Wendling Fabrice, Hernandez Alfredo, Bellanger Jean-Jacques, Chauvel Patrick, Bartolomei Fabrice
Laboratoire Traitement du Signal et de L'Image, INSERM Université de Rennes 1, Campus de Beaulieu, Rennes Cedex, France.
J Clin Neurophysiol. 2005 Oct;22(5):343-56.
In human partial epilepsies and in experimental models of chronic and/or acute epilepsy, the role of inhibition and the relationship between the inhibition and excitation and epileptogenesis has long been questioned. Besides experimental methods carried out either in vitro (human or animal tissue) or in vivo (animals), pathophysiologic mechanisms can be approached by direct recording of brain electrical activity in human epilepsy. Indeed, in some clinical presurgical investigation methods like stereoelectroencephalography, intracerebral electrodes are used in patients suffering from drug resistant epilepsy to directly record paroxysmal activities with excellent temporal resolution (in the order of 1 millisecond). The study of neurophysiologic mechanisms underlying such depth-EEG activities is crucial to progress in the understanding of the interictal to ictal transition. In this study, the authors relate electrophysiologic patterns typically observed during the transition from interictal to ictal activity in human mesial temporal lobe epilepsy (MTLE) to mechanisms (at a neuronal population level) involved in seizure generation through a computational model of EEG activity. Intracerebral EEG signals recorded from hippocampus in five patients with MTLE during four periods (during interictal activity, just before seizure onset, during seizure onset, and during ictal activity) were used to identify the three main parameters of a model of hippocampus EEG activity (related to excitation, slow dendritic inhibition and fast somatic inhibition). The identification procedure used optimization algorithms to minimize a spectral distance between real and simulated signals. Results demonstrated that the model generates very realistic signals for automatically identified parameters. They also showed that the transition from interictal to ictal activity cannot be simply explained by an increase in excitation and a decrease in inhibition but rather by time-varying ensemble interactions between pyramidal cells and local interneurons projecting to either their dendritic or perisomatic region (with slow and fast GABAA kinetics). Particularly, during preonset activity, an increasing dendritic GABAergic inhibition compensates a gradually increasing excitation up to a brutal drop at seizure onset when faster oscillations (beta and low gamma band, 15 to 40 Hz) are observed. These faster oscillations are then explained by the model feedback loop between pyramidal cells and interneurons targeting their perisomatic region. These findings obtained from model identification in human temporal lobe epilepsy are in agreement with some results obtained experimentally, either on animal models of epilepsy or on the human epileptic tissue.
在人类部分性癫痫以及慢性和/或急性癫痫的实验模型中，抑制作用的角色以及抑制与兴奋和癫痫发生之间的关系长期以来一直受到质疑。除了在体外（人体或动物组织）或体内（动物）进行的实验方法外，还可以通过直接记录人类癫痫患者的脑电活动来探究病理生理机制。实际上，在一些临床术前检查方法中，如立体脑电图检查，对于药物难治性癫痫患者会使用脑内电极来直接记录具有出色时间分辨率（约1毫秒）的阵发性活动。研究此类深度脑电图活动背后的神经生理机制对于理解发作间期到发作期的转变至关重要。在本研究中，作者通过脑电图活动的计算模型，将人类内侧颞叶癫痫（MTLE）从发作间期到发作期活动转变过程中典型观察到的电生理模式与癫痫发作产生所涉及的机制（在神经元群体水平）联系起来。从五名MTLE患者海马体记录的脑内脑电图信号在四个时期（发作间期活动期间、癫痫发作即将开始前、癫痫发作开始时以及发作期活动期间）被用于确定海马体脑电图活动模型的三个主要参数（与兴奋、慢树突抑制和快胞体抑制相关）。识别过程使用优化算法来最小化真实信号与模拟信号之间的频谱距离。结果表明，该模型针对自动识别的参数生成了非常逼真的信号。研究还表明，从发作间期到发作期活动的转变不能简单地用兴奋增加和抑制减少来解释，而是由锥体细胞与投射到其树突或胞体周围区域的局部中间神经元之间随时间变化的整体相互作用来解释（具有慢和快的GABAA动力学）。特别是，在发作前活动期间，逐渐增加的树突状GABA能抑制补偿了逐渐增加的兴奋，直到癫痫发作开始时出现急剧下降，此时观察到更快的振荡（β和低γ频段，15至40赫兹）。然后，这些更快的振荡由锥体细胞与靶向其胞体周围区域的中间神经元之间的模型反馈回路来解释。这些从人类颞叶癫痫模型识别中获得的发现与在癫痫动物模型或人类癫痫组织上通过实验获得的一些结果一致。
