Medical Physics Department, Epilepsy Institute of The Netherlands Foundation (SEIN), Heemstede, The Netherlands.
Epilepsy Behav. 2010 Mar;17(3):310-23. doi: 10.1016/j.yebeh.2009.12.023. Epub 2010 Feb 16.
We focus on the implications that the underlying neuronal dynamics might have on the possibility of anticipating seizures and designing an effective paradigm for their control. Transitions into seizures can be caused by parameter changes in the dynamic state or by interstate transitions as occur in multi-attractor systems; in the latter case, only a weak statistical prognosis of the seizure risk can be achieved. Nevertheless, we claim that by applying a suitable perturbation to the system, such as electrical stimulation, relevant features of the system's state may be detected and the risk of an impending seizure estimated. Furthermore, if these features are detected early, transitions into seizures may be blocked. On the basis of generic and realistic computer models we explore the concept of acute seizure control through state-dependent feedback stimulation. We show that in some classes of dynamic transitions, this can be achieved with a relatively limited amount of stimulation.
我们关注潜在神经元动力学对预测癫痫发作的可能性以及设计有效的控制范式的影响。癫痫发作的转变可能是由动态状态中的参数变化引起的，也可能是多吸引子系统中发生的州际转变引起的；在后一种情况下，只能对癫痫发作风险进行微弱的统计预测。然而，我们声称，通过对系统施加适当的扰动，如电刺激，可以检测到系统状态的相关特征，并估计即将发生的癫痫发作的风险。此外，如果这些特征被早期检测到，癫痫发作的转变可能会被阻止。基于通用和现实的计算机模型，我们探索了通过状态相关反馈刺激来实现急性癫痫控制的概念。我们表明，在某些类别的动态转变中，通过相对有限量的刺激就可以实现这一点。
