Network Connectivity in Epilepsy: Resting State fMRI and EEG-fMRI Contributions.
Network Connectivity in Epilepsy: Resting State fMRI and EEG-fMRI Contributions.
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DOI：
10.3389/fneur.2014.00093
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发表时间：
2014
影响因子：
3.4
通讯作者：
Carmichael DW
中科院分区：
文献类型：
--
作者：
Centeno M;Carmichael DW
越来越多的证据指向癫痫核心现象背后的大规模网络，从癫痫发作到认知功能障碍或对治疗的反应。癫痫网络的研究已成为深入了解该疾病的关键概念。功能成像可以提供有价值的信息来表征网络功能障碍;特别是静息态fMRI（RS-fMRI），它越来越多地被应用于研究许多疾病中的脑网络。在癫痫患者中，来自RS-fMRI的网络连接发现了一些网络的连接异常;这些网络包括癫痫，认知和感觉处理网络。然而，在大多数这些研究中，癫痫瞬态的网络连接的影响被忽视。脑电功能磁共振成像经常显示与癫痫瞬变相关的网络，在许多情况下与RS研究中显示的异常一致。这一点在RS-fMRI研究中检测到的网络异常癫痫瞬态的相关作用。在这篇综述中，我们总结了这两种技术并排报告的网络异常，提供了它们重叠发现的证据，并讨论了它们在每种技术方法论背景下的意义。与连接性变化相关的许多临床相关因素反过来又与癫痫瞬变频率的变化相关。这些因素包括癫痫的不同方面，从治疗效果、认知过程或不同警觉状态之间的过渡（即，清醒-睡眠转换）。对于RS-fMRI成为一个更有效的工具，以调查临床相关方面的癫痫，它是必要的，以了解连接的变化与癫痫瞬变，与其他临床相关因素和它们之间的相互作用，这代表了在目前的文献差距。我们提出了一个框架，癫痫患者的网络连接的调查，可以整合癫痫过程发生在不同的时间尺度，如癫痫瞬态和疾病持续时间和这种方法的影响进行了讨论。
There is a growing body of evidence pointing toward large-scale networks underlying the core phenomena in epilepsy, from seizure generation to cognitive dysfunction or response to treatment. The investigation of networks in epilepsy has become a key concept to unlock a deeper understanding of the disease. Functional imaging can provide valuable information to characterize network dysfunction; in particular resting state fMRI (RS-fMRI), which is increasingly being applied to study brain networks in a number of diseases. In patients with epilepsy, network connectivity derived from RS-fMRI has found connectivity abnormalities in a number of networks; these include the epileptogenic, cognitive and sensory processing networks. However, in majority of these studies, the effect of epileptic transients in the connectivity of networks has been neglected. EEG–fMRI has frequently shown networks related to epileptic transients that in many cases are concordant with the abnormalities shown in RS studies. This points toward a relevant role of epileptic transients in the network abnormalities detected in RS-fMRI studies. In this review, we summarize the network abnormalities reported by these two techniques side by side, provide evidence of their overlapping findings, and discuss their significance in the context of the methodology of each technique. A number of clinically relevant factors that have been associated with connectivity changes are in turn associated with changes in the frequency of epileptic transients. These factors include different aspects of epilepsy ranging from treatment effects, cognitive processes, or transition between different alertness states (i.e., awake–sleep transition). For RS-fMRI to become a more effective tool to investigate clinically relevant aspects of epilepsy it is necessary to understand connectivity changes associated with epileptic transients, those associated with other clinically relevant factors and the interaction between them, which represents a gap in the current literature. We propose a framework for the investigation of network connectivity in patients with epilepsy that can integrate epileptic processes that occur across different time scales such as epileptic transients and disease duration and the implications of this approach are discussed.
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DOI：
10.1073/pnas.0504136102
发表时间：
2005-07-05
影响因子：
11.1
作者：
Fox, MD;Snyder, AZ;Raichle, ME
通讯作者：
Raichle, ME
影响因子：
4.8
作者：
Doucet, Gaelle;Osipowicz, Karol;Sharan, Ashwini;Sperling, Michael R.;Tracy, Joseph I.
通讯作者：
Tracy, Joseph I.
影响因子：
3.2
作者：
Daunizeau J;Lemieux L;Vaudano AE;Friston KJ;Stephan KE
通讯作者：
Stephan KE
影响因子：
5.7
作者：
Britz, Juliane;Van De Ville, Dimitri;Michel, Christoph M.
通讯作者：
Michel, Christoph M.
影响因子：
4.8
作者：
Chaudhary, Umair J.;Centeno, Maria;Koepp, Matthias
通讯作者：
Koepp, Matthias