠海马CA1区急性癫痫模型的棘波信号,即群峰电位(PS),并计算其特征参数。实验结果表明,在钾离子通道拮抗剂4-氨基吡啶(4-AP)和γ-氨基丁酸A型受体拮抗剂印防己毒素(PTX)诱导的癫痫模型中,该算法可直接从原始宽频带记录信号中正确识别PS波。两种模型中的PS检出率分别为94.2%±1.6%(n=11)和95.9%±1.9%(n=12),且误检率分别为3.5%±2.3%(n=11)和4.8%±2.3%(n=12),远小于普通阈值法的误检率。比较4-AP和PTX模型的PS波特征,结果显示:4-AP诱导的PS波具有较宽的波形,发放较分散,发放间隔主要分布于100~700 ms范围内。而PTX诱导的PS则呈现爆发式发放,发放率较高,发放间隔主要分布于2~20 ms范围内,使得每秒PS幅值之和显著大于4-AP模型。因此,PTX模型的神经元群体同步发放活动比4-AP模型要强烈。总之,该棘波检测新算法可以正确识别和分析痫样棘波,为癫痫发生机制的研究和癫痫治疗新方法的评估提供了一种有用的数据分析工具。
[Abstract]:The typical feature of epilepsy is the abnormal synchronous distribution of neurons, which is presented as epileptiform spike in recorded neuroelectric signals, in order to quantitatively analyze epileptiform spike at the time of epilepsy. In this paper, a window-based detection method is designed to detect the spike signal of rat hippocampal CA1 region acute epilepsy model, that is, group peak potential, and its characteristic parameters are calculated. The experimental results show that, In the epileptic model induced by potassium channel antagonist 4-aminopyridine 4-APand 纬 -aminobutyric acid A receptor antagonist Tetrandrine PTX), The detection rate of PS in the two models is 94.2% 卤1.6 and 95.9% 卤1.9, respectively, and the false detection rate is 3.5% 卤2.3 and 4.8% 卤2.3 respectively, which is much less than that of the conventional threshold method, and the characteristics of PS wave in 4-AP and PTX models are compared. The results showed that the PS wave induced by: 4-AP had a wide waveform, and the distribution interval was mainly distributed in the range of 100m ~ 700ms, while that induced by PTX was explosive, and the distribution rate was higher, and the distribution interval was mainly within the range of 2o 20ms. The sum of PS amplitudes per second is significantly larger than that of 4-AP model. Therefore, the synchronous distribution activity of neuron population in PTX model is stronger than that in 4-AP model. In short, the new spike detection algorithm can correctly identify and analyze epileptiform spike waves. It provides a useful data analysis tool for the study of the mechanism of epilepsy and the evaluation of new methods of epilepsy treatment.
【作者单位】：浙江大学生物医学工程与仪器科学学院生物医学工程教育部重点实验室;
【基金】：国家自然科学基金项目资助(30970753)
【分类号】：R742.1;TN911.23

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