On the nature of seizure dynamics
On the nature of seizure dynamics
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DOI：
10.1093/brain/awu133
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发表时间：
2014-08-01
期刊：
影响因子：
14.5
通讯作者：
Bernard, Christophe
中科院分区：
文献类型：
--
作者：
Jirsa, Viktor K.;Stacey, William C.;Bernard, Christophe
通过对癫痫发作动力学进行数学建模，Jirsa等人根据第一原理开发了癫痫发作分类法。他们使用典型模型（“Epileptor”）和实验验证，证明局灶性发作的癫痫发作大多属于一个特定的类别，从苍蝇到人类，这种类别在大脑区域和物种中普遍存在。癫痫发作可以自发发生，也可以以反复发作的方式发生，这定义了癫痫;或者它们可以在正常大脑中在各种条件下在大多数神经网络和物种中诱导，从苍蝇到人类。这种普遍性提出了一种可能性，即在不同的生理和病理条件下，存在表征癫痫发作的不变特性。在这里，我们从数学上分析了癫痫发作的动力学，并建立了一个基于第一原则的癫痫发作分类。对于主要的癫痫发作类别，我们开发了一种称为癫痫发作的通用模型。作为一个实验模型系统，我们使用在体外诱导的小鼠海马癫痫样放电。我们发现，只有五个状态变量的积分-微分方程是足以描述发作样放电的发作，时间过程和偏移量，以及它们的复发。两个状态变量负责产生快速放电（快速时间尺度），两个用于尖峰和波事件（中间时间尺度），一个用于控制时间过程，包括“正常”和发作期之间的交替（慢时间尺度）。我们建议，正常和发作活动共存：分界线作为这些国家之间的障碍（或癫痫发作阈值）。癫痫发作是在正常大脑轨迹与分界线碰撞时达到的。我们从理论上和实验上展示了一个系统如何在各种条件下被推向癫痫发作。在我们的实验模型中，发作样放电的开始和结束是定义明确的数学事件：分别是鞍结和同宿分叉。这些分叉需要在发作时基线偏移和偏移时峰间期的对数标度。这些预测不仅在我们的体外实验中得到了证实，而且在不同综合征，脑区和物种（人类和斑马鱼）中记录的局灶性癫痫发作中也得到了证实。最后，我们确定了几个可能的生物物理参数有助于我们的模型系统中的五个状态变量。我们表明，这些参数适用于特定的实验条件，并提出存在广泛的生物物理机制癫痫发作成因，同时保持中心不变的属性。癫痫和癫痫分类学将通过确定控制癫痫发作开始和终止的普遍规则并预测这些转变所需的条件来指导未来的建模和转化研究。
By modelling seizure dynamics mathematically, Jirsa et al. develop a taxonomy of seizures based on first principles. Using a canonical model ('Epileptor') and experimental validation, they demonstrate that seizures with focal onset mostly fall into one particular class that is universal across brain regions and species, from flies to humans.Seizures can occur spontaneously and in a recurrent manner, which defines epilepsy; or they can be induced in a normal brain under a variety of conditions in most neuronal networks and species from flies to humans. Such universality raises the possibility that invariant properties exist that characterize seizures under different physiological and pathological conditions. Here, we analysed seizure dynamics mathematically and established a taxonomy of seizures based on first principles. For the predominant seizure class we developed a generic model called Epileptor. As an experimental model system, we used ictal-like discharges induced in vitro in mouse hippocampi. We show that only five state variables linked by integral-differential equations are sufficient to describe the onset, time course and offset of ictal-like discharges as well as their recurrence. Two state variables are responsible for generating rapid discharges (fast time scale), two for spike and wave events (intermediate time scale) and one for the control of time course, including the alternation between 'normal' and ictal periods (slow time scale). We propose that normal and ictal activities coexist: a separatrix acts as a barrier (or seizure threshold) between these states. Seizure onset is reached upon the collision of normal brain trajectories with the separatrix. We show theoretically and experimentally how a system can be pushed toward seizure under a wide variety of conditions. Within our experimental model, the onset and offset of ictal-like discharges are well-defined mathematical events: a saddle-node and homoclinic bifurcation, respectively. These bifurcations necessitate a baseline shift at onset and a logarithmic scaling of interspike intervals at offset. These predictions were not only confirmed in our in vitro experiments, but also for focal seizures recorded in different syndromes, brain regions and species (humans and zebrafish). Finally, we identified several possible biophysical parameters contributing to the five state variables in our model system. We show that these parameters apply to specific experimental conditions and propose that there exists a wide array of possible biophysical mechanisms for seizure genesis, while preserving central invariant properties. Epileptor and the seizure taxonomy will guide future modeling and translational research by identifying universal rules governing the initiation and termination of seizures and predicting the conditions necessary for those transitions.