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本文引用的文献

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Single-neuron dynamics in human focal epilepsy.人类局灶性癫痫中单神经元动力学。
Nat Neurosci. 2011 May;14(5):635-41. doi: 10.1038/nn.2782. Epub 2011 Mar 27.
2
Epileptic seizures: Quakes of the brain?癫痫发作:脑部的震动?
Phys Rev E Stat Nonlin Soft Matter Phys. 2010 Aug;82(2 Pt 1):021919. doi: 10.1103/PhysRevE.82.021919. Epub 2010 Aug 20.
3
High-frequency oscillations in epileptic brain.癫痫脑的高频振荡。
Curr Opin Neurol. 2010 Apr;23(2):151-6. doi: 10.1097/WCO.0b013e3283373ac8.
4
Sprouting in human temporal lobe epilepsy: excitatory pathways and axons of interneurons.人颞叶癫痫中的发芽:中间神经元的兴奋性通路和轴突。
Epilepsy Res. 2010 Mar;89(1):52-9. doi: 10.1016/j.eplepsyres.2010.01.002. Epub 2010 Feb 11.
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Intra-familial incidence and characteristics of hot water epilepsy.
Can J Neurol Sci. 2009 Sep;36(5):575-81. doi: 10.1017/s0317167100008064.
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Pharmaco-resistant seizures: self-triggering capacity, scale-free properties and predictability?耐药性癫痫发作:自触发能力、无标度特性和可预测性?
Eur J Neurosci. 2009 Oct;30(8):1554-8. doi: 10.1111/j.1460-9568.2009.06923.x. Epub 2009 Oct 12.
7
Seizure prediction: any better than chance?癫痫发作预测:是否比随机猜测更有效?
Clin Neurophysiol. 2009 Aug;120(8):1465-78. doi: 10.1016/j.clinph.2009.05.019. Epub 2009 Jul 2.
8
Unilateral cortical spreading depression induced by sound in rats.声音诱导大鼠单侧皮质扩散性抑制
Brain Res. 2009 Aug 25;1286:201-7. doi: 10.1016/j.brainres.2009.06.047. Epub 2009 Jun 25.
9
Serial correlation in neural spike trains: experimental evidence, stochastic modeling, and single neuron variability.神经脉冲序列中的序列相关性:实验证据、随机建模与单个神经元变异性
Phys Rev E Stat Nonlin Soft Matter Phys. 2009 Feb;79(2 Pt 1):021905. doi: 10.1103/PhysRevE.79.021905. Epub 2009 Feb 6.
10
Phase-dependent stimulation effects on bursting activity in a neural network cortical simulation.神经网络皮层模拟中相位依赖性刺激对爆发活动的影响。
Epilepsy Res. 2009 Mar;84(1):42-55. doi: 10.1016/j.eplepsyres.2008.12.005. Epub 2009 Jan 29.

异常网络引发的癫痫发作:为何有些癫痫发作难以预测。

Epileptic seizures from abnormal networks: why some seizures defy predictability.

机构信息

The Johns Hopkins University School of Medicine, Department of Neurosurgery, 600 North Wolfe Street, Baltimore, MD 21287, USA.

出版信息

Epilepsy Res. 2012 May;99(3):202-13. doi: 10.1016/j.eplepsyres.2011.11.006. Epub 2011 Dec 12.

DOI:10.1016/j.eplepsyres.2011.11.006
PMID:22169211
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3312991/
Abstract

Seizure prediction has proven to be difficult in clinically realistic environments. Is it possible that fluctuations in cortical firing could influence the onset of seizures in an ictal zone? To test this, we have now used neural network simulations in a computational model of cortex having a total of 65,536 neurons with intercellular wiring patterned after histological data. A spatially distributed Poisson driven background input representing the activity of neighboring cortex affected 1% of the neurons. Gamma distributions were fit to the interbursting phase intervals, a non-parametric test for randomness was applied, and a dynamical systems analysis was performed to search for period-1 orbits in the intervals. The non-parametric analysis suggests that intervals are being drawn at random from their underlying joint distribution and the dynamical systems analysis is consistent with a nondeterministic dynamical interpretation of the generation of bursting phases. These results imply that in a region of cortex with abnormal connectivity analogous to a seizure focus, it is possible to initiate seizure activity with fluctuations of input from the surrounding cortical regions. These findings suggest one possibility for ictal generation from abnormal focal epileptic networks. This mechanism additionally could help explain the difficulty in predicting partial seizures in some patients.

摘要

在临床现实环境中,癫痫发作的预测已被证明是困难的。皮层放电的波动是否可能影响癫痫发作区的发作?为了检验这一点,我们现在在皮层的计算模型中使用神经网络模拟,该模型总共有 65536 个神经元,细胞间的连接模式是根据组织学数据设计的。一个空间分布的泊松驱动的背景输入代表邻近皮层的活动,影响了 1%的神经元。对爆发间的相位间隔进行伽马分布拟合,应用非参数随机性检验,并进行动力系统分析,以在间隔中搜索周期 1 轨道。非参数分析表明,间隔是从其基础联合分布中随机抽取的,动力系统分析与爆发相位产生的非确定性动力解释一致。这些结果表明,在类似于癫痫灶的异常连接的皮层区域中,有可能通过来自周围皮层区域的输入波动来引发癫痫发作活动。这些发现为异常局灶性癫痫网络产生癫痫发作提供了一种可能性。这种机制还可以帮助解释为什么在某些患者中难以预测部分性癫痫发作。