Sargsyan Armen, Casillas-Espinosa Pablo M, Melkonian Dmitri, O'Brien Terence J, van Luijtelaar Gilles
Kaoskey Pty Ltd, Sydney, New South Wales, Australia.
Orbeli Institute of Physiology, Yerevan, Armenia.
Epilepsia Open. 2024 Dec;9(6):2365-2377. doi: 10.1002/epi4.13062. Epub 2024 Oct 9.
Frequency properties of the EEG characteristics of different seizure types including absence seizures have been described for various rodent models of epilepsy. However, little attention has been paid to the frequency properties of individual spike-wave complexes (SWCs), the constituting elements characterizing the different generalized seizure types. Knowledge of their properties is not only important for understanding the mechanisms underlying seizure generation but also for the identification of epileptiform activity in various seizure types. Here, we compared the frequency properties of SWCs in different epilepsy models.
A software package was designed and used for the extraction and frequency analysis of SWCs from long-term EEG of four spontaneously seizing, chronic epilepsy models: a post-status epilepticus model of temporal lobe epilepsy, a lateral fluid percussion injury model of post-traumatic epilepsy, and two genetic models of absence epilepsy-GAERS and rats of the WAG/Rij strain. The SWCs within the generalized seizures were separated into fast (three-phasic spike) and slow (mostly containing the wave) components. Eight animals from each model were used (32 recordings, 104 510 SWCs in total). A limitation of our study is that the recordings were hardware-filtered (high-pass), which could affect the frequency composition of the EEG.
We found that the three-phasic spike component was similar in all animal models both in time and frequency domains, their amplitude spectra showed a single expressed peak at 18-20 Hz. The slow component showed a much larger variability across the rat models.
Despite differences in the morphology of the epileptiform activity in different models, the frequency composition of the spike component of single SWCs is identical and does not depend on the particular epilepsy model. This fact may be used for the development of universal algorithms for seizure detection applicable to different rat models of epilepsy.
There is a large variety between people with epilepsy regarding the clinical manifestations and the electroencephalographic (EEG) phenomena accompanying the epileptic seizures. Here, we show that one of the EEG signs of epilepsy, an epileptic spike, is universal, since it has the same shape and frequency characteristics in different animal models of generalized epilepsies, despite differences in recording sites and location.
针对包括失神发作在内的不同癫痫发作类型的脑电图(EEG)特征的频率特性,已在各种啮齿类癫痫模型中有所描述。然而,对于单个棘慢复合波(SWC)的频率特性却鲜有关注,而SWC是表征不同全身性癫痫发作类型的构成要素。了解其特性不仅对于理解癫痫发作产生的机制很重要,而且对于识别各种癫痫发作类型中的癫痫样活动也很重要。在此,我们比较了不同癫痫模型中SWC的频率特性。
设计了一个软件包,用于从四种自发性发作的慢性癫痫模型的长期EEG中提取和分析SWC的频率:颞叶癫痫的癫痫持续状态后模型、创伤后癫痫的侧脑室液压冲击伤模型,以及两种失神癫痫的遗传模型——遗传失神癫痫大鼠(GAERS)和WAG/Rij品系大鼠。全身性发作中的SWC被分为快速(三相棘波)和慢速(主要包含波)成分。每个模型使用8只动物(共32次记录,104510个SWC)。我们研究的一个局限性是记录进行了硬件滤波(高通),这可能会影响EEG的频率组成。
我们发现,三相棘波成分在所有动物模型的时域和频域中都相似,其振幅谱在18 - 20Hz处显示出一个单一的明显峰值。慢速成分在不同大鼠模型中的变异性要大得多。
尽管不同模型中癫痫样活动的形态存在差异,但单个SWC的棘波成分的频率组成是相同的,且不依赖于特定的癫痫模型。这一事实可用于开发适用于不同大鼠癫痫模型的通用癫痫发作检测算法。
癫痫患者在癫痫发作的临床表现和脑电图(EEG)现象方面存在很大差异。在此,我们表明癫痫的EEG征象之一——癫痫棘波是通用的,因为尽管记录部位和位置不同,但在不同的全身性癫痫动物模型中,它具有相同的形状和频率特征。