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本文引用的文献

1
Imaging structural and functional brain networks in temporal lobe epilepsy.颞叶癫痫中脑结构和功能网络的成像
Front Hum Neurosci. 2013 Oct 1;7:624. doi: 10.3389/fnhum.2013.00624.
2
Altered resting state brain dynamics in temporal lobe epilepsy can be observed in spectral power, functional connectivity and graph theory metrics.颞叶癫痫患者的静息态脑动力学改变可以在频谱功率、功能连接和图论指标中观察到。
PLoS One. 2013 Jul 26;8(7):e68609. doi: 10.1371/journal.pone.0068609. Print 2013.
3
Interictal network properties in mesial temporal lobe epilepsy: a graph theoretical study from intracerebral recordings.内侧颞叶癫痫的发作间期网络特性:脑内记录的图论研究。
Clin Neurophysiol. 2013 Dec;124(12):2345-53. doi: 10.1016/j.clinph.2013.06.003. Epub 2013 Jun 28.
4
Groupwise whole-brain parcellation from resting-state fMRI data for network node identification.基于静息态 fMRI 数据的群组全脑分割用于网络节点识别。
Neuroimage. 2013 Nov 15;82:403-15. doi: 10.1016/j.neuroimage.2013.05.081. Epub 2013 Jun 4.
5
Potential use and challenges of functional connectivity mapping in intractable epilepsy.功能连接图在难治性癫痫中的潜在应用和挑战。
Front Neurol. 2013 May 22;4:39. doi: 10.3389/fneur.2013.00039. eCollection 2013.
6
Diminished default mode network recruitment of the hippocampus and parahippocampus in temporal lobe epilepsy.颞叶癫痫中海马和旁海马默认模式网络募集减少。
J Neurosurg. 2013 Aug;119(2):288-300. doi: 10.3171/2013.3.JNS121041. Epub 2013 May 24.
7
Improved diagnosis in children with partial epilepsy using a multivariable prediction model based on EEG network characteristics.基于 EEG 网络特征的多变量预测模型提高儿童部分性癫痫的诊断。
PLoS One. 2013;8(4):e59764. doi: 10.1371/journal.pone.0059764. Epub 2013 Apr 2.
8
Imaging structural co-variance between human brain regions.人类脑区结构协变的影像。
Nat Rev Neurosci. 2013 May;14(5):322-36. doi: 10.1038/nrn3465. Epub 2013 Mar 27.
9
Connectomics and epilepsy.连接组学与癫痫
Curr Opin Neurol. 2013 Apr;26(2):186-94. doi: 10.1097/WCO.0b013e32835ee5b8.
10
Effect of lateralized temporal lobe epilepsy on the default mode network.优势侧颞叶癫癎对默认模式网络的影响。
Epilepsy Behav. 2012 Nov;25(3):350-7. doi: 10.1016/j.yebeh.2012.07.019. Epub 2012 Oct 24.

图论在颞叶癫痫病理生理学中的研究发现。

Graph theory findings in the pathophysiology of temporal lobe epilepsy.

机构信息

Department of Statistics, Rice University, Houston, TX, USA.

Department of Neurology, Baylor College of Medicine, Houston, TX, USA; Neurology Care Line, VA Medical Center, Houston, TX, USA.

出版信息

Clin Neurophysiol. 2014 Jul;125(7):1295-305. doi: 10.1016/j.clinph.2014.04.004. Epub 2014 Apr 21.

DOI:10.1016/j.clinph.2014.04.004
PMID:24831083
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4281254/
Abstract

Temporal lobe epilepsy (TLE) is the most common form of adult epilepsy. Accumulating evidence has shown that TLE is a disorder of abnormal epileptogenic networks, rather than focal sources. Graph theory allows for a network-based representation of TLE brain networks, and has potential to illuminate characteristics of brain topology conducive to TLE pathophysiology, including seizure initiation and spread. We review basic concepts which we believe will prove helpful in interpreting results rapidly emerging from graph theory research in TLE. In addition, we summarize the current state of graph theory findings in TLE as they pertain its pathophysiology. Several common findings have emerged from the many modalities which have been used to study TLE using graph theory, including structural MRI, diffusion tensor imaging, surface EEG, intracranial EEG, magnetoencephalography, functional MRI, cell cultures, simulated models, and mouse models, involving increased regularity of the interictal network configuration, altered local segregation and global integration of the TLE network, and network reorganization of temporal lobe and limbic structures. As different modalities provide different views of the same phenomenon, future studies integrating data from multiple modalities are needed to clarify findings and contribute to the formation of a coherent theory on the pathophysiology of TLE.

摘要

颞叶癫痫(TLE)是成人癫痫中最常见的形式。越来越多的证据表明,TLE 是异常致痫网络的紊乱,而不是局灶性起源。图论允许对 TLE 脑网络进行基于网络的表示,并且有可能阐明有利于 TLE 病理生理学的脑拓扑特征,包括发作起始和传播。我们回顾了基本概念,我们相信这些概念将有助于快速解释图论研究中迅速出现的结果。此外,我们总结了图论在 TLE 病理生理学中的当前研究状态。从使用图论研究 TLE 的多种模态中已经出现了一些常见的发现,包括结构 MRI、弥散张量成像、表面 EEG、颅内 EEG、脑磁图、功能 MRI、细胞培养、模拟模型和小鼠模型,包括发作间期网络结构的规则性增加、TLE 网络的局部分离和全局整合改变以及颞叶和边缘结构的网络重组。由于不同的模态提供了同一现象的不同视角,因此需要整合来自多种模态的数据的未来研究来澄清发现,并有助于形成关于 TLE 病理生理学的连贯理论。