Department of Pediatrics, Division of Neurology, University of Florida, Gainesville, FL 32610, United States.
Seizure. 2012 Dec;21(10):748-59. doi: 10.1016/j.seizure.2012.08.012. Epub 2012 Sep 18.
Approximately 30% of epilepsy patients suffer from medically refractory epilepsy, in which seizures can not controlled by the use of anti-epileptic drugs (AEDs). Understanding the mechanisms underlying these forms of drug-resistant epileptic seizures and the development of alternative effective treatment strategies are fundamental challenges for modern epilepsy research. In this context, computational modeling has gained prominence as an important tool for tackling the complexity of the epileptic phenomenon. In this review article, we present a survey of computational models of epilepsy from the point of view that epilepsy is a dynamical brain disease that is primarily characterized by unprovoked spontaneous epileptic seizures.
We introduce key concepts from the mathematical theory of dynamical systems, such as multi-stability and bifurcations, and explain how these concepts aid in our understanding of the brain mechanisms involved in the emergence of epileptic seizures.
We present a literature survey of the different computational modeling approaches that are used in the study of epilepsy. Special emphasis is placed on highlighting the fine balance between the degree of model simplification and the extent of biological realism that modelers seek in order to address relevant questions. In this context, we discuss three specific examples from published literature, which exemplify different approaches used for developing computational models of epilepsy. We further explore the potential of recently developed optogenetics tools to provide novel avenue for seizure control.
We conclude with a discussion on the utility of computational models for the development of new epilepsy treatment protocols.
大约 30%的癫痫患者患有药物难治性癫痫，即抗癫痫药物（AEDs）无法控制的癫痫发作。了解这些耐药性癫痫发作的机制以及开发替代有效治疗策略是现代癫痫研究的基本挑战。在这种情况下，计算建模作为解决癫痫现象复杂性的重要工具得到了重视。在这篇综述文章中，我们从癫痫是一种主要表现为自发性癫痫发作的大脑疾病的角度，对癫痫的计算模型进行了综述。
我们介绍了动力系统数学理论中的关键概念，如多稳定性和分岔，并解释了这些概念如何帮助我们理解癫痫发作中涉及的大脑机制。
我们对用于研究癫痫的不同计算建模方法进行了文献综述。特别强调了在寻求模型简化程度和生物现实程度之间的精细平衡，以便解决相关问题。在这方面，我们讨论了来自已发表文献的三个具体示例，这些示例说明了为开发癫痫计算模型而采用的不同方法。我们进一步探讨了最近开发的光遗传学工具在提供新的癫痫控制途径方面的潜力。
我们讨论了计算模型在开发新的癫痫治疗方案中的效用。
