Onias Heloisa, Viol Aline, Palhano-Fontes Fernanda, Andrade Katia C, Sturzbecher Marcio, Viswanathan Gandhimohan, de Araujo Draulio B
Brain Institute/Onofre Lopes University Hospital, Federal University of Rio Grande do Norte (UFRN), Natal, Brazil.
Department of Physics, UFRN, Natal, Brazil.
Epilepsy Behav. 2014 Sep;38:71-80. doi: 10.1016/j.yebeh.2013.11.019. Epub 2013 Dec 27.
Functional magnetic resonance imaging (fMRI) has just completed 20 years of existence. It currently serves as a research tool in a broad range of human brain studies in normal and pathological conditions, as is the case of epilepsy. To date, most fMRI studies aimed at characterizing brain activity in response to various active paradigms. More recently, a number of strategies have been used to characterize the low-frequency oscillations of the ongoing fMRI signals when individuals are at rest. These datasets have been largely analyzed in the context of functional connectivity, which inspects the covariance of fMRI signals from different areas of the brain. In addition, resting state fMRI is progressively being used to evaluate complex network features of the brain. These strategies have been applied to a number of different problems in neuroscience, which include diseases such as Alzheimer's, schizophrenia, and epilepsy. Hence, we herein aimed at introducing the subject of complex network and how to use it for the analysis of fMRI data. This appears to be a promising strategy to be used in clinical epilepsy. Therefore, we also review the recent literature that has applied these ideas to the analysis of fMRI data in patients with epilepsy.
功能磁共振成像（fMRI）问世已有20年。目前，它在正常和病理状态下的广泛人脑研究中作为一种研究工具，癫痫研究就是如此。迄今为止，大多数功能磁共振成像研究旨在描述大脑对各种激活范式的反应活动。最近，当个体处于静息状态时，已采用多种策略来描述功能磁共振成像信号的低频振荡。这些数据集大多在功能连接的背景下进行分析，功能连接检查大脑不同区域功能磁共振成像信号的协方差。此外，静息态功能磁共振成像正逐渐用于评估大脑的复杂网络特征。这些策略已应用于神经科学中的许多不同问题，包括阿尔茨海默病、精神分裂症和癫痫等疾病。因此，我们在此旨在介绍复杂网络主题以及如何将其用于功能磁共振成像数据分析。这似乎是一种有望用于临床癫痫的策略。因此，我们还回顾了最近将这些理念应用于癫痫患者功能磁共振成像数据分析的文献。
