论文标题
癫痫活性的现象学介质模型
Phenomenological Mesoscopic Models for Seizure Activity
论文作者
论文摘要
在本章中，我们回顾了癫痫发作的现象学模型。我们讨论了癫痫发作和偏移，前尖峰，尖峰和波形复合物以及状态癫痫症的动力学机制，突出了模型的分叉结构，噪声的存在以及多个相互作用的时间尺度的出现。这些模型可用于构建大规模的患者特定的大脑网络模型，该模型用作测试临床假设并进行虚拟手术的内利科平台。他们提出了创新的治疗策略，例如完全利用系统的网络和动力学特性的微创消融或刺激，甚至调节变量和参数，以迫使在分叉图的更安全区域中进行系统。我们讨论了现象学模型的见解，这些见解可以帮助我们促进我们对癫痫发作基础机制的理解。
In this chapter we review phenomenological models of seizure like activity. We discuss dynamical mechanisms for seizure onset and offset, preictal spikes, spike and wave complexes and status epilepticus, highlighting the role played by the bifurcation structure of the model, the presence of noise and the emergence of multiple interacting time-scales. These models can be used to build large-scale patient specific brain network models serving as in-silico platforms to test clinical hypothesis and perform virtual surgeries. They suggest innovative treatment strategies, such as minimally invasive ablations or stimulations that fully exploit the network and dynamical properties of the system, or even modulation of variables and parameters to force the system in safer regions of the bifurcation diagram. We discuss insights from phenomenological models that can help to foster our understanding of the mechanisms underlying epileptic seizures.
