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时空模式的皮质脑电图非常快的振荡 (> 80 Hz) 与基于主神经元电耦合的网络模型一致。

Spatiotemporal patterns of electrocorticographic very fast oscillations (> 80 Hz) consistent with a network model based on electrical coupling between principal neurons.

机构信息

Department of Physical Sciences, IBM T.J. Watson Research Center, Yorktown Heights, New York 10598, USA.

出版信息

Epilepsia. 2010 Aug;51(8):1587-97. doi: 10.1111/j.1528-1167.2009.02420.x. Epub 2009 Dec 7.

Abstract

PURPOSE

We sought to characterize spatial and temporal patterns of electrocorticography (ECoG) very fast oscillations (> ∼80 Hz, VFOs) prior to seizures in human frontotemporal neocortex, and to develop a testable network model of these patterns.

METHODS

ECoG data were recorded with subdural grids from two preoperative patients with seizures of frontal lobe onset in an epilepsy monitoring unit. VFOs were recorded from rat neocortical slices. A "cellular automaton" model of network oscillations was developed, extending ideas of Traub et al. (Neuroscience, 92, 1999, 407) and Lewis & Rinzel (Network: Comput Neural Syst, 11, 2000, 299); this model is based on postulated electrical coupling between pyramidal cell axons.

RESULTS

Layer 5 of rat neocortex, in vitro, can generate VFOs when chemical synapses are blocked. Human epileptic neocortex, in situ, produces preseizure VFOs characterized by the sudden appearance of "blobs" of activity that evolve into spreading wavefronts. When wavefronts meet, they coalesce and propagate perpendicularly but never pass through each other. This type of pattern has been described by Lewis & Rinzel in cellular automaton models with spatially localized connectivity, and is demonstrated here with 120,000- to 5,760,000-cell models. We provide a formula for estimating VFO period from structural parameters and estimate the spatial scale of the connectivity.

DISCUSSION

These data provide further evidence, albeit indirect, that preseizure VFOs are generated by networks of pyramidal neurons coupled by gap junctions, each predominantly confined to pairs of neurons having somata separated by < ∼1-2 mm. Plausible antiepileptic targets are tissue mechanisms, such as pH regulation, that influence gap-junction conductance.

摘要

目的

我们旨在描绘人类前额叶新皮层癫痫发作前脑电描记术(ECoG)超快速振荡(>∼80 Hz,VFO)的时空模式,并开发这些模式的可测试网络模型。

方法

ECoG 数据是在癫痫监测单元中,从两名额叶起始癫痫发作的术前患者的硬膜下网格中记录的。VFO 是从大鼠新皮层切片中记录的。我们开发了一种网络振荡的“元胞自动机”模型,扩展了 Traub 等人(《神经科学》,92,1999,407)和 Lewis & Rinzel(《网络:计算神经系统》,11,2000,299)的思想;该模型基于假定的锥体细胞轴突之间的电耦合。

结果

在体外,当化学突触被阻断时,大鼠新皮层的第 5 层可以产生 VFO。原位人类癫痫性新皮层产生发作前的 VFO,其特征是突然出现“团块”活动,然后演变成扩展波阵面。当波阵面相遇时,它们会合并并垂直传播,但从不相互穿透。这种类型的模式已经在具有空间局部连接的元胞自动机模型中被 Lewis & Rinzel 描述过,这里用 12 万到 576 万细胞模型展示了这种模式。我们提供了一个从结构参数估计 VFO 周期的公式,并估计了连接的空间尺度。

讨论

这些数据提供了进一步的证据,尽管是间接的,表明发作前的 VFO 是由通过缝隙连接耦合的锥体神经元网络产生的,每个网络主要局限于具有相隔<∼1-2 mm 的胞体的神经元对。合理的抗癫痫靶点是组织机制,如 pH 调节,它影响缝隙连接电导。

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