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惊厥性癫痫发作终止及发作后广泛性脑电图抑制的动力学

Dynamics of convulsive seizure termination and postictal generalized EEG suppression.

作者信息

Bauer Prisca R, Thijs Roland D, Lamberts Robert J, Velis Demetrios N, Visser Gerhard H, Tolner Else A, Sander Josemir W, Lopes da Silva Fernando H, Kalitzin Stiliyan N

机构信息

Stichting Epilepsie Instellingen Nederland (SEIN), Achterweg 5, 2103 SW Heemstede, The Netherlands.

NIHR University College London Hospitals Biomedical Research Centre, UCL Institute of Neurology, Queen Square, London WC1N 3BG, UK.

出版信息

Brain. 2017 Mar 1;140(3):655-668. doi: 10.1093/brain/aww322.

Abstract

It is not fully understood how seizures terminate and why some seizures are followed by a period of complete brain activity suppression, postictal generalized EEG suppression. This is clinically relevant as there is a potential association between postictal generalized EEG suppression, cardiorespiratory arrest and sudden death following a seizure. We combined human encephalographic seizure data with data of a computational model of seizures to elucidate the neuronal network dynamics underlying seizure termination and the postictal generalized EEG suppression state. A multi-unit computational neural mass model of epileptic seizure termination and postictal recovery was developed. The model provided three predictions that were validated in EEG recordings of 48 convulsive seizures from 48 subjects with refractory focal epilepsy (20 females, age range 15-61 years). The duration of ictal and postictal generalized EEG suppression periods in human EEG followed a gamma probability distribution indicative of a deterministic process (shape parameter 2.6 and 1.5, respectively) as predicted by the model. In the model and in humans, the time between two clonic bursts increased exponentially from the start of the clonic phase of the seizure. The terminal interclonic interval, calculated using the projected terminal value of the log-linear fit of the clonic frequency decrease was correlated with the presence and duration of postictal suppression. The projected terminal interclonic interval explained 41% of the variation in postictal generalized EEG suppression duration (P < 0.02). Conversely, postictal generalized EEG suppression duration explained 34% of the variation in the last interclonic interval duration. Our findings suggest that postictal generalized EEG suppression is a separate brain state and that seizure termination is a plastic and autonomous process, reflected in increased duration of interclonic intervals that determine the duration of postictal generalized EEG suppression.

摘要

目前尚不完全清楚癫痫发作是如何终止的,以及为什么有些癫痫发作后会出现一段时间的全脑活动抑制,即发作后广泛性脑电图抑制。这在临床上具有相关性,因为发作后广泛性脑电图抑制、心肺骤停和癫痫发作后的猝死之间可能存在关联。我们将人类脑电图癫痫发作数据与癫痫发作的计算模型数据相结合,以阐明癫痫发作终止和发作后广泛性脑电图抑制状态背后的神经网络动力学。开发了一个癫痫发作终止和发作后恢复的多单元计算神经团模型。该模型提供了三个预测,并在48名难治性局灶性癫痫患者(20名女性,年龄范围15 - 61岁)的48次惊厥性癫痫发作的脑电图记录中得到验证。人类脑电图中发作期和发作后广泛性脑电图抑制期的持续时间遵循伽马概率分布,表明这是一个确定性过程(形状参数分别为2.6和1.5),正如模型所预测的那样。在模型和人类中,两次阵挛性发作之间的时间从癫痫发作的阵挛期开始呈指数增加。使用阵挛频率下降的对数线性拟合的预测终值计算的终末阵挛间期与发作后抑制的存在和持续时间相关。预测的终末阵挛间期解释了发作后广泛性脑电图抑制持续时间变异的41%(P < 0.02)。相反,发作后广泛性脑电图抑制持续时间解释了最后阵挛间期持续时间变异的34%。我们的研究结果表明,发作后广泛性脑电图抑制是一种独立的脑状态,癫痫发作终止是一个可塑性的自主过程,反映在阵挛间期持续时间的增加上,而阵挛间期持续时间决定了发作后广泛性脑电图抑制的持续时间。

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