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现象学网络模型:癫痫手术的经验教训。

Phenomenological network models: Lessons for epilepsy surgery.

作者信息

Hebbink Jurgen, Meijer Hil, Huiskamp Geertjan, van Gils Stephan, Leijten Frans

机构信息

Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands.

Department of Applied Mathematics, MIRA Institute for Biomedical Engineering and Technical Medicine, University of Twente, Enschede, The Netherlands.

出版信息

Epilepsia. 2017 Oct;58(10):e147-e151. doi: 10.1111/epi.13861. Epub 2017 Jul 26.

DOI:10.1111/epi.13861
PMID:28744852
Abstract

The current opinion in epilepsy surgery is that successful surgery is about removing pathological cortex in the anatomic sense. This contrasts with recent developments in epilepsy research, where epilepsy is seen as a network disease. Computational models offer a framework to investigate the influence of networks, as well as local tissue properties, and to explore alternative resection strategies. Here we study, using such a model, the influence of connections on seizures and how this might change our traditional views of epilepsy surgery. We use a simple network model consisting of four interconnected neuronal populations. One of these populations can be made hyperexcitable, modeling a pathological region of cortex. Using model simulations, the effect of surgery on the seizure rate is studied. We find that removal of the hyperexcitable population is, in most cases, not the best approach to reduce the seizure rate. Removal of normal populations located at a crucial spot in the network, the "driver," is typically more effective in reducing seizure rate. This work strengthens the idea that network structure and connections may be more important than localizing the pathological node. This can explain why lesionectomy may not always be sufficient.

摘要

目前癫痫手术领域的观点认为,成功的手术在于从解剖学意义上去除病变皮质。这与癫痫研究的最新进展形成对比,在最新进展中,癫痫被视为一种网络疾病。计算模型提供了一个框架,用于研究网络以及局部组织特性的影响,并探索替代切除策略。在此,我们使用这样一个模型来研究连接对癫痫发作的影响,以及这可能如何改变我们对癫痫手术的传统观点。我们使用一个由四个相互连接的神经元群体组成的简单网络模型。其中一个群体可被诱导为过度兴奋,模拟皮质的病变区域。通过模型模拟,研究手术对癫痫发作率的影响。我们发现,在大多数情况下,去除过度兴奋的群体并非降低癫痫发作率的最佳方法。去除位于网络关键位置即“驱动者”的正常群体,通常在降低癫痫发作率方面更有效。这项工作强化了这样一种观点,即网络结构和连接可能比定位病变节点更为重要。这可以解释为什么病灶切除术可能并不总是足够的。

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